Posts Tagged ‘Contact Data’

Your Contact Data Doesn’t Keep Fresh Very Long

Your company’s revenue most likely depends on having accurate, genuine and up-to-date contact data. In fact, this is probably one of the biggest factors in the overall ROI of your contact database. In light of this, it is essential to have a clear understanding of how and why contact data decays – and more importantly, what you can do about it.

Contact data decay: a fact of life

A widely held figure nowadays is that business contact databases decay at a rate of about 30% per year on average. And much of this decay takes place for reasons that you have no control over. For example, look at some of the things that can happen with B2B contact data alone:

  • People move and change jobs
  • Contacts get promoted to new responsibilities
  • Your contact’s organization moved to a new headquarters across town
  • Life goes on and contacts get married, change careers or retire
  • Corporate changes such as layoffs or downsizing impact your active contacts
  • Product lines or service areas change or become obsolete
  • Even when people’s jobs stay the same, their phone numbers or email addresses change

And when you look at marketing to consumers, issues such as data privacy compliance and business reputation come into play as well. That phone number you contacted for your last marketing campaign may have opted in at one point, but now it has changed hands to a new wireless user who didn’t give you permission to contact them – and now you have run afoul of the US Telephone Consumer Protection Act (TCPA), with liability for stiff fines. And then there is the question of reputational damage from using outdated contact data – no one likes to receive unsolicited marketing messages.

This means that good data hygiene is no longer an option for companies of any size. Aside from risks such as compliance penalties and reputational damage, data decay has a real competitive impact on the return on your marketing efforts: for example, in 2017 the ROI of email marketing alone was $41 per $1 spent, with other channels such as mobile marketing also in double digits.

Today’s contact data needs to be seen for what it is: a perishable asset that requires regular maintenance.

Managing changes in contact data

Thankfully automated validation tools can help make solving contact data decay a regular part of your business process. Here are some of the options that you have with our products:

  • Individual component validation products such as DOTS Address Validation, DOTS Email Validation and DOTS GeoPhone can validate component contact information and verify that it is still accurate.
  • Bundled validation tools such as DOTS Lead Validation cross-validates and corrects your contact data against numerous data points, returning a quantitative confidence score that alerts you to changes in this data.
  • For important contacts that you wish to maintain correspondence with, our USPS-approved DOTS NCOA Live product links with official change-of-address data to keep your contact addresses up to date.

Our data quality tools are available through API interfaces that integrate directly with popular CRM and marketing automation platforms, as well as through cloud connectors, batch list processing and quick lookup options. Want to learn more about how to solve your own specific contact data issues? Our knowledgeable data quality professionals are happy to help: contact us anytime for a friendly, no-pressure consultation.

Spring Cleaning for Your Data

Cleaning up has always been a virtue. Thanks to Netflix and bestselling Japanese organizing expert Marie Kondo, who preaches a mindful approach to better living through tidying up, it has now also become a major viral trend. Today, I would like to help you explore another path to inner joy and peace in your business: cleaning up your contact data.

You see, your contact data assets are a bit like most people’s closets: they start off being functional, but without the right kind of effort, they decompose into clutter over time. (Over 70% of this data changes every year as people move, change jobs, their companies merge, and more.) Unfortunately, this clutter can cost you – in time, wasted marketing efforts, or even severe compliance penalties for unwanted marketing contacts. So here is a three-step process that will help ensure that your contact data is always genuine, accurate, and up-to-date.

First: Getting it Right at the Time of Data Acquisition

What is one of the more common sources of contact data error? Acquiring it in the first place. Most organizations have multiple touch points where contact data enters their system: web pages, inbound customer inquiries, lead processing, and more. Customers fat-finger their addresses or contact information, data entry team members are human and make mistakes, and sometimes fraud or fakery is even involved.

One productive solution to this is to use API-based tools the plug in to your sales, marketing or CRM platforms, to seamlessly help ensure contact data quality on the front end. For example, address validation services check inbound address data against USPS, international and other databases to ensure address accuracy or correct them if needed. For other forms of contact data, phone validation can identify a numbers owner and validity, as well as carrier, line type and geolocation data, while email validation verifies email validity and corrects things like common typos.

Other API tools bundle advanced services such as validating the quality of incoming leads, appending contact phone numbers, or linking your contacts to demographics data for business analysis or compliance purposes. Whatever level you need, implementing API-based services like these in your business automation platforms helps ensure getting the right contact data every time, at the point of entry.

Second: Cleaning Your Database

Congratulations – you’ve now entered accurate, validated contact data. Which leads to the next issue: practically the minute you get up to grab some coffee, your contact data assets are starting to decay. So periodically, it makes sense to bring this data back in line with reality, to maintain its usefulness for functions like market analysis, business intelligence, campaign planning and more.

In situations like these, batch or list processing services often represent a convenient way to clean an entire contact database at once. Our own batch services can process an entire list or database with little or no programming required. Tools like these are often a smart and simple way to make good data hygiene part of your regular routine.

Third: Lather, Rinse, Repeat

How often should you clean up your data? Repeat after me: every time you use it. Here’s why: accurate contact data may be important for things like market planning and business analytics, but it is absolutely critical when you actually get in touch with people on your lists. Direct mail campaigns have human and material costs tied in with bad address data, outbound telemarketing to changed numbers potentially risk severe penalties from the Telephone Consumer Protection Act (TCPA), and unwanted email contact can get you blacklisted.

The same tools you use to validate and clean your data are at your service here, each and every time you run a campaign or contact your customers. But here, the solution is as much organizational as technical: make sure someone is “on first” for ensuring your ongoing data quality and data governance.

Questions? We Can Help!

When it comes to cleaning your data, we actually do one thing much better than Marie Kondo: her bestselling book sprang from an infamous months-long waiting list for her organizing services, but our knowledgeable team of data experts will return your call in just 90 minutes or less! So whether it’s questions on international data, API interfaces, or simply discussing what strategy works best for you, contact us anytime and let us help you discover the life-changing magic of tidying up your data.

Photo of a judge's gavel in front of a Canadian

Canada’s New PIPEDA Law: What It Means for You

If you do business with customers in Canada, an important new privacy law has taken effect as of November 2018: The Personal Information Protection and Electronic Documents Act (PIPEDA). People are already starting to refer to PIPEDA as Canada’s version of GDPR, the sweeping privacy regulations implemented in May 2018 by the European Union.

There are some common denominators between PIPEDA and GDPR. Both mandate acquiring explicit customer permission for the use of personal information, as well as disclosure of how this information will be used. Both also require breach notification in cases where personal information has been compromised: in Canada’s case, notification must be made to that country’s Privacy Commissioner a well as to affected parties. Other common threads include requirements to maintain accurate and secure data, giving individuals access to their own data, and the need for a formal compliance officer.

Getting started with PIPEDA

The Canadian government has published a downloadable guide to help organizations understand and become compliant with the new PIPEDA law, entitled Privacy Toolkit: A Guide for Businesses And Organizations. It provides an overview of the law and its principles, together with descriptions of its complaint handling procedures and audit provisions.

PIPEDA compliance revolves around ten principles that businesses must follow:

1. Accountability. Comply with these principles, appoint an individual responsible for compliance, protect information handled by you and third parties, and develop policies and practices for personal information.

2. Identifying purposes. Document and inform individuals why information is being collected, before or at the time it is collected.

3. Valid, informed consent. Specify what information is being collected, used or disclosed along with its purpose, and obtain explicit consent – before collection, and again if a new use of their personal information is identified.

4. Limiting collection. Do not collect personal information indiscriminately, or deceive or mislead individuals about the reasons for collecting personal information.

5. Limiting use, disclosure, and retention. Use or disclose personal information only for the purpose for which it was collected or consented to, keep personal information only as long as necessary, and have policies for the retention and destruction of information that is no longer required.

6. Accuracy. Minimize the possibility of using incorrect information when making a decision about a person or when disclosing information to third parties.

7. Safeguards. Protect personal information against loss or theft, as well as unauthorized access, disclosure, copying, use or modification.

8. Openness. Inform customers, clients and employees that you have policies and practices for the management of personal information, and make them understandable and easily available.

9. Individual access. Provide individuals with access to their personal information on file with you, along with how and to whom it has been disclosed, as well as the ability to correct or amend this information.

10. Challenging compliance. Develop simple and easily accessible complaint procedures, inform complainants of their avenues of recourse, investigate all complaints received, and take appropriate measures to correct information handling practices and policies.

Some important distinctions

While the goals of PIPEDA are very similar to those of other privacy regulations such as GDPR – and many of the same compliance strategies will apply to both markets – there are some key differences with Canada’s new regulations. Here are two of the more important ones:

A focus on mediation. Compared with other global privacy regulations, which often carry stiff financial penalties, PIPEDA is designed to enforce privacy laws through mediation where possible. However, this does not mean that the law is without teeth: both complainants and Canada’s Privacy Commissioner can apply for a Federal Court hearing and potential damage awards. In addition, specific violations such as intentional destruction of requested personal information or whistleblower retaliation may be prosecuted as offenses.

Limits on scope for employee data. Unlike GDPR, the PIPEDA law’s application to employee data only applies to federally regulated entities such as banks, airlines and shipping companies (although some provinces have stricter provincial privacy laws). For consumer data, however, PIPEDA applies to personal data from all Canadians.

Knowing the location of customers is key to PIPEDA compliance

Contact data quality is no longer an option when dealing with the Canadian market. Service Objects has been at the forefront of helping firms with their compliance efforts for data privacy regulations, including flagging the geographic location of customers and prospects, which is key to getting started with any compliance effort.

Contact us for more information about how our data quality solutions can help your business.

It Don’t Mean a Thing If It Ain’t Got That Ping

How do you know if an email address is valid? There is more than one way to find out. In this article, we will show you how something we do – known as “ping testing” – makes these results much more accurate. More important, we will show you how to get the best out of these capabilities.

Email Verification 101

There are fundamentally three ways to make sure an email address is legitimate:

  • Examine the email address itself for things like proper syntax, obvious misspellings (like “gmial” instead of “gmail”), and other problems (like missing “@” symbol).
  • Compare this email address against lists of existing emails – both to see if it is a legitimate address, and also to flag known problem addresses such as spam traps, honeypots, known spammers, blacklisted addresses, and more.
  • Physically test (or “ping”) the email server, domain and address to make sure the address is valid.

All three of these checks are important in their own way. Basic address testing quickly weeds out addresses that are clearly invalid, with fast response times. List testing is also quick but often isn’t enough, because of addresses that haven’t made the list yet. (According to a report from the Radicati Group, new email addresses get created at the rate of a quarter billion per year!)

Then there is “ping” testing, which involves checking the actual email server and address for a response, which is the gold standard for determining the validity of an address. It can also be important for applications such as fraud prevention, to guard against perpetrators who create email addresses in near-real time. There are three main types of ping checks:

  • Testing an email server (STMP) to see if it is real and available.
  • Testing to see if an email address is allowing emails at the domain (DNS) level.
  • Testing to see if the address can reach an inbox.

Of course, Service Objects’ DOTS Email Validation service performs all of these checks. Now, let’s see how you can use them efficiently for your own email validation.

Here’s where you come in

Service Objects’ Email Validation capabilities give you a great deal of control over both performance levels and output tests. Here are some tips to get the most out of your email validation, taken from our developer guide:

To ping or not to ping: You can validate emails quickly – at the expense of possibly missing ping testing – by using our ValidateEmailFast operation. If a “ping” takes too long, it will not be considered in the check (and STMP data about this address will not be returned). However, be aware that this is a less accurate check.

Putting a lid on pinging. The amount of time a “ping” takes may vary widely, from nearly instant response to lengthy delays. If you are using email validation in a real-time application, or are concerned about response speed, the Timeout input variable is your friend. This value specifies how long the service is allowed to wait for all real-time network level checks to finish, such as STMP and DNS testing. Time is entered in milliseconds, with a minimum value of 200ms.

Email servers can be slow to respond to ping checks, and one of the most important aspects is how long you are willing to wait for a response. If you only wait a second or two – and you fail emails that do not respond in that time – you will get a lot of false negatives. If you can wait and/or update the results based on latent responses, you will get a more accurate verification.  If real-time responses are a priority, we recommend setting up a two-step verification process, to help mitigate slow email server response times and ensure a quality user experience.

Two-step validation. The initial step will validate the email address using real-time syntax and ping testing. Syntax issues and fast-responding email servers will provide accurate feedback, so issues can be flagged in real-time.  This allows for real-time notification of any issues, enabling user corrections before being captured by your application or CRM. The amount of time you are willing to wait should be considered in your user’s experience.

The second step is to accommodate slow-responding email servers that ‘timed-out’ in the initial step.  When capturing the email address to your database, include a Yes/No flag of whether the email validation timed-out before completing validation.  For those email addresses that timed-out, you can validate them again but with a much longer Timeout setting, allowing slower email servers time to respond and ensuring the email address has been fully validated.

Pinging isn’t perfect. Sometimes a non-existent address will still “ping” properly. Why? Because some email domains are “catch-all” domains, meaning that their servers will accept mail to any address within that domain. You can test for this using the IsCatchAllDomain output variable that comes back with your results.

Finally, remember that ping testing is not the only factor in effective email validation. Our developer guide has a wealth of tools you can use as part of your specific use case, ranging from optional email address correction to warning codes for bogus, vulgar or disposable email addresses. Check it out, or better yet, “ping” our friendly support team for expert advice. We’re always glad to help!

DOTS Name Validation 2: What Do The Scores Mean?

What’s in a name? Hopefully, valuable contact data for your business. But some names clearly contain red flags for bad data – and that’s where we come in.

Name Validation is a very effective tool for weeding out garbage, bogus and unreliable names. This service can be used in real-time while creating leads, or used to process a large list of names at once. It is great tool for cutting down on the amount of unreliable data that can be entered into a system.

This article will walk you through the different scores that the DOTS Name Validation 2 service provides, to help you get the most out of this tool. In addition to a massive list of names that we compare input names against, we also do several other checks. These scores can help identify why a particular name was considered to be invalid, as well as helping to shed some light as to what types of validation Name Validation performs.

Overall scores

One of the first things users will want to look at is the OverallNameScore value. This score represents the service overall rating for the given name. This score value ranges from 0 to 5, with 0 indicating a definitely bad name and 5 indicating a definitely good name. This is usually the first result someone might look at when determining the validity of a name.

We generate this overall score based on several other checks, validations and scores that the service can generate. However this might not be the last stop a user would make when attempting to determine if a name is valid or not. Based on your use case, you may want to look at one of the other score values our service provides, described below.

Other scores provided

The other score values that the service gives also range from 0 to 5. These values indicate the likelihood that the particular scoring category applies to that name. For example if a name received a VulgarityScore of 5, then that name would definitely have some type of vulgar word present. Below are the different scoring categories that the service provides.


As mentioned above, this score indicates the likelihood that a vulgar word is present in the input name. This score highly affects the overall score, as this is a key item used to sniff out bad or unprofessional name information.


This rating represents the likelihood that the input name provided is a known celebrity. This field will also work with fictional celebrities, so names like “Micky Mouse” and “Homer Simpson” will receive high Celebrity scores, as well as real life celebrities like “Tom Cruise” or “Madonna”.


The BogusScore field will let the user know if a given name is simply just a word or phrase that wouldn’t make sense. For example, single words or phrases that aren’t names (such as “Sandwich” or “The Quick Brown Fox”) will receive a high bogus score.


Random key strokes or inputs that are not valid words will receive a high Garbage score. This would correspond to input like “asdfg” or any other series of random letters, keystrokes and input that doesn’t make a whole lot of sense as a name.


Finally, we provide scores that indicate the likelihood that the input text is a dictionary word. These tend to have less weight on the overall score, as there are quite a few legitimate dictionary terms that can be considered last names. For example, the name “Park” is a relatively common last name, so it will receive a lower dictionary score of 1, while a word like “Fluorescent” would receive a high dictionary score because it is less common.

As with any of our services, there can always be specific use cases that may require some more information about how our services work. Service Objects has a team of customer focused people standing by to help you get the validated data you need. If you have any questions about our services, don’t hesitate to reach out to us – we would love to help you get the validated data you need!

Help Santa Check It Twice: A Holiday Addressing Gift for You!

The holidays are fast approaching. Soon you’ll be celebrating the season and sending holiday gift baskets and cards to people you have enjoyed working with this year. So here at Service Objects, we’ve teamed up with none other than Santa Claus himself, with a great gift for you! A free web-based portal where Santa will help you verify addresses online, powered by our Address Validation capabilities.

It’s ready to use right now.

If you have never used online address validation before – or even if you have, and want a quick, fun way to check a few addresses – Santa is here to help. Take a look:

Use this form to give him a delivery address – anywhere in the world where reindeer fly, business or personal – and then he and his helpers will be right back with one of the following results:

Finally, a little bit of fine print. You will be allowed to look up a maximum of 10 addresses using this tool. This screen will allow you to look up one address at a time, including business names where needed, but bear in mind that we offer convenient API and list-processing versions of these tools as well. If you need to look up more addresses, no worries – a convenient link will lead you to learn more about our full-feature capabilities, as well as additional information about our phone and email validation capabilities.

We’re hoping that once you get a taste of some holiday address verification – and find out how simple it is to implement for your business – you’ll want to have these capabilities for yourself, all year round. (In fact, Santa confided to us that he and Mrs. Claus will keep using Service Objects tools to improve his own delivery accuracy every Christmas from here, because sometimes even reindeer are no match for automated shipping.) Want to learn more? Talk to our friendly technical experts, and we’ll make it a happy holiday season for you too!

Cyber Monday is Coming. Is Your Business Ready?

In 2017, Cyber Monday sales reached an all-time high – and trends show that we may see another record-breaking year. Service Objects broke its own record last Cyber Monday with the most transactions in a single day. Why were our data validation tools so in-demand? Because excited customers rushing to score online deals make lots of data entry errors. Capturing authentic contact data helps businesses avoid mistakes in the ordering and shipping processes and prepares them for future opportunities, like marketing campaigns and additional sales.

Data validation services enhance data quality in real-time by identifying and correcting inaccuracies. For example, order validation not only verifies that an order is legitimate, it also corrects and appends contact data like name, address, email, and phone number using up-to-date, proprietary databases. Cross-referencing IP, address, phone, email, and credit card information helps every aspect of your business – from making ordering and shipping efficient to helping flag identify fraud and verifying email addresses for future communications.

Data quality at point of sale

Validating an order at point of sale helps smooth out transactions for customers by suggesting more accurate addresses and updating typos. Adobe Insights reported that Cyber Monday sales grew 16.8% from 2016 to 2017 reaching $6.59 billion, $2 billion of which were completed on a mobile device. Because we make five times more mistakes on mobile than desktop, fat-fingered typos and autocorrect issues are becoming more prevalent.

Order Validation can also help prevent fraud in real-time by verifying that customers are legitimate through cross-checks of contact data, IP address, and credit card information. These verifications can flag suspicious activity related to identity theft and high-risk prepaid cards, which helps avoid related chargebacks. Fraud hurts businesses through lost product, money, and hours managing the fallout – the best way to avoid those costs is through preventative measures, like validating orders before shipping.

Data quality and order fulfillment

With last year’s record sales came unprecedented shipping demand, and shippers like UPS struggled to meet delivery expectations all over the country. Customers anxiously awaiting their packages took to Facebook and Twitter to air their grievances, but while UPS was the bottleneck, many angry tweets were directed at vendors.

Given the rising trend in Cyber Monday sales over the years, it’s likely this year will bring even more orders, shipments, and delivery-related problems. Using a CASS certified address validation service, like the one incorporated in Service Objects’ DOTS Order Validation API, can help ensure that your shipping addresses are correct and deliverable. The service can be implemented to help customers self-correct inaccurate information before submitting their order, or can be used post-transaction to ensure accuracy by finding issues and suggesting corrections before shipping.

Customer service benefits from high quality data

The holidays are a stressful time, and shoppers have hard deadlines when ordering gifts in November and December. According to the National Retail Federation, 38% of consumers expect free two-day delivery when making online purchases. Address verification helps meet these expectations, cutting down on service inquiries for delayed packages. Order Validation also validates email addresses and phone numbers, ensuring notifications reach shoppers and giving your customer service representatives everything they need to communicate effectively.

Precise contact data saves your customer service team time troubleshooting and appeasing upset callers, strengthens your relationship to promote repeat business, and helps you manage your reputation. And, in the off-chance that something does go wrong, your team will have the most up-to-date order information to handle the call and assure your customers that you care.

High risk days require high quality data

Data quality plays an important role in managing the risks of high-volume transaction days like Cyber Monday. The best way to ensure contact data doesn’t get in the way of your biggest sales day is by validating and verifying transactions with a service like Order Validation. You can even try it out today with a free trial key.

Contact Data Spam: A Lesson from Google Maps

We have spoken often on these pages about the importance of validating your contact data, to make sure you have a valid address and a quality lead. Whether it is a mistyped ZIP code, a lead pretending to be Donald Duck to fake out your marketing team, or a phony email address used to commit fraud, problems can and do occur. It takes planning to stay one step ahead of the bad guys or the bad data.

Which is why we were fascinated to hear about a new cottage industry that has sprung up in recent years: fake listings on Google Maps. By cataloging the streets and business listings of much of the planet, Google Maps has often become a go-to resource for finding a business. Unfortunately, this has also made this platform a tempting target for shady operators and unfair competitors.

A few years ago, some enthusiasts succeeded in pranking Google Maps with obviously fake business listings, just to show that they could do it. One hacker even managed to plant fake contact information for the FBI and the Secret Service, forwarding callers to the actual agencies while surreptitiously recording the calls. In cases like these, the goal was to try and get Google’s attention about flaws in their system and verification procedures.

Unfortunately, fake listings have also been exploited by people with darker motives than showing off their hacking talents. Here are some examples:

Contractor fraud: Some types of businesses, such as locksmiths or plumbers, are ripe for shady contractors who come to your home and then charge exorbitant prices. By placing a listing in your neighborhood using a phony address, they are able to swoop down from anywhere on unsuspecting homeowners. According to Google, this represents about 40% of their fake listings.

Fake reviews: In this case, real businesses have shadowy people post phony reviews to disparage their competitors or build up their own business – or phony businesses run by fraudsters use fake reviews to give themselves an air of legitimacy. Despite volunteer fraud-hunters and the threat of FTC fines, a listing on Google Maps may not accurately reflect a business’s true ratings.

Squatter’s rights: Here a scammer claims a listing for an actual business such as a restaurant, often pocketing online referral fees for customers who actually found this business via organic search. Google notes that 1 out of 10 of its fake Google Maps listing fall under this category.

To be fair, Google has made attempts to keep on top of this problem. In a 2017 report on one of their blogs, they note that that have tightened up their procedures for verifying new listings, and now claim to detect and disable 85% of fraudulent ones before they are posted – resulting in a 70% reduction in such listings from their peak in 2015. However, while pointing out that less than 0.5% of searches today are fraudulent, they acknowledge that they still aren’t perfect.

The lesson here? As former US President Ronald Reagan used to say at the height of the Cold War, “Trust but verify.” To which we would add, keep your data quality practices up-to-date with your own contact data assets. Good luck, and be careful out there!

Why Google Maps Isn’t Perfect

Google Maps is an amazing service. Much of the civilized world has now been mapped through its data sources, ranging from satellite data to its ubiquitous camera-mounted vehicles. The result is a tool that allows you to find a location, link to local businesses, or virtually drive anywhere from downtown Paris to rural Mexico.

However, if you use Google Maps to validate addresses in a business, it is a little like trying to find a lifelong mate for your grandmother on Tinder: it is possible, but with a tool that wasn’t necessarily designed for that purpose. So let’s look at the differences between this service versus professional address validation and geolocation tools.

Google maps versus address validation

Let’s start with the most important difference: Google Maps is very complete, but sometimes wrong. How wrong? Mistakes can range from bad directions, wrong street names, and bad addresses to wrong country borders, omitting large cities and everything in between. Once, in a mistake Google acknowledged, a Texas construction firm even demolished the wrong house when Google Maps sent them there.

Another difference is where the data comes from in the first place. Google Maps uses a variety of sources including administrative boundaries, parcels, topographic features, points of interest, trails, road features, and address points or ranges. It also accepts data from “authoritative” organizations as well as individuals, subject to a vetting process. As a result, however, it is possible for mistakes to be introduced and/or made when aggregating or consolidating the data.

Finally and perhaps most importantly, Google does not know exactly where every address is. When it does not have rooftop level data to pinpoint the address it will estimate where an address is using techniques such as address interpolation. Sometimes an address may also be wrong because an individual claimed the location and entered the information incorrectly, or changes such as new municipal or postcode boundaries were not updated.

What the pros do

By comparison, professional address validation and geolocation tools don’t guess at results, because their focus is more on accuracy. Tools such as Service Objects’ DOTS Address Validation and Address Geocode capabilities are focused on delivering an accurate and precise response, versus settling for “close enough.”

To get specific, if our address validation tool cannot correct and validate that an address is real, we will fail it and will not guess. By comparison, Google may just use the closest approximation, which can lead to issues. Similar rules apply to geocoding latitude and longitude coordinates from address data: where necessary, Service Objects will move down a gradient of accuracy/precision, but will still often be closer to the correct coordinates than Google.

Another key difference lies in our data sources. For example, DOTS Address Validation uses continually updated USPS, Canada Post and international data in combination with proprietary databases, to create near-perfect match accuracy. Likewise, for Address Geocoding addresses and coordinates are validated against our master database, the US Census Bureau, TIGER®/Line file, USPS® ZIP+4 tables, and other proprietary databases, ultimately yielding a 99.8% match rate accuracy when translating an address to its latitude and longitude coordinates.

Use the right tool

We like Google Maps. Without it we wouldn’t be able to easily visit major world cities online, find a good sushi bar near our hotel, or get directions to visit Aunt Mildred. But when you need professional-grade accuracy in address and location data for your business, be sure to use the right tools. Need more specifics? Contact us for a no-pressure consultation, and our team will be happy to explore your specific needs.

Why Data Quality Isn’t a Do-It-Yourself Project

Here is a question that potential customers often ask: is it easier or more cost-effective to use data validation services such as ours, versus building and maintaining in-house capabilities?

We are a little biased, of course – but with good reason. Let’s look at why our services are a lot easier to use versus in-house coding, and save you money in the process.

Collecting and using information is a crucial part of most business workflows. This could be as simple as taking a name for an order of a burger and fries, or as complex as gathering every available data point from a client. Either way, companies often find themselves with databases comprised of client info. This data is a valuable business asset, and at the same time often the subject of controversy, misuse, or even data privacy laws.

The collection and use of client information carries an important responsibility when it comes to security, utility, and accuracy. If you find yourself tasked with keeping your data genuine, accurate, and up-to-date, let’s compare the resources you would need for creating your own data validation solution versus using a quality third-party service.

Using your resources

First, let’s look at some of the resources you would need for your own solution:

Human. The development, testing, deployment, and maintenance of an in-house solution requires multiple teams to do properly, including software engineers, quality assurance engineers, database engineers, and system administrators. As the number of data points you collect increases, so does the complexity of these human resources.

Financial. In addition to the inherent cost of employing a team of data validation experts, there is the cost of acquiring access to verified and continually updated lists of data (address, phone, name, etc.) that you can cross-validate your data against.

Proficiency. Consider how long it would take to develop necessary expertise in the data validation field. (At Service Objects, for example, our engineers have spent 15+ years increasing their proficiency in this space, and there is still more to learn!) There is a constant need to gain more knowledge and translate that into new and improved data validation services.

Security. Keeping your sensitive data secure is important, and often requires the services of a team. An even worse cost can be failing to take the necessary steps to ensure privacy, which can even lead to legal troubles. Some environments need as much as bank grade security to protect their information.

Using our resources

The points above are meant to show that any data validation solution, even an in-house one, carries costs with it. Now, let’s look at what you get in return for the relatively small cost of a third-party solution such as ours for data validation:

Done-for-you capabilities. When you use services such as our flagship Address Validation, Lead Validation, geocoding, or others, you leverage all the capabilities we have in place: CASS-certifiedTM validation against continually updated USPS data, lead quality scores computed from over 100 data points, cross-correlation against geographic or demographic data, global reach, and much, much more.

Easy interfacing. We have multiple levels of interfacing, ranging from easy to really easy. For small or well-defined jobs, our batch list processing capabilities can clean or process your data with no programming required. Or integrate our capabilities directly into your platform using enterprise-grade RESTful API calls, or cloud connectors interfacing to popular marketing, sales and e-commerce platforms. You also spot-check specific data online – and sample it right now if you wish, with no registration required!

Support and documentation. Our experts are at your service anytime, including 24/7/365 access in an emergency. And we combine this with extensive developer guides and documentation. We are proud of our support, and equally proud of all the customers who never even need to contact us.

Quality. Our services come with a 99.999% uptime guarantee – if you’re counting, that means less than a minute and a half per day on average. We employ multiple failover servers to make sure we are here when you need us.

We aren’t trying to say that creating your own in-house data validation solution can’t be done. But for most people, it is a huge job that comes at the expense of multiple company resources. This is where we come in at Service Objects, for over 2500 companies – including some of the nation’s biggest brands, like Amazon, American Express, and Microsoft.

The combination of smart data collection/storage choices on your end and the expert knowledge we’ve gained over 15 years in the data validation space can help to ensure your data is accurate, genuine and up-to-date. Be sure to look at the real costs of ensuring your data quality, talk with us, and then leave the fuss of maintaining software and security updates and researching and developing new data validation techniques to us.

More Than an Address: What is a Delivery Point?

Most people think that they mail or ship things to addresses – and they would be wrong. And the reasons for this might be very important to your bottom line.

First, let’s look at one actual address here in our native Santa Barbara, California: 1540 N. Ontare Road.


This address is quite real. (In fact, its property is currently for sale on But we wouldn’t recommend shipping a package there – at least not yet – because at the moment it is a vacant 20-acre lot.

Now, let’s look at another address: 350 Fifth Avenue, New York, NY:


This is also a valid address: it is the famous Empire State Building, one of the tallest buildings in the United States. We wouldn’t recommend using this address by itself for shipping a package either, because without more detail such as a suite number, there is no way of knowing which of its more than 1000 businesses serves as the destination. (In fact, the address itself isn’t even that important here: this building is large enough to have its own ZIP code, 10118.)

Understanding delivery points

These are both examples of the differences between an address and a delivery point. Addresses simply describe the location of a piece of geography, while delivery points are the lifeblood of physical shipments: they are approved unique locations served by delivery services such as the U.S. Postal Service. Many people think they are shipping to addresses, but they are actually shipping to delivery points.

This underscores the importance of delivery point validation, whether you are doing a direct mail marketing campaign or shipping products to customers. There are several possible points of failure where a delivery point may be invalid or undeliverable:

  • The physical address may be incorrect
  • The physical address may be correct, but undeliverable (such as our vacant lot example above)
  • The physical address alone may be insufficient, such as a multi-tenant building
  • Additional delivery point information may be incorrect or invalid: for example, a fourth-floor suite in a three-story building, or a nonexistent suite number
  • The delivery point information may be completely correct, but correspond to the wrong recipient

So from here, your new mantra should be: is it deliverable?

Address validation: the key to accurate delivery points

This is where our flagship address validation tools come in. Available for US, Canadian and international markets, these services provide real-time verification of deliverability – including flagging of vacancy, returned mail, and general delivery addresses – to ensure accurate contact data at the time of data entry or use.

These tools instantly verify, correct and append delivery addresses, using APIs that integrate with your CRM or marketing automation platforms, cloud connectors, or convenient batch services for cleaning your databases without the need for programming. Whichever approach you use, you will leverage our vast infrastructure of up-to-the-minute data from the USPS, Canada Post and other sources, along with sophisticated and accurate address verification capabilities.

Our DOTS Address Validation – US 3 service, for example, provides near-perfect match accuracy with updates mirroring the USPS, and sub-second response times that allow you to validate live customer input in real time. And our industry-leading GetBestMatches operation combines Delivery Point Validation (DPV) to verify an address is deliverable, Residential Delivery Indicator (RDI) to identify residential or business, and SuiteLink (SLK) to add secondary suite information for businesses, all with a single API call to our USPS CASS Certified™ engine.

Want to learn more about engineering delivery point validation into your operations? Contact us for friendly, knowledgeable answers from our experienced team of data quality professionals.

Data Quality, AI, and the Future

What do you think of when you hear the term “artificial intelligence” (or AI for short)? For many people, it conjures up images of robots, science fiction, and movies like “2001 – A Space Odyssey,” where an evil computer wouldn’t let the hero back on his spaceship to preserve itself.

Real AI is a little less dramatic than that, but still pretty exciting. At its root, it involves using machine learning – often based on large samples of big data – to automate decision-making processes. Some of the more public examples of AI are when computers square off against human chess masters or diagnose complex problems with machinery. And you already use AI every time you ask your phone for directions or a spam filter keeps junk mail from reaching your inbox.

In the area of contact marketing and customer relationship management, some experts are now talking about using AI for applications such as predictive marketing, automated targeting, and personalized content creation. Many of these applications are still in the future, but product introductions aimed at early adopters are already making their way to the market.

Data quality is key in AI

One thing nearly everyone agrees on, however, is that data quality is a potential roadblock for AI. Even a small amount of bad data can easily steer a machine learning algorithm wrong. Imagine, for example, you are trying to do demographic targeting – but given the percentage of contact data that normally goes bad in the course of a year, your AI engine may soon be pitching winter coats to prospects in Miami.

Here are what some leadership voices in the industry are saying about the data quality problem in AI:

  • Speaking at a recent Salesforce conference, Leadspace CEO Doug Bewsher described data quality as “AI’s Achilles heel,” going on to note that its effectiveness is crippled if you try using it with static CRM contact data or purchased datasets.
  • Information Week columnist Jessica Davis states in an opinion piece that “Data quality is really the foundation of your data and analytics program, whether it’s being used for reports and business intelligence or for more advanced AI and related technologies.”
  • A recent Compliance Week article calls data quality “the fuel that makes AI run,” noting that centralized data management will increasingly become a key issue in preventing “silos” of incompatible information.

The ROI of accurate and up-to-date contact data is larger than ever

Naturally, this issue lies right in our wheelhouse. For years, we have been preaching the importance of data quality and data governance for contact data – particularly given the costs of bad data in time, human effort, marketing effectiveness, and customer reputation. But in an era where automation continues to march on, the ROI of good contact data is now growing larger than ever.

We aren’t predicting a world where your marketing efforts will be taken over by a robot – not anytime soon, at least. But AI is a very real trend, one which deserves your attention from here. Some exciting developments are on the horizon in marketing automation, and we are looking forward to what evolves over the next few years.

Find out more about how data quality and contact validation can help your business by visiting the Solutions section of our website.

Address Detective – Why it is so cool!

Service Objects has been providing USPS CASS-Certified Address Validation services for over 17 years. Over this time, we have developed one of the best systems for validating, correcting and appending useful data points to US addresses. Our address validation service specializes in fuzzy matching for address corrections and, more importantly, making sure that each and every address provided is NOT changed to something unexpected or incorrect.

While our address validation service is top notch, the focus on both USPS and accuracy introduces necessary limits on how we treat addresses that might be messy or missing key elements.  Which brings us to one of Service Objects more under appreciated offerings, our DOTS Address Detective service.

Address Detective and its operations

Address Detective was born from a need to help our customers fill in the gaps and make sense of their very messy and/or incomplete addresses. This service is an ever-evolving collection of address utilities designed to help with various problems that can arise from these messy or incomplete addresses.  Currently, there are three operations available that each solve uniquely different problems.  It is helpful to understand what each operations does and how it can be best used to correct an address before you even start your implementation.

Operation NameDescription
FindAddressUses name and phone number to assist with the processing of very messy or incomplete addresses.
FindAddressLineTakes inputs that might be jumbled into the wrong columns and parses them into a usable result.
FindOutlyingAddressesDigs into alternative data sets from USPS to identify addresses that while not deliverable may still be good addresses.

Address Detective’s operations explained: FindAddress

The flagship operation of Address Detective is FindAddress. This service was designed to help clients with addresses that may be so messy or incomplete that they may not be obviously fixable, even to the human eye. FindAddress is given free reign to be more aggressive in its basic operation but also makes use of other data points like name, business name or phone number to assist with the validation.

Behind the scenes the service will dig into public and proprietary data sources to connect the dots between given data points to return an accurate result. The service is not designed to return an address if one is not given, its designed to analyze data given with cross referenced values in order improve or validate a normally unvalidatable address.

For example, perhaps the desired address is:

Taco Bell
821 N Milpas St
Santa Barbara, CA 93103

But what if the input address is something like:

Milpas Street
Santa Barbara, CA 93103

Clearly, not enough information is given for this address to pass validation. A house number is always required. DOTS Address Detective is able to use either the name “Taco Bell” or the phone number, (805) 962-1114, to properly identify and standardize the right location. The partial input values given are still important to compare back and make sure the most accurate result is returned.

What about addresses that are even messier with misspelled or incorrect data:

Milpaaaas Str
Santa Bar, CF 93103

Given either “Taco Bell” or (805) 962-1114, there is still enough information to go on to compare, cleanse and return the correct standardized result.

Address Detective’s operations explained: FindAddressLines

The second operation, FindAddressLines, solves a very different problem. We would often run lists of addresses for clients where they would give us a .csv file of addresses with data points that were in unexpected locations. Perhaps they tracked multiple address lines in which the third or fourth address line contained the normal “main” address line.  For example; what if they had something like this:

Four Address Lines:

Address 1: Johson Paper Bag Company
Address 2: C/O John Smith
Address 3: Floor 4
Address 4: 123 Main Street
City: Santa Barbara
State: California
ZIP: 93101

If the user does not know that the needed address in this case is Address4 (123 Main Street) its possible they may be sending the address: Johnson Paper Bag Company, C/O John Smith, Santa Barbara, CA, 93101 which obviously would not be a valid address. Perhaps they have an even bigger problem and there was an error in how the address was stored or a corrupted database leading to something like this:

Corrupted Database Example:

Address 1: 123 Main St
City: Apt 5
State: Santa Barbara

Both of these cases are solved by using the FindAddressLines. FindAddressLines takes in a generic list of Address inputs and analyzes them to figure out how to properly assign the inputs to the correct fields.  The result is then validated, corrected and standardized as a normal address. While there is some synergy with the FindAddress operation here, in order to properly parse out an address, the address would have to at least look like an address.  FindAddressLines would not be able to do anything with an address of “Milpas Street” as opposed to “821 Milpas Street”.

Address Detective’s operations explained: FindOutlyingAddresses

The final operation is FindOutlyingAddresses. This operation cross references several massive non-USPS datasets to find likely good addresses when USPS cannot. While our Address Validation service is designed to accurately identify deliverable addresses and contains the vast majority of US based addresses it does not cover everything. Pockets of addresses either in very rural areas or some well known areas like Mammoth Lakes (California) do not have deliverable houses, all mail is delivered to a local post office for pickup by residents.

FindOutlyingAddresses aims to fill in the blanks of these hard to find addresses. They may not be important for mail delivery but still play a vital role in identifying lead quality. While the data returns for this operation are not as complete as our Address Validation service, we will attempt to identify the data points at the lowest level we can. Do we know the house number exists? Maybe the house number does not exist but we know the street does? This operation will return as much useful information as it can about these locations.

Address Validation + Address Detective = Powerful one-two punch

One of the best ways to ensure you have accurate and up-to-date address information is by combining our Address Validation service with Address Detective. This combination allows many of our customers to identify and repair addresses that they would have normally discarded.  We are always happy to help our clients set up this powerful one-two punch.

In its most basic form, we use Address Validation to correct and verify all addresses. Addresses that could not be validated or corrected by the initial, stricter validation process, would be sent to our Address Detective service where supplemental information helps ‘solve’ the address and returns a viable address.

What is next for Address Detective?

DOTS Address Detective is an ever-evolving collection of operations that were created to meet the needs of our clients. We are always looking for new algorithms, data sets and features we can add to meet these needs and help clients recover and update even more addresses.

One of the more recent requests we are working on is helping identify GDPR exposure.  Our clients need to know if a contact record resides in any of the European Countries that are covered by the far-reaching privacy protection regulations of the GDPR. It is always a little more fun to solve real-world problems that our clients are facing and we are excited to be launching a new international address detective service in the coming week to help.  (By the way, if you think it is simple to identify a country by an address, try taking this Country Quiz.)

We encourage clients and prospects alike to reach out and let us know if they have a need that does not seem to be covered by one of our current products.  Share your needs or try it today to see what DOTS Address Detective can do to help!


data privacy laws

A New Data Privacy Challenge for Europe – and Beyond

New privacy regulations in Europe have recently become a very hot topic again within the business community. And no, we aren’t talking about the recent GDPR law.

A new privacy initiative, known as the ePrivacy Regulation, deals with electronic communications. Technically a revision to the EU’s existing ePrivacy Directive or “cookie law,” and pending review by the European Union’s member states, it could go into effect as early as this year. And according the New York Times, it is facing strong opposition from many technology giants including Google, Facebook, Microsoft and others.

Data privacy meets the app generation

Among other things, the new ePrivacy Regulation requires explicit permission from consumers for applications to use tracking codes or collect data about their private communications, particularly through messaging services such as Skype, iMessage, games and dating apps.  Companies will have to disclose up front how they plan to use this personal data, and perhaps more importantly, must offer the same access to services whether permission is granted or not.

Ironically this new law will also remove the previous directive’s need for the incessant “cookie notices” consumers now receive, by using browser tracking settings, while tightening the use of private data. This will be a mixed blessing for online services, because a simple default browser setting can now lock out the use of tracking cookies that many consumers routinely approved under the old pop-up notices. As part of its opposition to these new rules, trade groups are painting a picture of slashed revenues, fewer free services and curbs on innovation for trends such as the Internet of Things (IoT).

A longstanding saying about online services is that “when something is free, you are the product,” and this new initiative is one of the more visible efforts for consumers to push back and take control of the use of their information. And Europe isn’t alone in this kind of initiative – for example, the new California Consumer Privacy Act, slated for the late 2018 ballot, will also require companies to provide clear opt-out instructions for consumers who do not wish their data to be shared or sold.

The future: more than just European privacy laws

So what does this mean for you and your business? No one can precisely foretell the future of these regulations and others, but the trend over time is clear: consumer privacy legislation will continue to get tighter and tighter. And the days of unfettered access to the personal data of your customers and prospects are increasingly coming to an end. This means that data quality standards will continue to loom larger than ever for businesses, ranging from stricter process controls to maintaining accurate consumer contact information.

We frankly have always seen this trend as an opportunity. As with GDPR, regulations such as these have sprung from past excesses the lie at the intersection of interruptive marketing, big data and the loss of consumer privacy. Consumers are tired of endless spam and corporations knowing their every move, and legislators are responding. But more important, we believe these moves will ultimately lead businesses to offer more value and authenticity to their customers in return for a marketing relationship.

Freshly Squeezed…Never Frozen

Data gets stale over time. You rely on us to keep this data fresh, and we in turn rely on a host of others – including you! The information we serve you is the product of partnerships at many levels, and any data we mine or get from third party providers needs to be up-to-date.

This means that we rely on other organizations to keep their data current, but when you use our products, it is still our name on the door. Here at Service Objects, we use a three-step process to do our part in providing you with fresh data:

Who: We don’t make partnerships with just anyone.  Before we take on a new vendor, we fully vet them to be sure this partnership will meet our standards, now and in the future. To paraphrase the late President Reagan, we take a “trust but verify” approach to every organization we team up with.

What: We run tests to make sure that data is in fact how we expect it to be. This runs the gamut from simple format tests to ensuring that results are accurate and appropriate.

When: Some of the data we work with is updated in real time, while other data is updated daily, weekly, or monthly.  Depending on what type of data it is, we set up the most appropriate update schedule for the data we use.

At the same time, we realize this is a partnership between us and you – so to get the most out of our data, and for you to have the best results, we always suggest that you make sure to re-check some of your data points periodically, regardless of whether you are using our API or our batch processing system. Some of the more obvious reasons for this are that people move, phone numbers change, emails change, areas get redistricted, and so on. To maintain your data and keep it current, we recommend periodically revalidating it against our services.

Often business will implement our services to check data at the point of entry into their system, and also to perform a one-time cleanse to create a sort of baseline. This is all a good thing, especially when you make sure that data is going into your systems properly and is as clean as possible. However, it is important to remember that in 6-12 months some of this data will no longer be current.  Going the extra step to create a periodic review of your data is a best practice and is strongly recommended.

We also suggest keeping some sort of time stamp associated with when a record was validated, so that when you have events such as a new email campaign and some records have not been validated for a long time – for example, 12 months or more – you can re-run those records through our service.  This way you will ensure that you are getting the most out of your campaign, and at the same time protect your reputation by reducing bounces.

Finally, here is a pro tip to reduce your shipping costs: in our Address Validation service, we return an IsResidential indicator that identifies an address as being residential or not.  If this indicator changes, having the most recent results will help your business make the most cost-effective shipping decisions.

For both us and you, keeping your data fresh helps you get the most out of these powerful automation tools. In the end there is no specific time span we can recommend for verification that will suit every business across the board, and there will be cases where it isn’t always necessary to keep revalidating your data: the intervals you decide to use for your application will depend mostly on your application. But this is still an important factor to keep in mind as you design and evaluate your data quality process.

To learn more about how our data quality solutions can help your business, visit the Solutions section of our website.

When that data is incomplete, poorly defined, or wrong, there are immediate consequences: angry customers, wasted time, and difficult execution of strategy. Employing data quality best practices presents a terrific opportunity to improve business performance.

The Unmeasured Costs of Bad Customer and Prospect Data

Perhaps Thomas Redman’s most important recent article is “Seizing Opportunity in Data Quality.”  Sloan Management Review published it in November 2017, and it appears below.  Here he expands on the “unmeasured” and “unmeasurable” costs of bad data, particularly in the context of customer data, and why companies need to initiate data quality strategies.

Here is the article, reprinted in its entirety with permission from Sloan Management Review.

The cost of bad data is an astonishing 15% to 25% of revenue for most companies.

Getting in front on data quality presents a terrific opportunity to improve business performance. Better data means fewer mistakes, lower costs, better decisions, and better products. Further, I predict that many companies that don’t give data quality its due will struggle to survive in the business environment of the future.

Bad data is the norm. Every day, businesses send packages to customers, managers decide which candidate to hire, and executives make long-term plans based on data provided by others. When that data is incomplete, poorly defined, or wrong, there are immediate consequences: angry customers, wasted time, and added difficulties in the execution of strategy. You know the sound bites — “decisions are no better than the data on which they’re based” and “garbage in, garbage out.” But do you know the price tag to your organization?

Based on recent research by Experian plc, as well as by consultants James Price of Experience Matters and Martin Spratt of Clear Strategic IT Partners Pty. Ltd., we estimate the cost of bad data to be 15% to 25% of revenue for most companies (more on this research later). These costs come as people accommodate bad data by correcting errors, seeking confirmation from other sources, and dealing with the inevitable mistakes that follow.

Fewer errors mean lower costs, and the key to fewer errors lies in finding and eliminating their root causes. Fortunately, this is not too difficult in most cases. All told, we estimate that two-thirds of these costs can be identified and eliminated — permanently.

In the past, I could understand a company’s lack of attention to data quality because the business case seemed complex, disjointed, and incomplete. But recent work fills important gaps.

The case builds on four interrelated components: the current state of data quality, the immediate consequences of bad data, the associated costs, and the benefits of getting in front on data quality. Let’s consider each in turn.

Four Reasons to Pay Attention to Data Quality Now

The Current Level of Data Quality Is Extremely Low

A new study that I recently completed with Tadhg Nagle and Dave Sammon (both of Cork University Business School) looked at data quality levels in actual practice and shows just how terrible the situation is.

We had 75 executives identify the last 100 units of work their departments had done — essentially 100 data records — and then review that work’s quality. Only 3% of the collections fell within the “acceptable” range of error. Nearly 50% of newly created data records had critical errors.

Said differently, the vast majority of data is simply unacceptable, and much of it is atrocious. Unless you have hard evidence to the contrary, you must assume that your data is in similar shape.

Bad Data Has Immediate Consequences

Virtually everyone, at every level, agrees that high-quality data is critical to their work. Many people go to great lengths to check data, seeking confirmation from secondary sources and making corrections. These efforts constitute what I call “hidden data factories” and reflect a reactive approach to data quality. Accommodating bad data this way wastes time, is expensive, and doesn’t work well. Even worse, the underlying problems that created the bad data never go away.

One consequence is that knowledge workers waste up to 50% of their time dealing with mundane data quality issues. For data scientists, this number may go as high as 80%.

A second consequence is mistakes, errors in operations, bad decisions, bad analytics, and bad algorithms. Indeed, “big garbage in, big garbage out” is the new “garbage in, garbage out.”

Finally, bad data erodes trust. In fact, only 16% of managers fully trust the data they use to make important decisions.

Frankly, given the quality levels noted above, it is a wonder that anyone trusts any data.

When Totaled, the Business Costs Are Enormous

Obviously, the errors, wasted time, and lack of trust that are bred by bad data come at high costs.

Companies throw away 20% of their revenue dealing with data quality issues. This figure synthesizes estimates provided by Experian (worldwide, bad data cost companies 23% of revenue), Price of Experience Matters ($20,000/employee cost to bad data), and Spratt of Clear Strategic IT Partners (16% to 32% wasted effort dealing with data). The total cost to the U.S. economy: an estimated $3.1 trillion per year, according to IBM.

The costs to businesses of angry customers and bad decisions resulting from bad data are immeasurable — but enormous.

Finally, it is much more difficult to become data-driven when a company can’t depend on its data. In the data space, everything begins and ends with quality. You can’t expect to make much of a business selling or licensing bad data. You should not trust analytics if you don’t trust the data. And you can’t expect people to use data they don’t trust when making decisions.

Two-Thirds of These Costs Can Be Eliminated by Getting in Front on Data Quality

“Getting in front on data quality” stands in contrast to the reactive approach most companies take today. It involves attacking data quality proactively by searching out and eliminating the root causes of errors. To be clear, this is about management, not technology — data quality is a business problem, not an IT problem.

Companies that have invested in fixing the sources of poor data — including AT&T, Royal Dutch Shell, Chevron, and Morningstar — have found great success. They lead us to conclude that the root causes of 80% or more of errors can be eliminated; that up to two-thirds of the measurable costs can be permanently eliminated; and that trust improves as the data does.

Which Companies Should Be Addressing Data Quality?

While attacking data quality is important for all, it carries a special urgency for four kinds of companies and government agencies:

Those that must keep an eye on costs. Examples include retailers, especially those competing with Inc.; oil and gas companies, which have seen prices cut in half in the past four years; government agencies, tasked with doing more with less; and companies in health care, which simply must do a better job containing costs. Paring costs by purging the waste and hidden data factories created by bad data makes far more sense than indiscriminate layoffs — and strengthens a company in the process.

Those seeking to put their data to work. Companies include those that sell or license data, those seeking to monetize data, those deploying analytics more broadly, those experimenting with artificial intelligence, and those that want to digitize operations. Organizations can, of course, pursue such objectives using data loaded with errors, and many companies do. But the chances of success increase as the data improves.

Those unsure where primary responsibility for data should reside. Most businesspeople readily admit that data quality is a problem, but claim it is the province of IT. IT people also readily admit that data quality is an issue, but they claim it is the province of the business — and a sort of uneasy stasis results. It is time to put an end to this folly. Senior management must assign primary responsibility for data to the business.

Those who are simply sick and tired of making decisions using data they don’t trust. Better data means better decisions with less stress. Better data also frees up time to focus on the really important and complex decisions.

Next Steps for Senior Executives

In my experience, many executives find reasons to discount or even dismiss the bad news about bad data. Common refrains include, “The numbers seem too big, they can’t be right,” and “I’ve been in this business 20 years, and trust me, our data is as good as it can be,” and “It’s my job to make the best possible call even in the face of bad data.”

But I encourage each executive to think deeply about the implications of these statistics for his or her own company, department, or agency, and then develop a business case for tackling the problem. Senior executives must explore the implications of data quality given their own unique markets, capabilities, and challenges.

The first step is to connect the organization or department’s most important business objectives to data. Which decisions and activities and goals depend on what kinds of data?

The second step is to establish a data quality baseline. I find that many executives make this step overly complex. A simple process is to select one of the activities identified in the first step — such as setting up a customer account or delivering a product — and then do a quick quality review of the last 100 times the organization did that activity. I call this the Friday Afternoon Measurement because it can be done with a small team in an hour or two.

The third step is to estimate the consequences and their costs for bad data. Again, keep the focus narrow — managers who need to keep an eye on costs should concentrate on hidden data factories; those focusing on AI can concentrate on wasted time and the increased risk of failure; and so forth.

Finally, for the fourth step, estimate the benefits — cost savings, lower risk, better decisions — that your organization will reap if you can eliminate 80% of the most common errors. These form your targets going forward.

Chances are that after your organization sees the improvements generated by only the first few projects, it will find far more opportunity in data quality than it had thought possible. And if you move quickly, while bad data is still the norm, you may also find an unexpected opportunity to put some distance between yourself and your competitors.


Service Objects spoke with the author, Tom Redman, and he gave us an update on the Sloan Management article reprinted above, particularly as it relates to the subject of the costs associated with bad customer data.

Please focus first on the measurable costs of bad customer data.  Included are items such as the cost of the work Sales does to fix up bad prospect data it receives from Marketing, the costs of making good for a customer when Operations sends him or her the wrong stuff, and the cost of work needed to get the various systems which house customer data to “talk.”  These costs are enormous.  For all data, it amounts to roughly twenty percent of revenue.

But how about these costs:

  • The revenue lost when a prospect doesn’t get your flyer because you mailed it to the wrong address.
  • The revenue lost when a customer quits buying from you because fixing a billing problem was such a chore.
  • The additional revenue lost when he/she tells a friend about his or her experiences.

This list could go on and on.

Most items involve lost revenue and, unfortunately, we don’t know how to estimate “sales you would have made.”  But they do call to mind similar unmeasurable costs associated with poor manufacturing in the 1970s and 80s.  While expert opinion varied, a good first estimate was that the unmeasured costs roughly equaled the measured costs.

If the added costs in the Seizing Opportunity article above doesn’t scare into action, add in a similar estimate for lost revenue.

The only recourse is to professionally manage the quality of prospect and customer data.  It is not hyperbole to note that such data are among a company’s most important assets and demand no less.

©2018, Data Quality Solutions


The Role of Data Quality in GDPR

If you do business with clients in the European Union, you have probably heard of the new General Data Protection Regulation (GDPR) that takes effect in Spring 2018. This new EU regulation ushers in strict new requirements for safeguarding the security and privacy of personal data, along with requiring active opt-in permission and ease of changing this permission.

Most articles you read about GDPR nowadays focus on the risks on non-compliance, and penalties are indeed stiff: up to €20 million or 4 percent of annual turnover. However, we recently hosted a webinar at Service Objects with two experts on GDPR, and they had a refreshing perspective on the issue – in their view, regulators are in fact helping your business by fundamentally improving your relationship with your customers. As presenter Tom Redman put it, “Regulators are people (and customers) too!”

Dr. Redman, known as the Data Doc, is the author of three books on data quality as well as the founder of Data Quality Solution, and the former head of AT&T’s Data Quality Lab. He was joined on our webinar by Daragh O’Brien, founder and CEO of Castlebridge, an information strategy, governance, and privacy consultancy based in Ireland. Together they made a case that GDPR is, in a sense, a healthy evolution across Europe’s different cultures and legal systems, taking a lead role in how we interact with our customers.

As Daragh put it, “(What) we’re currently calling data are simply a representation of something that exists in the real world who is a living breathing person with feelings, with emotions, with rights, and with aspirations and hopes, and how we handle their data has an impact on all of those things.” And Tom painted a picture of a world where proactive data quality management becomes a corporate imperative, undertaken to benefit an organization rather than simply avoid the wrath of a regulator.

At Service Objects, we like Tom and Daragh’s worldview a great deal. For our entire 15-plus year history, we have always preached the value of engineering data quality into your business processes, to reap benefits that range from cost savings and customer satisfaction all the way to a stronger brand in the marketplace. And seen through the lens of recent developments such as GDPR, we are part of a world that is rapidly moving away from interruptive marketing and towards customer engagement.

We would like to help you be part of this revolution as well. (And, in the process, help ensure your compliance with GDPR for your European clients.) There are several ways we can help:

1) View the on-demand replay of this recent webinar, at the following link:

2) Download our free white paper on GDPR compliance:

3) Finally, contact us for a free one-on-one GDPR data quality assessment:

In a very real sense, we too are trying to create a more interactive relationship with our own clients based on service and customer engagement. This is why we offer a rich variety of information, resources and personal connections, rather than simply tooting our horn and bugging you to purchase something. This way we all benefit, and close to 2500 existing customers agree with us. We feel it is time to welcome the brave new customer-focused world being ushered in by regulations such as GDPR, and for us to help you become part of it.

Three Building Blocks to Global Data Protection Regulation (GDPR) Compliance

Is your business ready for the GDPR? On May 25, 2018 a sweeping change in global consumer privacy, one that will fundamentally change the way companies around the world perform outbound marketing, will become law. This is the date that enforcement commences for the European Union’s new General Data Protection Regulation (GDPR), governing the use of personal data for over 500 million EU residents. US companies who market to customers or prospects in Europe will now face strict regulations surrounding the use and storage of consumer data, backed by potentially hefty revenue-based fines.

However, recent studies have shown that many businesses are woefully unprepared for GDPR, which will require changes ranging from point-of-entry data validation to the management of changing contact information. So, what is a good way to get started on the road to compliance? Start with these three building blocks.

For most organizations, GDPR compliance pivots around three fundamental building blocks: consent management, data protection, and data quality.

The first two of these building blocks will revolve around process change for most organizations. In the first case, consent management means that you will now need to prove that you have permission to use someone’s personal data for marketing purposes, and maintain records of this permission.

There are no exceptions to this rule for previously captured data, which means that consent may need to be re-acquired under mechanisms acceptable under GDPR. This also extends to providing easy and accessible ways for consumers to reverse this permission, extending all the way to Europe’s concept of “the right to be forgotten”—requiring you to erase all traces of a person’s contact information if requested by a consumer.

The second building block, data protection, involves deploying processes—and possibly specific people—designed to protect consumers’ personal data from unauthorized disclosure.

At a process level, this means that organizations will need to show that they have safeguards in place against personal data being stolen or misused. One popular approach for this involves pseudonomization, where key personal information is kept separate and secure until actual use. Unlike anonymization, where ownership of data cannot be reconstructed, pseudonomiization allows certain identifying characteristics to be used as a “password” to combine other separately-stored components of information at the time of use.

If your organization is large enough, GDPR may also require the formal role of a Data Protection Officer (DPO), with dedicated responsibilities within an organization for protecting personal data. The specific criteria for needing a DPO is “large-scale systematic monitoring of individuals,” along with more specific situations such as public authorities and organizations handling large scale data processing of criminal convictions. With or without a formal DPO, companies will be expected to have a documented game plan for protecting consumer information.

Finally, data quality serves as the third building block. Once upon a time incorrect, fraudulent or changing contact records were seen as an annoyance, or perhaps an unavoidable expense—and if people received unsolicited marketing materials or contacts as a result, it was their problem to endure or resolve. Today, in the era of GDPR, data quality issues can lead to compliance problems with serious financial consequences. This means that data must be verified and corrected, both at the point of entry and time of use.

Of all three of these building blocks, data quality is the one area that is probably represents the largest ongoing responsibility for most organizations. Thankfully, it is also the one that is the most amenable to automation.

Interested in finding out more about the role contact data plays in Global Data Protection Regulation (GDPR)? Visit our GDPR Solutions page, which contains a variety of resources that explain the key principles of GDPR compliance for contact data, and how automated data quality tools can protect your marketing efforts in the European marketplace.

Email Marketing Tip: Dealing With Role Addresses

Do you have any friends named “info” or “customerservice”?

If you do, our sympathies, because their parents were probably way over-invested in their careers. But in all likelihood, you probably don’t. Which leads to a very important principle about your email marketing: you always need to make sure you are marketing to real people.

Email addresses like “” or “” are examples of what we call role addresses. They are not addressed to a person, but rather to a job function and generally include a number of people on the distribution list. They serve a valuable purpose, particularly in larger organizations – if you have a problem with, for example, you don’t want to wait for Cindy to get back from vacation first to respond to you.

You probably realize that role email addresses create the same problems as any other non-person in your marketing database: wasted human effort, lower response rates, bounces, and the like. However, there are several other important reasons to purge role addresses from your contact database:

Bounce Rate. Role emails are generally the responsibility of an email administrator.  These administrators are not always kept in the loop when individuals move onto other positions or leave the company.  This can result in a role email’s distribution list not being up-to-date and emails being sent to inactive email addresses.  These inactive addresses are usually set to automatically bounce emails, resulting in a higher bounce rate and poorer campaign performance.

Blacklisting. Spamming a role email address doesn’t just annoy people. As one article points out, it can trigger spam complaints and damage your sender reputation – in fact, role accounts are often used as spam traps by account holders. This can lead to your IP being blacklisted for the entire organization, cutting you off from leads or even existing customers far beyond the original email.

CAN-SPAM compliance. Permission to send email is fundamentally a contract with an individual, and marketing to a role email address risks having your materials go to people who did not opt-in or agree to your terms and conditions – putting you at risk for being in violation of the US CAN-SPAM act that governs email marketing.

New laws. In Europe, the new General Data Protection Regulation (GDPR) takes effect in 2018, severely restricting unsolicited email marketing. While it is not always clear that you are mailing to Europe (for example, many people do not realize that household names like Bayer and Unilever are based there), you are still bound by their laws and potentially stiff penalties. Eliminating role accounts from your contact database is an important part of mitigating this exposure.

Exponential risk. When it comes to risk, role addresses are the gift that keeps on giving. One of these addresses may go to 10 different people or more – and only one of them needs to complain to get you in trouble. Moreover, you can easily get multiple complaints for the price of one errant message.

Customer reputation. When someone signs up for your contact list using a role address, it is a form of “friendly fraud” that absolves them from personally receiving your emails – much like the person who signs up as “Donald Duck” to receive a free marketing goodie. But when other people start receiving your materials without their permission as a result, it is not a good way to start a customer relationship.

Thankfully, avoiding role-based addresses is relatively easy. In fact, many large email marketing providers won’t import these address in the first place. Or if you manage your contact database from within your own applications environment, we can help. Our email validation capabilities flag role-based addresses in your database like sales, admin, support, webmaster, billing, and much more. In addition, we perform over 50 verification tests, clean up common spelling and syntax errors, and return a quantitative quality score that helps you accept or reject addresses at the point of import.

So, with pun fully intended, your role in data quality is to ensure that your online marketing only goes to live, real people who welcome your message. Our role is to automate this process to make it as frictionless as possible. Together, we can keep your email contact data ready to roll!

Character Limitations in Shipping Address Fields – There is a Solution

If you are using an Address Validation service for shipping labels, then you may occasionally run into character count limitations with the Address1 field. Whether you are using UPS, FedEx, ShipStation or any other shipping solution, most character limits tend to range between 30 or 35 characters (some even as low as 25 characters). While most addresses tend to be under this limit, there are always outliers that you’ll want your business solution to be ready to handle.

If you are using a DOTS Address Validation solution, you are in luck! The response from our API not only validates and corrects bad addresses but also allows you to customize address lines to meet your business needs.  Whether you are looking to have your address lines be under a certain limit, want to place apartment or unit information on a separate line, or customize the address line in some other way, we can show you how to integrate the Address Validation response from Service Objects’ API into your business logic.

Below is a brief example using our DOTS Address Validation US 3 service to demonstrate the fragments that are returned in a typical valid response:


If you are worried about exceeding a certain character limit, you can programmatically check the Address1 line result from our service to see if it exceeds a particular limit.

Check the result – not the input

There are two obvious reasons you should check the result of the service instead of the input.   First, you want to use validated and corrected addresses on your mailing label. Second, the input address may be too long before validating but post-validation, the corrected addressed could meet the requirements and no customizations are needed to fit within the character limitations.

With this understanding, if the resulting validated street address in Address1 line is over the character limitation, then your application can go about splitting up the address in ways that best suit your needs.

For example, let’s say you have a long address line like the following:


This is obviously a fake street, but it helps demonstrate some of the different ways you can handle long address lines. In the example, the address ends up being around 45 characters long, including spaces. The service would return the following fragments for this address:

Fragment House: 12345
FragmentPreDir: W
FragmentStreet: Fake Industrial
FragmentSuffix: St
FragmentPostDir: NE
FragmentUnit: STE
Fragment: 130
FragmentPMBPrefix: #
FragmentPMBNumber: 678

With this example, one solution to reduce the character limits would be to move the Suite and Mail Box information to a separate address line, so it would appear like so:

STE 130, #678

You may need to fine tune the logic in your business application from this basic algorithm, but this can help you get started with catering your validated address information to meet different character limitations.

In most cases, the following can be used in Address line 1:

  • FragmentHouse
  • FragmentPreDir
  • FragmentStreet
  • FragmentSuffix
  • FragmentPostDir

And the following in Address line 2:

  • FragmentUnit,
  • Fragment
  • FragmentPMBPrefix
  • FragmentPMBNumber

PO Boxes

There is an important exception to be aware of – PO Boxes. It is necessary to determine if the address is a PO Box to avoid applying the above logic to this type of address. It is simple to determine if the result is a PO Box by checking the DPVNotes field returned from the Address Validation service.  PO Boxes typically will fit under character length limitations but some organizations choose to rebuild addresses from fragments regardless of field length.  If this is the case and you have a PO Box, then the fragments to rebuild the PO Box are:

  • FragmentStreet
  • FragmentHouse

Highly Customizable

The examples above may require some fine-tuning to meet your business requirements but hopefully, they have also demonstrated the highly customizable nature of the address validation service and how it can be catered to meet your address validation needs.

If you have any questions about different integrations into your particular application contact our support team at and we will gladly provide any support that we can!

Now or Later? When to Clean Your Marketo Database

If you were to make a list of the things people love to do, data cleanup would usually rank pretty low on the list. (Except for us here at Service Objects. We rather enjoy data cleanup. But then again, we’ve always been a little different.) This naturally leads to another question: should you clean up your contact data BEFORE you put it into Marketo, or LATER, before you actually use it in a campaign?

We have a three-part answer to this question: yes, yes, and automate the process.

Here’s why: there are irreplaceable benefits to each process. And when you properly automate it with the right tools, the process becomes frictionless and institutionalizes the ROI of these benefits. Let’s explore this in more detail.

Validating contact data such as names, email, physical addresses and phone numbers BEFORE loading them into Marketo has several advantages:

Saving money.  Your Marketo pricing tier is depending on the number of leads in your database. By cleaning this data on the front end, you can often delay or perhaps even avoid entirely the problem of moving to a higher tier and paying more for non-viable leads. And within your tier, fewer bad leads translates directly to less human intervention throughout the marketing cycle and more accurate analytics.

Garbage in, garbage out. Putting dirty data into your marketing database skews whatever metrics or analyses you might do beyond marketing campaigns, including the all-important conversion rate. And catching bad contact information in real-time lets you message the user at time of entry so they can correct it, preserving valuable leads and preventing possible customer service issues.

Detecting bogus names and fraudulent leads. What good is a database full of Donald Ducks and Ninja Turtles, who faked you out to get a free report? Tools such as name validation can programmatically catch and keep fraudulent contact information out of your lead database in the first place.

Lead preservation. Conversely, your bad contact data can be a hidden source of leads and revenue – if you use automated tools to correct bad addresses or append missing information such as contact phone numbers.

Finally, there is the broader question of lead quality. Marketo’s own lead scoring – based on tracking activities, behavior and demographics – is important but may not provide front-end protection from fraudulent or bad data. Contact-level lead validation adds a quantitative value for lead quality, based on over 200 criteria, that lets you decide to fast-track a lead, put them in your drip campaign to see how they respond, or even discard the lead.

Now, let’s look at the other side of the coin. Validating lead data LATER at regular intervals, particularly at the time you use it, has several advantages as well.

Coping with change. Over 70% of contact data will go bad in the course of just a year. Lead validation tools can check your existing leads and then correct, update, or remove them based on the results. This saves you money by only keeping and paying for viable leads, allowing you to better identify sources of high and low quality leads and providing more accurate reporting.

Taking care of your customers. By triggering emails or other contacts to customers who appear to have changed their addresses, using tools such as our national change-of-address (NCOA Live) capabilities, you provide better service and pro-actively avoid future service or delivery failures.

Making your IT department happy. Lead and contact validation tools from Service Objects are easily automated within Marketo using our Webhooks which can be found on Marketo’s LaunchPoint marketplace. In addition, we offer convenient offline batch processing for contact data files without a technical interface.

Of course, automated contact and lead validation are not the only forms of data cleanup that can help – this blog by Perkuto’s John Hill touches on other useful areas such as screening out competitors, inactive leads and people with unresponsive email addresses. With a clear process in place – and the right automation partner – it can be easy and inexpensive to optimize the value of your Marketo database at EVERY contact touch point.

GDPR Compliance: Is Your Business Ready?

If you conduct business in Europe, May 2018 will be an important date. This is when the planned introduction of the European Union’s General Data Protection Regulation (GDPR) is scheduled to take effect.

GDPR represents a sweeping set of privacy regulations that impact your use of personal data from European citizens. If you conduct business with people from Europe – whether they are your customers, employees, or job prospects – GDPR affects you as well. It will require you to have policies in place to protect people’s personal data, as well as require notification when this data has been breached. And penalties for violations will be extremely stiff, up to the greater of 20 million Euros or 4% of your gross turnover.

GDPR starts with the definition of “personal data.” This is an extremely broad net: a recent article from Software Development magazine notes that the European Commission’s guidelines include both obvious data such name, address or email, and associated data ranging from bank accounts to photos and social media posts. Even the IP address a European is using on their computer is considered part of this personal data.

Much like the HIPAA requirements on electronic health care data in the United States, GDPR will require organizations to safeguard the personal data they collect and store in the course of doing business. At one level, this will involve technology such as encrypted data storage, password protection, and other approaches, along with policies and procedures for protecting this data. At another level, it obligates you to inform European consumers about your privacy policies, gain explicit consent to collect and use their personal data and provide them with the ability to control or opt-out of data collection. And in the event personal data is compromised, you need a plan for reaching people affected by the breach.

Each of these levels have important areas where data quality and GDPR compliance efforts intersect. Some of the questions businesses will have to ask themselves include:

  • Do we have accurate contact information for people we do business with in Europe?
  • Is there a notification procedure in place for our privacy and data policies, including opting out of data collection or making changes to personal data?
  • If a breach notification were necessary, do we have the means to quickly reach all affected parties?
  • How do we handle changes to contact information? What if a person in your database moves, changes jobs, or gets a new email address?

This means that your GDPR and data quality strategies will need to be closely linked. Tools such as international address verification, lead validation and name validation can help make sure data is complete and correct as it enters your system, and stays correct when it is needed later. As a recent article in Information Management points out, the key to GDPR compliance lies in proactively analyzing your data and performing a thorough risk assessment long before an actual privacy issue arises.

The European Union has long been on the vanguard of consumer protection legislation, and the new GDPR regulations are the latest in an effort to level the playing field between big data and the individual rights of its citizens. They have a global reach, whether you do business in Europe or serve Europeans from elsewhere. At a broader level, GDPR is part of a new reality that businesses will soon need to work with, one that is part of a larger trend toward increasing privacy regulations.

May 2018 is coming soon – is your business ready?

Omnichannel Solutions and Data Quality

Just a few decades ago the concept of a “channel” didn’t exist, other than on your television. If a customer or prospect wanted to contact you, they called you or wrote you a letter. And if you wanted to contact them, you got out your Rolodex – or if you were a large enterprise, perhaps your batch mainframe computer, with disk drives the size of a washing machine.

Today, sales, marketing and customer support take place across multiple touch points that include point of sale, online orders, emails, social media inquiries – and even those same traditional phone calls and letters. Increasingly, this contact data is managed by integrated enterprise systems rather than separate vertical applications. Which also means that all of your sales and support channels often serve as pipelines to a common contact database.

Over the past five years, we have been in the midst of an omnichannel revolution in enterprise solutions. The reason is simple economics – particularly the growth of inexpensive, scalable, cloud-based software-as-a-service (SaaS) applications. Once upon a time, enterprise software seemingly required months of planning and a cast of thousands to implement. Today, even the smallest operation can license applications that integrate ALL of their customer touch points on an inexpensive per-seat basis.

The era of integrated, multi-channel applications also means that the impact of bad contact data is now greatly amplified. Here are some examples:

  • Many customer touch points are notorious for providing incomplete or incorrect contact information. This can range from the person who enters “Mickey Mouse” or a fake address to get free marketing incentives, all the way to customer support tickets with missing contact data.
  • An estimated 25% of marketing contact data is bad – and in an enterprise solutions environment, this bad data propagates across all of your sales and marketing activities, wasting time and resources.
  • Telephone numbers change constantly, and your next telemarketing campaign could find you inadvertently – and illegally – calling consumer cell phones in violation of the Telephone Consumer Protection Act (TCPA), exposing you to potential fines of up to $1500 per violation.
  • Data entry mistakes in order processing can lead to lost shipments, wasted time and human intervention, and customer dissatisfaction.
  • Identity fraud cost businesses over $18 billion in losses in 2014, and much of it could be avoided by matching IP address locations to customer orders – so, for example, your system can red-flag a big-ticket domestic order originating from an overseas computer.

The solution to issues like these is to build data quality right in to your enterprise contact data, with a little help from Service Objects. Our tools can validate, append and update addresses using continually verified data from the USPS or Canada Post. We can geocode and analyze your order data for fraud verification, tax compliance and more. We can do real-time phone number verification to help you maintain TCPA compliance. More strategically, we can do lead scoring and enhancement to turn your contact data into a revenue-generating engine. Using API and batch processing interfaces, these tools and more provide a seamless way to put your contact data quality on autopilot.

The omnichannel era is here to stay – and in the process, contact data has become a strategic asset for companies of any size. We can help you leverage the power of this asset, by making sure this data is genuine, accurate, and up-to-date. And with the right partner, you can let data quality drive a tangible difference in revenue across all of your channels.

The 2018 European Data Protection Regulation – Is Your Organization Prepared?

The General Data Protection Regulation (GDPR) is a regulation intended to strengthen and unify data protection for all individuals within the European Union (EU). It also addresses the export of personal data outside the EU. The primary objectives of the GDPR are to give citizens and residents back control of their personal data and to simplify the regulatory environment for international business by unifying the regulation within the EU.

According to research firm Gartner, Inc., this regulation will have a global impact when it goes into effect on May 25, 2018.  Gartner predicts that by the end of 2018, more than 50 percent of companies affected by the GDPR will not be in full compliance with its requirements.

To avoid being part of the 50 percent that may not be in compliance one year from now, organizations should start planning today. Gartner recommends organizations focus on five high-priority changes to help organizations to get up to speed:

    1. Determine Your Role Under the GDPR
      Any organization that decides on why and how personal data is processed is essentially a “data controller.” The GDPR applies therefore to not only businesses in the European Union, but also to all organizations outside the EU processing personal data for the offering of goods and services to the EU, or monitoring the behavior of data subjects within the EU.
    2. Appoint a Data Protection Officer
      Many organizations are required to appoint a data protection officer (DPO). This is especially important when the organization is a public body, is processing operations requiring regular and systematic monitoring, or has large-scale processing activities.
    3. Demonstrate Accountability in All Processing Activities
      Very few organizations have identified every single process where personal data is involved. Going forward, purpose limitation, data quality and data relevance should be decided on when starting a new processing activity as this will help to maintain compliance in future personal data processing activities. Organizations must demonstrate an accountable ground posture and transparency in all decisions regarding personal data processing activities. It is important to note that accountability under the GDPR requires proper data subject consent acquisition and registration. Prechecked boxes and implied consent will be largely in the past.
    4. Check Cross-Border Data Flows
      As of today, data transfers to any of the 28 EU member states, as well as 11 other countries, are still allowed, although the consequences of Brexit are still unknown. Outside of the EU, organizations processing personal data on EU residents should select the appropriate mechanism to ensure compliance with the GDPR.
    5. Prepare for Data Subjects Exercising Their Rights Data subjects have extended rights under the GDPR, including the right to be forgotten, to data portability and to be informed (e.g., in case of a data breach).

Having poor quality data has several impacts on an organization and could hinder your efforts to being in compliance. Visit Service Objects’ website to see how our global data quality solutions can help you ensure your contact data is as genuine, accurate and up-to-date as possible.

Big Data – Applied to Day to Day Life

With so much data being constantly collected, it’s easy to get lost in how all of it is applied in our real lives. Let’s take a quick look at a few examples starting with one that most of us encounter daily.

Online Forms

One of the most common and fairly simple to understand instances we come across on a daily basis is completing online forms. When we complete an online form, our contact record data points, like; name, email, phone and address, are being individually verified and corrected in real time to ensure each piece of data is genuine, accurate and up to date. Not only does this verification process help mitigate fraud for the companies but it also ensures that the submitted data is correct. The confidence in data accuracy allows for streamlined online purchases and efficient deliveries to us, the customers. Having our accurate information in the company’s data base also helps streamline customer service should there be a discrepancy with the purchase or we have follow up questions about the product. The company can easily pull up our information with any of the data points initially provided (name, email, phone, address and more) to start resolving the issue faster than ever (at least where companies are dedicated to good customer service).

For the most part we are all familiar with business scenarios like the one described above. Let’s shift to India & New Orleans for a couple new examples of how cities are applying data to improve the day-to-day lives of citizens.

Addressing the Unaddressed in India

According to the U.S. Census Bureau, India is the second most populated country in the world with 1,281,935,911 people. With such a large population there is a shortage of affordable housing in many developed cities, leading to about 37 million households residing in unofficial housing areas referred to as slums. Being “unofficial” housing areas means they are not mapped nor addressed leaving residents with very little in terms of identification. However, the Community Foundation of Ireland (a Dublin based non-profit organization) and the Hope Foundation recently began working together to provide each home for Kolkata’s Chetla slum their very first form of address consisting of a nine-digit unique ID. Beside overcoming obvious challenges like giving someone directions to their home and being able to finally receive mail, the implementation of addresses has given residents the ability to open bank accounts and access social benefits. Having addresses has also helped officials identify the needs in a slum, including healthcare and education.

Smoke Detectors in New Orleans

A recent article, The Rise of the Smart City, from The Wall Street Journal highlights how cities closer to home have started using data to bring about city wide enhancements. New Orleans, in particular, is ensuring that high risk properties are provided smoke detectors. Although the fire department has been distributing smoke detectors for years, residents were required to request them. To change this, the city’s Office of Performance and Accountability, used Census Bureau surveys and other data along with advanced machine-learning techniques to create a map for the fire department that better targets areas more susceptible to deaths caused by fire. With the application of big data, more homes are being supplied with smoke detectors increasing safety for entire neighbors and the city as a whole.

FIRE RISK | By combining census with additional data points, New Orleans mapped the combined risk of missing smoke alarms and fire deaths, helping officials target distribution of smoke detectors. PHOTO: CITY OF NEW ORLEANS/OPA

While these are merely a few examples of how data is applied to our day to day lives around the world, I hope they helped make “Big Data” a bit more relatable. Let us know if we can answer any questions about how data solutions can be applied to help your company as well.

From Hello Operator to Hey Siri – Accurate Contact Data Has Always Been Crucial

Fueled by our desire to communicate with one another, no matter distance, the telephone has undergone extraordinary technological enhancements since the first test call on March 10, 1876. Today, the average wireless phone even functions as a portable computer offering a multitude of ways to communicate. Although phone technology dramatically changed over the last 141 years and continues to change, one aspect of placing a call remains vitally important: accurate contact data.

Originally, the telephone was sold in pairs of two with a single connection to each other. Since these early telephones were directly connected to each other, phone numbers were not yet required. However, with the invention of the switchboard in 1878, callers could connect with many other subscribers leading to the establishment of phone numbers consisting of a few digits. By 1910 the U.S. population grew to 92,228,496, over seven million of whom were phone subscribers. To accommodate so many users the length of the phone number increased.  For the majority of the 1900s, whether using a candlestick, rotary or push button phone, the telephone operator manually connected callers by switchboard and without accurate contact information to start with callers could not be properly connected. As the pool of subscribers grew further, alphanumeric numbers were introduced and used through the 1960s. This format consisted of two letters representative of location (name of the village, town or city) of the central office that the phone was connected to, followed by numbers.  Although fewer miscommunication between callers and operators occurred with the use of alphanumeric numbers, having accurate information to begin with was still imperative.

Jumping forward to today, various devices ranging from wireless phones, computers, tablets, and even televisions can be used to place calls. Somewhat reminiscent of telephone operators, virtual assistants like Apple’s Siri and Amazon’s Alexa can even be used to connect to someone by dictation which is how a four year old boy recently contacted emergency services to save his mother’s life. Although a phone number is still required for most devices, platforms such as Skype and FaceTime also use email address as unique identifiers to connect callers. While new types of contact information like email are being used more commonly, once the information is entered into the calling device you don’t need to remember it again. With just a few taps on a screen or a simple phrase, “hey Siri, call mom,” the call is initiated.

Whether placing a call now or 141 years ago starting with genuine, correct and up to date contact data is essential for reaching each other by phone. As forms of contact data continue to evolve with technology, our validation tools will as well to ensure your business communications are as fast and easy as possible.

Peer-to-Peer: The Next Frontier

How do you get millennials interested in a cause?

For starters, you don’t use traditional direct marketing techniques. Millennials won’t even answer a call from an unknown phone number more than 95 percent of the time. Email is something their grandparents used to use, with conversion rates hovering around 1 percent. And many of them don’t sit in front of a television every night passively watching advertising – they live within a broad web of individual human connections, fueled by smartphones and social media.

These are the kinds of numbers that motivated Bay Area startup Hustle ( to create a new paradigm: large-scale peer-to-peer communications via text messaging.

The Hustle platform is an enabling technology that allows text messages to be sent rapidly to people’s phones, using automated templates that can be personalized for each message. While still requiring human intervention to send messages, it dramatically increases the productivity of organizations trying to reach large amounts of people for an event, cause or campaign – and these people can text back and get responses from a real human being. The result is often a response rate in the 30-40% range.

As a result, Hustle has now attracted substantial venture funding, and its product was used to reach nearly 4 million people during the latest election season. More important, the concept of mass communication between individuals is now attracting a great deal of attention.

Of course, peer-to-peer communications are much more than a marketing technique. They are quickly becoming a revolution. You can see it in action when you use Uber to get a ride from a private car owner, or AirBnB to rent someone’s house for a week. Uber owns no vehicles, and AirBnB owns no real estate, but both companies connect people to other people on a massive scale. And in the future, respected prognosticators like Daniel Burrus and Donald Tapscott predict the same paradigm will transform banking, voting, education and many other industries that fuel our daily life.

So how can you prepare for the peer-to-peer revolution? By having better access to these peers. When you are blasting text messages to thousands of people, these numbers need to be correct. Otherwise, you face unintended consequences ranging from intrusive spamming to wasted human effort. Moreover, as you move from organizing to marketing, any one-to-one contact model needs verification tools to assess the legitimacy of your contacts and prevent fraud and waste.

Thankfully effective tools existing for verifying phone contact information. These tools include reverse lookup capabilities that can verify wireless or other numbers against US and Canadian databases, including geocoded carrier information and phone type. You can also detect numbers such as VoIP or prepaid phones for use in lead validation or fraud prevention. Taking things a step further, qualified phone numbers can have other contact information appended to them, and entered phone numbers can be contacted via phone or text for active verification by the customer.

The world is increasingly moving away from centralized market models to a distributed peer-to-peer marketplace. This means that now, more than ever, the data quality of both your contact database and your inbound contacts are emerging as key business drivers for the future. With a small incremental investment in maintaining this quality, you can be prepared to grow in an increasingly interconnected world.

People, Process, and Technology: The Three Pillars of Data Quality

For many people, managing data quality seems like a daunting task. They may realize that it is an important issue with financial consequences for their organization, but they don’t know how to proceed in managing it. With the right strategy, however, any organization can reap the benefits of consistent data quality, by focusing on three core principles: People, Process, and Technology.

Taken together, these three areas serve as the cornerstones of a structured approach to data quality that you can implement and manage. And more importantly, a framework that lets you track the ROI of successful data quality. Let’s look at each of these in detail:


This is frankly where most organizations fail at the data quality game: not allocating dedicated gatekeepers for the health of their data. It is a very easy mistake to make when budgets are tight, resources are focused on revenue-generating functions like sales or product development, and the business case for data quality gets lost amidst a host of competing priorities.

The single biggest thing an organization can do for data quality is to devote dedicated resources to it. This becomes an easier sell once you look at the real costs of bad data: for example, research shows that 25% of all contact records contain bad data, a third of marketing leads use fake names, and half of all phone numbers provided won’t connect. Run these numbers across the direct costs of customer acquisition, add in missed sales opportunities, increased customer care costs, and even potential compliance fines, and you often have the financial justification for a data quality gatekeeper.


How much control do you have over data entry points, data accuracy, and verification? For too many organizations, the answer is none – with resulting costs due to factors such as duplicate data entry, human error, or lack of verification. And who is responsible for maintaining the integrity of your business data? Too often, the answer is “no one,” in a world where data rarely ages well. An average of 70% of contact data goes bad in some form each year, which ushers in yet another level of direct and indirect costs.

One of the more important roles of a data gatekeeper is to have processes in place to manage the touch points for your data, engineer data quality in on the front end of customer and lead acquisition, and maintain this data over the course of its life cycle. Having the right policies and procedures in place gives you control over your data, and can make the mechanics of data quality frictionless and cost-effective. Or as your teachers used to put it, an ounce of prevention is worth a pound of cure.


Data quality solutions range from simply scanning spreadsheets for duplicates and mistakes, all the way to automated tools for tasks such as address validation, lead validation, and verification of email or phone contact information. And far too often, the solution of choice for an organization is to do nothing at all.

Ironically, using the best available automated tools for data quality is often a surprisingly cost-effective strategy, and can yield your best ROI. Automated tools can be as simple as verifying an address, or as sophisticated as creating a statistical ranking value for the quality of a lead or contact record. Used properly, these tools can put much of the hard work of data quality on autopilot for you and your organization.

Ensuring your organization’s data quality can seem like an overwhelming task. But broken into its component parts – your people, your process, and your technology – this task can turn into logical steps that pay themselves back very quickly. It is a simple and profitable three-step strategy for any organization that runs on data.

How Much Is Bad Contact Data Costing Your Organization?

Collecting visitor and customer data through a variety of channels allows you to quickly grow your contact list. When contact information comes in, your company is provided many new opportunities to expand your business. However, receiving high-quality data isn’t necessarily a given. After all, some visitors will enter bad contact data, such as bogus phone numbers, in an attempt to limit telemarketing calls; others may think they’re being funny by entering fake names such as Donald Duck or Homer Simpson; others might accidentally misspell a street name. Even autocorrect may change a legitimate entry, and some visitors may intentionally enter a bad address in an attempt to commit fraud.

Managing the effects of bad contact data is a surprisingly large cost for many organizations, involving a great deal of human intervention as well as diluted contact effectiveness. This is one area where an ounce of prevention is worth a pound of cure – particularly in today’s era of automated contact verification tools. Whatever your touch points are with customers or prospects – including customer data, contest entry forms, phone surveys, lead generation and point of sale interactions – some data will be inaccurate, incomplete, or fraudulent.

Why Data Quality Matters

Do you really need to worry about a few Donald Ducks or Homer Simpsons in your contact database? Yes, you do! Poor data quality translates into wasted time, resources, and money. For example, if you have a mailing list of 10,000 addresses, and 10 percent of those are inaccurate, you will waste 1,000 pieces of mail — plus the cost of product and postage – not to mention the human resources involved in processing incorrect outgoing and returned mail.

Data quality from a customer service perspective is another big concern. Suppose that a customer orders an expensive product from your website, and accidentally enters their address as “2134 Main Street” instead of the correct address of “1234 Main Street”? First of all, you would ship the package to the wrong address. Not your fault, but it doesn’t matter: delivery will be delayed, the customer will have a poor experience, and you will incur re-shipping costs. You may even not get the original shipment back. It’s a lose-lose situation.

The problem is compounded when it comes to getting these customers in the first place: an estimated 25% percent of marketing contact data is bad. And according to the Data Warehouse Institute, this ocean of bad data costs businesses over US $600 billion per year. At the level of the individual company, this means that over a quarter of your sales and marketing resources are lost to bad prospects, for reasons that range from intentional fake contact data to the natural contact record aging process. In fact, reports that after just one year, nearly 70% of contact data goes bad in some form as people change jobs, phone numbers and email addresses.

So how can your company avoid the challenges associated with bad data? Start by assessing what areas of your company need better data quality control. Whether you identify a single area or several areas that could benefit from improved data quality, realigning your data quality goals to hit the data trifecta can improve your bottom line, optimize your human capital and even help the environment.

To read more about this topic, download our white paper Hitting the Data Trifecta – Three Secrets of Achieving Data Quality Excellence.

Name Deduplication Techniques

The bane of any Database Administrator is maintaining duplicate records. They take up unnecessary space and generally do not provide any added value to contact records. A more challenging task for Database Administrators is how to identify and merge records which might be duplicates, and in particular, duplicate names.

Identifying Duplicate Records

There may be variants for a given name which might not be easily identified in a query, but they are invariantly linked. A common example might be Joe Smith vs Joseph Smith. Both could be referring to the same person depending on how the user may have entered their name.

Name Variants, Finding the Common Name

A particularly useful feature of the Name Validation 2 service is the Related Names output field. This field provides a comma-separated list of first name variants for a provided name. For example, using the given name; Joe, related names returned include Joel, Joeseph, Joey, Josef, Joseph, and José.

With this information, it becomes easier to identify names which are related but in a different form. There may be cases, however, where names cannot be identified as related but can be linked from similarity. Some examples include names that are misspelled or alternate names which are not related but similar. These names can still be identified through the Similar Names output fields of the Name Validation 2 service.

Similar Sounding Names

DOTS Name Validation 2 employs sophisticated similar name matching algorithms to match names drawing from a database of international names with up to 1.4 million first names and 2.75 million last names. First and last name similar results are returned in a comma-separated list which can be used to compare against names that already exist in the database.

An example similar name result for the given name; Robert Smith, would return similar first names Rhobert, Róbert, Robertt, Roebert, Roibert, Rubert, Robbert, and similar last names Smyth, Smithe, Smiith, Smiyth. Of the similar names that are found, names are returned in order of most common to least common.

Merge and Promote the Winning Record

Using these results, a query can potentially link similar or related names and identify records which are duplicates. Once duplicate records are identified, the question becomes which should be promoted as the winning record? This decision can depend on factors based on business logic, perhaps a record which contains other vital contact points such as address or phone number or perhaps entry date is chosen as the winning record. Once a winning record is chosen, a merge process is incorporated to merge contact fields from identified duplicates to build a complete record.


Ridding your database of duplicate contact records can be an arduous task, but with the help of Name Validation 2, it doesn’t have to be. Leveraging the vast quantity of names that Name Validation 2 draws upon yields a top quality solution to identifying duplicates through related and similar names.

For more information about Name Validation 2 service, or to receive a free trial key, click here.

For developers, our Name Validation 2 documentation can be found here.

Make Customer Data the Foundation of Your Marketing Campaigns

Gaining Insight on Customers and Prospects

No question: customers are the backbone of your business and in order to make a connection, and ultimately generate sales, you need to maintain good insight into not only who and where they are, but what they are interested in. Making that connection between a customer’s needs and your product is one of the key components in driving your company to success!

Thus, by gaining insight into your customer’s geographic and demographic details, you will be in a better position to geo-target your marketing and understand the socio-economic levels of your customers. Ultimately these insights will help you to craft more accurate and targeted messages and products to drive sales.

Unlocking Customer Value

With data being the foundation of your marketing campaigns, it’s imperative that you get a handle on the information within your contact records before your marketing efforts, budgets, and customer satisfaction is affected.

So what can happen when customer insight is not on point? Let’s look at a specific scenario:

During a recession year, your company has made the decision to capitalize on existing customers, versus putting exhaustive efforts into acquiring new accounts. Your goal is to increase profitability and customer retention by 80% in the next year.

In order to carry this out effectively, you need to better understand not only who your customers are but where they live and what specific interests are driving them to market, or better yet, to your product/services.

After extensive research, your team realizes that there are many missing data points within your customer contact records, precluding you from creating a better customer value management solution. Without solid customer insight, you are not able to understand, target, reach, and interact with their customers in the most effective way possible. 

To avoid this type of scenario in your organization, you need to have a solution that enables you to tap into the hidden insights that are waiting to be discovered within your contact records. After all, the better you can communicate with your prospects and customers, the more likely the chance that you will increase new sales opportunities and upsell your products and solutions to existing customers.

Service Objects proprietary algorithms enable you to append over 130 data points to a contact record, such as household income, age distribution, ethnic distribution, education and much more, enabling you to make more informed business decisions, and clearly determine new revenue opportunities and gain a competitive advantage.

Service Objects integrations can help improve your contact data quality, help with data validation, and enhance your business operations.

Integrating Service Objects with Salesforce

Salesforce is a great CRM that allows businesses to easily put customers at the center of their attention. But even a tool like Salesforce can be halted by poor quality customer data. Well, luckily for businesses and their data, Salesforce allows its users to call outside APIs and web services like our data validation services. If this is something that you haven’t done before, it can be a bit tricky; but don’t worry! The integration specialists here at Service Objects have you covered and we can show you how to get up and running in Salesforce in no time!

Remote Site Settings

One of the first things you will want to do to get your data validated is to add the Service Objects domain as an allowed site to access from within Salesforce. To do this, log into your Salesforce account and enter “Remote” in the Quick Find search bar as shown below.

Salesforce, Service Objects

Select “Remote Site Settings” and you will be taken to a page that lists all of the external sites that you can access from within Salesforce. Select “New Remote Site” and enter the information as shown below.

Salesforce, Service Objects

Once you click “Save” you will be ready to validate your data through a Service Objects web service. You should also add the site to the list of remote site settings as this will allow the ability to integrate proper failover configuration into your application.


If you are using REST to access a Service Objects web service, then you are good to start validating data. You simply have to make the HTTP call to one of our web services and then decide how you want to implement your newly validated data.

If you happen to be using SOAP to connect to our services, then you will have to alter the WSDL you use to connect to our services. A WSDL is a machine-readable document that tells a platform and coding language how to connect and interact with a web service. In order to do this, a bit of the WSDL will need to be altered. Lucky for you, we have already done this! We have a flight of updated WSDLs, Apex code examples, and handy guides for each of our services that will help you get up and running in Salesforce in no time.

To upload the edited WSDL, select the “Develop” link under the “Build” heading on the left-hand side of the main screen. Then select “Manage Apex Classes”.

Salesforce, Service ObjectsSalesforce, Service ObjectsOn this screen, you can select the “Generate from WSDL” button and then choose the updated WSDL to upload to Salesforce. If the WSDL has been properly edited then all the necessary classes will be successfully created and you can begin accessing Service Objects web services through Salesforce.

Your data is now ready to be validated! Once you have ensured the integrity of your customer data, you can get back to using Salesforce to guarantee the best interactions possible with your customers!

Also, be sure to check out our Free Salesforce Chrome Extension for a quick and easy validation tool to use in your browser!

Impacts of Bad Data Lead to Negative Consequences

Marketing Automation and Your Contact Records: A Five Part Series That Every Marketer Can’t Miss (Part 2)

Data integrity is beyond a doubt “the” cornerstone of your marketing campaigns. Think carefully about this. ALL company decisions, both operational and strategic, are based on the information you collect from your data. And we’ve already acknowledged that bad data exists in your marketing automation platform. So just how deep do these impacts go? Let’s dive right in, looking closely at the top two offenders: Mistrust and Costs.


“If you can’t trust the data, what else will you base your decisions on? If you can’t trust the data, how much effort will be wasted checking and rechecking certain results to figure out which is correct? And how much effort will be spent in investigations, root cause analysis and corrective actions required to fix data problems?” Carol Newcomb, Consultant with SAS Data Management Consulting

It’s no joke. Mistrust happens both internally and externally. Remember in our last post we stressed the importance of establishing trust between your marketing and sales teams (internal)? Well, that same nurturing needs to happen with your vendors and customers (external). Especially since their data is tied to everything in your organization. I would venture to guess that your CRM is connected to accounting. What if, after all your hard work to gain your customer, their invoice was sent to the wrong address? It’s going to get back to you and YOU are going to need to fix it. But here’s the bigger problem: when mistakes like this become repetitive, your reps stop believing that the data in their contact records is genuine, accurate, and up to date. They oftentimes feel compelled to update their own records. What’s worse, your customers and vendors will become annoyed, being asked over and over again, from different sources, for their contact info. Savvy marketers must realize that small missteps like this can lead to bigger issues, putting your company’s reputation and brand directly in harm’s way. Left unaccounted for, mistrust will weaken your company’s foundation in much the same way that a trickle of water slowly erodes bedrock, causing irreversible damage.

This leads us to costs:

“Most organizations overestimate the quality of their data and underestimate the impact that errors and inconsistencies can have on their bottom line.” The Data Warehouse Institute

Brace yourself…you ARE wasting money. That is, bad data is causing a loss of revenue. How many emails, direct mail, and phone calls go out on any given day? Knowing that 25% of your customer data is inaccurate due to duplicate accounts, intentional and unintentional data entry errors, lost contacts, aging contact records, there is a serious loss of productivity happening here. To demonstrate the cost of quality, let’s apply the 1-10-100 Quality Management rule by George Labovitz and Yu Sang Chang: it costs $1 to verify a record as it is entered, $10 to fix it later, and $100 if NOTHING is done, which leads to loss upon loss upon loss. And, we know that corporate data is growing at an average rate of 60% per year and climbing, so it’s all the more important to screen your data going in and then maintain and manage it over time. The takeaway: quality IN equates to quality OUT, saving you time, resources and money all the way around.

If you’re like me and enjoy a detailed checklist, you’ll appreciate the following. Business2Community has compiled a spot on list highlighting many of the consequences of bad data:

  • Lower customer satisfaction and retention
  • Loss of Revenue
  • Misinformed OR under-informed decisions
  • Dissatisfied sales and distribution channels
  • Lower productivity
  • Higher consumption of resources
  • Invalid reports
  • Failure of your marketing automation initiatives
  • Higher maintenance costs
  • Errors in product/mail deliveries
  • Increased churn rate
  • Distorting campaign success metrics
  • Higher spam counts and un-subscriptions
  • Negative publicity on social media

Hungry for more? Great! Let’s begin focusing on where to find the problems and inconsistencies so we can clean up the mess. In Part 3 of our series, we’ll get up close and personal with a lead form, how these can go wrong, and then how to correct them.

If you are interested, Service Objects provides a free Data Quality Scan that will give you insight into the quality and accuracy of your contact data. Click here to get your free scan.

Up Next: Part 3: Data Breakdown Happens. Know the Reasons “Why” and Protect it from the Start

Make Marketing Automation Work for You

Marketing automation and your contact records: A five part series that every marketer can’t miss (part 1)

Are you keeping up with the competition? If yes, then you’re likely using one of these excellent marketing automation platforms to run your campaigns:

Marketing Automation2No doubt, the planning, coordinating, and executing of your marketing efforts has never been easier. But, here’s the kicker: these platforms are only as good as the quality of your contact data.

There’s a common misconception that the quality of contact record data is automatically maintained within marketing automation platforms, but, in reality, these platforms are not built to correct contact records for accuracy nor genuineness.

Without accurate, genuine, and up-to-date contact records, even the most sophisticated and expensive platforms are handicapped from performing well. According to SiriusDecisions, it is estimated that over 25% contact records contain inaccurate or critical errors. In addition, 70% of your contact records will become obsolete/change over the year. Over time and quite systematically, the integrity of your contact records will become suspect, translating to missed lead opportunities across multiple marketing channels. So how can you decipher whether the quality of your contact records is good or bad? This is something we will look at in this five-part series.

Reaping the benefits

Switching gears, let’s imagine that your marketing automation is working at its full potential. You’re in a position to see some serious return on investment, along with reaching other important marketing and sales goals. We’ve listed three key benefits below to demonstrate why good data is at the heart of maximizing your marketing automation performance:

  • Cutting expenses—Some marketing platforms charge by the contact record. Simply correcting or eliminating bad records will result in cost savings. And this is just the tip of the iceberg. We will cover this in more detail as part of the series.
  • Increasing revenue—Handing off accurate contact records to your sales team means better contact rates and more sales, not to mention a happy sales team.
  • Accurately tracking and monitoring marketing campaigns—Good decision-making is based on good data. Accurate, measurable data is ESSENTIAL in order for these campaigns to be successful. Data needs to be precise, starting with your contact records.

Sounds so simple right? It absolutely can be, again, as long as your data is accurate, genuine, and up-to-date. And, we’ll repeat this point as many times as it takes: in doing so, you WILL save time and money!

Working smarter, not harder

Think about it: managing contact records is labor-intensive, especially in a large company. Marketing and sales teams need to establish a good workflow to efficiently turn leads into profits. And as we’ve discussed, even the best resources might need a little support themselves in order to get top results. How frustrating is it to hear complaints from your sales team, time, and time again, about bad contact information, incomplete profiles, or lead rejection? As the size, speed, and values of information increase, you might soon be spiraling out of control. The last thing you want is to contribute to the poor quality of customer data which costs U.S. businesses a staggering $611 BILLION annually. Bottom line: there is no room for error. Teams must be able to trust each other and work efficiently together. Period.

So, consider this your wake-up call as we embark on a 5-part series into the realm of contact data integrity and the role it plays in your company. It’s imperative that marketing teams understand what “bad data” is and how it affects their bottom line. We’ll wrap up the series with some solutions about how you can take action and rid your marketing automation platform of bad contact data. Before signing off, here’s something to chew on until our next post:

It’s not a question of “IF” you have bad contact data, it’s a question of “HOW MUCH”.

If you are interested, Service Objects provides a free Data Quality Scan that will give you insight into the quality and accuracy of your contact data. Click here to get your free scan.

Up Next: Part 2: Impacts of Bad Data Lead to Negative Consequences

Where Does Bad Data Come From?

We talk a great deal about data quality, validating information, and the impact on our business. Do we ever stop and think where bad data comes from? It’s not like there is some bad part of town where bad data hangs out as in some B-movie. Bad data doesn’t spontaneously appear as some clouds part. It’s not delivered by some evil version of the stork. Bad data has to come from someplace, but where?

I like to put the sources of bad data into one of three categories: people, processes, and policies. It’s not that any of this happens intentionally. In the course of doing business, we make decisions or perform actions that impact data quality. If we understand the source, we can be better prepared to address the issues. Let’s look at the categories:

The first source of bad data is people. People do enter names like “Mickey Mouse” in a web form to download a piece of information. The resulting lead quality is now very low. If I’m a salesperson, I want to be selling so I may not be very diligent entering prospect information into a CRM system. In many instances, people just don’t know. How many of us know the full 9 digits of our home zip code? Could you properly format an address on a letter to France? How many different versions of a company name could be in the order entry system because the contact center people want to get the order booked? None of this is malicious, but it happens.

The second category, process, is a little more subtle. Two companies combine through a merger or acquisition. Those companies have different ERP systems. Chances are the data in the two systems aren’t consistent, so we now have a data quality problem trying to find the common customer records. Even within a single organization, the people in accounts receivable may be treating data differently than the people in shipping. When a customer moves, the process to change the customer may not be getting enough attention. The orders and invoices are now going to the wrong place costing money and lowering customer satisfaction.

Policies can be external to an organization. Did you know that over 100 different postcode formats exist across the globe? In the US, we don’t even call them postcodes; we call them zip codes. Many countries don’t have postcodes at all. In countries like Japan, the format of the address changes depending on the language in which the address is written. The US includes states as a part of the address; most countries don’t. What happens to our data and our customers if we require a state and US-format zip code on a web form? You get the picture by now.

Rather than bemoan the state of data quality, let’s be aware of the sources. When we build our ERP systems, install our marketing automation systems, and create our websites, think about what can happen. From that point, we can help the people who use these systems and their policies and procedures cope with all the issues. Improving data quality at the source has huge payoffs.

30% of the data in your marketing automation platform is likely incorrect – see how bad your data is with a free scan!

Why We Geek Out Over Name Validation

What’s in a name? Everything — especially if you’re trying to connect with customers and prospects. If you’re emailing, mailing, or calling someone and you have her name wrong, you’ve already lost her.

The importance of name validation APIs

Name validation is becoming increasingly important in the modern world where social media and the Internet allow for a faster-than-ever propagation of bad data. For example, as people opt into various offers, it’s not unusual for auto-correct to change their entries, for a typo to occur, or for the person to enter a bogus name. On other occasions, a name that looks fraudulent and is labeled as such, could really be a legal name. This is the case for this man who legally changed his name to Fire Penguin Disco Panda:


Companies wanting to avoid potentially embarrassing situations like putting a bad name on a piece of mail, or removing a perfectly good contact with a name they think is fraudulent, should consider using a service like DOTS Name Validation, an essential ingredient in marketing automation, business databases, CRMs, and the like. Not only does name validation perform helpful changes such as parsing names into individual fields, fixing the order of names, and returning the gender of the individual, our name validation API runs a variety of checks to ensure the name isn’t a bogus, celebrity, or vulgar name.

Updated name validation scoring algorithms

We recently pushed a major update to our name validation service, including many international names as well as massive improvements to our scoring algorithms. Our name validation database now has almost 5 million first and last names in it.

Our scoring algorithms are where the service truly shines. Even when we get an obscure name that we are not sure about, we look to our algorithms to separate the unknown from the bad. This is where our team likes to geek out. We enjoy thinking of new ways to combine results to identify complex names.

Here’s where we get geeky

We love to get creative with our name validation service. We spend time pouring through lists of celebrities, vulgar names, and any crazy goofy thing we can think of.

What are some of the things we are interested in? We love unusual names. For example, should we consider the names Anakin and Khaleesi as valid now that people are actually naming their babies after these characters? And you can imagine the fun we’ve had talking about Anita Bath and Warren Peace.

We track a lot of vulgar and goofy-type potential names, but what about alterations to those? For example, we might nail the name Hugh Jass, but what about similar names like Hue Jass, Hugh Jazz, Hou Gass, or Hue G. Azz? What if someone submits the name Bob Ba$$? Could we figure out that the intended name should be Bob Bass?

What if a name is submitted that should not be a name like “House on the corner” or perhaps the name of a business instead of a person? These sorts of things can be tricky to identify in an automated system, but our team lives for solving these kinds of problems.

We let our inner geeks out so that we can anticipate and flag bogus, prank, and unusually challenging names. Though our name validation software uses algorithms to score and validate data, they’re powered by both artificial and human intelligence.

Increase Your Company’s Worth With Friendly APIs

Customer relationship management (CRM) software has become a powerful business tool. With a CRM tool such as Salesforce, Microsoft Dynamics CRM, Infusionsoft, or Oracle CRM On Demand, all customer data — including interactions and insights — is centralized for easy access and management.

As powerful as CRM applications may be, they are built for a single purpose: customer relationship management. Integrations, such as a data validation plug-in, can extend the functionality of CRMs, but only if APIs are created, and more importantly, well documented so that the third party developers can actually understand them.

CRM Basics

CRMs provide a centralized location for storing customer data and interactions. Early CRM applications, such as ACT! and Telemagic, were basically databases that stored customer phone and address data along with notes about the customer, recent orders, and so forth. Typically shared over a network, these programs allowed other employees to review contact notes as needed. They were also commonly used to create mail merge documents.

Today, modern CRMs are hosted on the cloud and loaded with robust contact relationship management, marketing automation, and social media features. These sophisticated applications are tightly focused on managing the customer’s journey. That’s what they’re designed for, and that’s what they do best. They are purposefully built to this end.

It’s a huge undertaking to create a piece of software to manage both the customer data (names, addresses, and contact information) and every single interaction across a multitude of channels. Small or large, CRM developers maintain a laser focus on their core product and its purpose. They’re concerned about making sure their software lives up to its core promise. They’re not necessarily concerned about extending their software to accommodate various users’ wish lists.

How User-Friendly APIs Ultimately Improve CRMs

While a CRM may have a plethora of tools built into it, the possibilities become endless when the CRM has an API that can be used by third party developers. For example, when Service Objects is able to integrate with a CRM’s API, we are able to create a data validation plug-in to clean up, standardize, and validate the data contained within the CRM.

This is valuable to everyone involved including:

  • The CRM developer — They don’t necessarily have the time or desire to add functions like data validation because their priorities are focused on the core product. With an API, valuable functions can be added without the developer having to expend resources on them.
  • The third party developer— Third party developers benefit by being exposed to the CRM developer’s customer base.
  • The end user — End users are happy to have external tools available through their company’s CRM platform where they can easily add the unique functions they want.

Creating an API for developers opens the door to new possibilities. A company like Service Objects can use the API to access the client’s data within the CRM, validate it, and then push it back in. With data validation plug-ins, the process is seamless for end users, the data quality improves, the business can operate more efficiently with less waste, and operating costs go down.

But there’s a catch: an API has to be available for a developer to use — complete with meaningful and current documentation. Integrations, such as a data validation plug-in for CRM, are magnitudes easier if the API documentation is up to date and organized.

We implore API creators to work hard to make a good API and supporting documentation. Doing so helps us all, and, most importantly, it helps all of our clients.

The True Cost Of Bad Data In Your Marketing Automation

Inbound marketing and marketing automation platforms promise to make your marketing more effective, and they have the potential to live up to that promise. However, reality often tells a different story — especially when bad data plays a starring role.

Marketing automation platforms like Eloqua, Hubspot, Marketo, and iContact are great tools that can help you connect with your leads and customers. But they are just that, tools. The idea of marketing automation tools is promising, but poor execution and bad data will limit your success.

The cost of bad data

You pay for every contact residing in your marketing database. If your data quality is bad, you are wasting time and money. Data quality suffers for several reasons. Some data starts out clean before going bad due to address or phone number changes. Meanwhile, it’s not uncommon for users to enter bogus information into lead and contact forms. For example, 88% of online users have admitted to lying on online contact forms.

Bad email addresses mean your messages never arrive as intended; the same is true with bad postal addresses, plus you’ve just wasted money on postage or shipping, and bad phone numbers waste your sales and marketing team’s time calling bogus numbers. Improving the data accuracy within your marketing automation platform could save a ton of money.

How much money is at stake? It’s more than you may realize. Applying Deming’s 1-10-100 rule, it costs $1 to prevent bad data, $10 to correct it, and $100 if it is left uncorrected1. So, if you had just 10 bad records, that would be $1,000 wasted. Chances are, you have far more than 10 bad records in your marketing automation software. Approximately 10 to 25 percent of B2B contact records contain critical errors2.

Moreover, using bad data has a cascading effect on the organization. Not only are you expending valuable resources to capture leads, each lead, whether good or bad, takes up a “seat” in your marketing automation plan — with each seat costing money.

The cost to contact bad leads is real. Some of the more obvious costs include printing and postage cost for direct mail and outbound calling, which average costs are about $1.25 per attempted call. Even email costs money, albeit not much (roughly $0.0025 per email), but this adds up over time if left uncorrected.

There’s more to data accuracy than cost savings alone

PrintLooking beyond obvious costs, it is important to understand the cascading impact of bad data on other areas of your business. For example, even though you are using the latest and greatest real-time CRM or marketing platform, if the data is bad, your CSRs will begin to doubt the effectiveness of the platform. This can lead to a lack of confidence in your data, poor morale, and poor performance.

Another example is the impact on your marketing intelligence reports and decision making. Marketing to bad leads will result in “false-negative” data. Since these leads do not respond (because the data quality is bad), your marketing campaigns’ performance will be dragged down.

If you don’t like to throw money away, cause undue stress on the team, or make decisions based off of bad data, improving the data accuracy of your marketing automation software can go a long way toward solving these problems. If that’s not compelling enough, consider this: clean records improve contact conversion rates by 25 percent2.

Service Objects can help ensure that the promise of marketing automation becomes a reality in your inbound marketing strategy. Our data quality tools correct and improve the data in marketing automation platforms, resulting in better performance. Benefits include reduced cost per lead and cost per sale, more reliable performance data, increased contact rates, increased response rate, reduced cost to contact, and more sales.

Isn’t it time you banish bad data from your Marketing Automation Platform?




Celebrate Data Privacy Day with 4 Insider Tricks to Help Manage Your Data Security

Here’s a list of tricks you can do to help keep identity thieves from stealing your personal data without reading the 48 page fine print legal talk that shows up with every smartphone OS upgrade.

1. Protect the “Fab 4” with Obfuscation:

Opening a credit line generally requires just 4 things: Name (last, first, middle initial), DOB, SSN and Address. So safeguarding these is paramount. They can be obfuscated – made unclear – which is what you want when showing them in the general public.

Of course, Name is hard to hide, but nicknames or shorter unofficial ones are good to consider. For example using one for eBay shipping purchases and another for Amazon, etc.

With your DOB, try to refrain from showing your birthday online, including on Facebook, but if you must then change your birth date to a different day than the one on file with credit agencies. It’s ok if your Facebook friends wish you Happy Birthday 3 days early.

Don’t give out your Social Security Number except when absolutely necessary. Many companies and forms ask for it, but do so because it is an easy identifier when in fact it is seldom required by law. So you can ‘accidentally’ type yours in with the last two digits set to your birth year.

2. The Unique Address Trick

This is how you find out who’s selling you out. When you sign up for frequent flier program, insurance, credit card, rewards programs, the girl scouts cookie order form, etc., create a unique identifier in the 2nd line of your address. For example:

John Wayne
123 Bourbon Street
Attn Delta-FreqFlierPrgm
New Orleans, LA 70116

The USPS doesn’t care what you put in that line. In fact, the USPS doesn’t even recognize a second address line as part of properly formatted address. It is meant simply for personal sorting after it arrives, so when you get the Geico or Capital One offer in the mail you’ll know who sold them your address because it will be right there on the Attn: line.

Hint: you can do the same thing with Gmail using the + symbol, see examples here.

3. Tiered Passwords

It’s hard to remember a different password for every website, so create levels of passwords or incorporate the name of the site to make the password unique to every site. You can keep 3-4 different passwords of increasing complexity using the most complex one on the most sensitive sites, like online banking.

Most Complex: Banks, Credit Cards, Paypal, AND the email accounts that are associated with them for password resets.
Complex: Online ordering platforms with stored credit cards (Amazon, Ebay, airlines etc.)
Less Complex: Facebook, Twitter, LinkedIn, etc. Sites of importance but easily fixed without monetary loss.
Least Complex: Online trials, rewards programs and sweepstakes, Starbucks app, and the like.

*Be sure to change all passwords once every few months while keeping the underlying increase in complexity.

4. Revamp Password Challenge Questions

If you’re worth it, a criminal can likely figure out your mother’s maiden name by going to sites like As for your first car, based on your date of birth + 15 years, one can probably narrow the field down to about 40 models, so take the opportunity to use those challenge questions and come up with something harder to figure out. For example, change “Ford Escort” to something like “RedandWhiteFordEscort.”

Remember, it may be easier for a thief to hack your email address and then request a password reset with your bank, so keep that secure too!

Today, Service Objects is reflecting on our data security, and we hope you do too. We are proud to be one of several hundred organizations collaborating to generate awareness about the importance of respecting privacy, safeguarding data, and enabling trust.


Revealed: 4 Fresh Lead-Generation Tools for Closers

Are you looking for fresh lead-generation tools to help boost sales? Do you have a rock star sales team already, yet know your sales force could close even more contracts if they had access to better leads? There are excellent new resources being developed for business owners and marketers thanks to entrepreneurs within the lead-generation sector. Following are four you might want to investigate if skyrocketing sales and happy customers are on your must-accomplish list:


OptinMonster offers a WordPress plugin for lead-gathering. You can create custom exit forms for your site to capture email subscribers for your business. Features include A/B testing capabilities, conversion tracking, and page-specific target messaging. If your business is using WordPress as its content management system, OptinMonster is definitely worth investigating.

Right Hello

Right Hello generates leads for businesses using a proprietary algorithm. Once qualified leads are generated, Right Hello helps connect you with potential customers via personalized emails and social media interactions. Your sales team doesn’t have to worry about discovering high-quality leads and can instead focus on closing sales with satisfied customers.


If you want to close more deals with businesses in your local area, ProspectWise is worth investigating. ProspectWise offers data on local businesses, obtained by having paid prospectors visit businesses. In addition to obtaining business cards from each establishment, lead generations sleuths interact with owners and staff to understand the needs of each company. Data is then passed onto ProspectWise customers capable of fulfilling the required needs of local business owners.


Sparta offers a handy platform to help turn your sales staff into supercharged lead-generation dynamos. You can create custom competition challenges for your staff to gamify the lead-generation and sales-closure process. Run multiple challenges at the same time for different departments and have team members compete against rival departments.

These are just four of numerous tools being developed by entrepreneurs within the lead-generation sector. Discovering fresh resources for your sales team can help increase sales while igniting team camaraderie at the same time. Will you be considering any of the above-listed tools for your sales force?

While generating leads is important for your business, making sure they’re accurate and up-to-date is even more so. All the leads in the world won’t help you if their contact information is incorrect. Be sure to clean your newly sourced leads with Lead Validation before importing them directly into your CRM to effectively reach your customers.

Moving To A New CRM? Clean Your Data FIRST!

Are you moving to a new customer relationship management (CRM) solution? While you’ve likely included various IT costs and end-user training in your migration budget, have you considered cleaning your data before your move it into your new CRM? Cleaning your data before a CRM migration is a best practice, one that will solve data quality problems, reduce costs, and position your new CRM for a successful implementation.

The pitfalls of migrating dirty data

Bad data, whether it’s a wrong address, misspelled name, duplicate or redundant, or flat-out fraudulent, is costly — and chances are, you have a lot of it. In fact, an analysis by DataBluePrint, The Cost of Bad Data by the Numbers, estimates that anywhere from 10 to 25 percent of data is inaccurate. This can seriously impact your bottom line time and time again.

For example, let’s say you have a mailing list of 100,000 and that 20 percent of your addresses are bad. That’s 20,000 mailers that disappear into the void, costing you print and material costs, postage, and manpower. Not only that, this waste happens every time you run a direct mail campaign. Meanwhile, you may have inaccurate customer data, resulting in lost or delayed orders, unhappy customers, and bad PR.

Why fix the data problem during the data migration?

First, it’s much cheaper to fix data quality issues as part of the migration than it is to let them fester. Rather than continually sending mail to bad addresses, cleaning the data will immediately solve the problem (and many others). Data hygiene quickly pays for itself anytime you do it.

When migrating data, it makes sense to fix the data problem as PART of the migration project. This is the perfect opportunity to focus on data hygiene. Just as most people clean out their junk before moving to a new home, cleaning bad data before you move creates a fresh start.

Cleaning data during migration is much easier than doing it after your new CRM goes online. After all, your old system is familiar, making it much easier to find and resolve data quality issues. If you wait until the data is in your new CRM, you’ll probably have a much harder time because everything is new and different.

It’s generally easier to approve a data hygiene project as part of the CRM upgrade than as an after-the-fact add-on. When included as part of the upgrade, the data hygiene element is understood to be a contributing — and necessary — success factor. If you tag it on after the migration is complete, you’ll probably encounter pushback and repercussions for lacking the foresight to clean the data before the move.

Fixing bad data during data migration is easier than you may think with the right tools

As part of the data migration, you will need to export your data from your legacy system and then import it into your new CRM. However, before you import it, you have the opportunity to clean it using an external data validation tool such as Service Objects’ data verification API. Service Objects’ CASS-certified data hygiene tools quickly identify and clean bad data by comparing records against a series of massive databases containing millions of accurate, standardized contact records.

This intermediary step is well worth doing as it instantly weeds out the bad data, leaving only accurate, verified data to import into your new CRM. If you’re planning a move, don’t forget to do a deep cleaning — of your data.

Sources: The Cost of Bad Data by the Numbers

Use Name Validation to Get your Customer’s Name Right

Name Validation

It’s very important in a lot of ways – it’s one of the easiest ways for someone to provide fake information on a web form but can be very tricky to properly detect. Take this example of a real piece of mail:


More processes that accept this sort of data are being run by computers. Less often human eyes review as the entire process from start to finish is becoming fully automated.

Name validation can be easily overlooked as an unnecessary addition, but the ramifications of making mistakes can be far reaching. Small mistakes can be very embarrassing, larger ones can lead to a big PR black eye for a company if a very embarrassing mistake makes its way onto the internet.

What’s going on behind the scenes

At Service Objects, we are always looking for ways to improve all data inputs at the point of entry, and name validation is no exception. We have millions of known first and last names from around the world and algorithms honed over years of work to weed out oddities in names. We are looking for celebrity names, vulgar words, words from a dictionary and things that just plain look like garbage or bogus. We constantly strive to improve our algorithms and take pride in identifying fake names.

In the example above it seems obvious that the name is bad, but to an automated process is it safe to say this is bad? What about a valid name such as Martita Boobier, which contains questionable words? What about something like Letit Boobra which doesn’t appear vulgar but also doesn’t appear to be a valid name as well? The goal of DOTS Name Validation is to properly place these names into the appropriate category to take the worry out of an automated process improperly placing them.

Avoid adding bad names to your CRM in real-time

Bad names such as “Trucker Bob”, “Doctor Nick”, “Homer Simpson”, and “Felix the Cat”, names that don’t appear to be names such as “The Big Bang” or “Service Objects”, or names that just appear to be complete garbage such as “Asdf Blah”. DOTS Name Validation can properly identify many cases that might otherwise slip through the cracks without proper review.

Why ‘Address Line 2’ Should Never Be Offered In Address Forms

You see address line 2 all the time. Your own web forms probably even have a field for it. However, did you know that address line 2 doesn’t really exist — at least in the U.S. Postal Service’s eyes? Not only does the USPS not require an address line 2, it doesn’t even acknowledge its existence.

USPS addressing standards

According to the USPS’s postal addressing standards, a complete address consists of just three lines:

Recipient Line
Delivery Address Line
Last Line

An example of a complete address using the three-line standard is:

John Doe
123 Main Street, Unit 21
New York City, NY 10001

Note that placing “Unit 21” on its own line, commonly referred to as “address line 2,” would result in a non-standardized address. While a human should be able to figure out that John Doe lives or works in unit 21, automated processing systems could have trouble.

John Doe2

Though address line 2 does not technically exist, the USPS does allow for additional information in a secondary address line (such as “deliver to dock 23.”) However, that information should be considered more like a comment area; it should not contain any deliverable address information. Our address validation software does scan address line 2 for this type of information, but there’s no guarantee the software will know what to do with it.

Suites and apartment numbers should be placed at the end of address line 1 while recipient details like name and company should go above the address.

What’s wrong with including an address line 2 field on your online forms?

Businesses commonly include an address line 2 field on their online forms, inviting end users to split address information as they see fit. When presented with two address lines, it’s only natural for users to separate floor, suite, and unit numbers into two separate lines. Some users will use address line 2 to add additional information such as “ATTN: John” or “Cross street: 2nd Avenue.”

In short, too much information can be mixed up in address line 2, making parsing out important information difficult and inconsistent. For example, if the recipient’s name is mixed into address line 2 along with an apartment number or letter, it may not be entirely clear to the address validation system what the intention of the address is since the name should have been the first line (above the address) and the apartment number should be placed in the address line itself. Situations like this can often be fixed with address validation software, but the likelihood of getting a perfect address match is reduced since there are so many ways address line 2 can be filled in.

Another issue with presenting an address line 2 for end users to complete is it invites them to mistakenly enter an alternative address line 1 (for example, their home and work addresses if both are in the same city). If both address lines 1 and 2 contain complete, proper addresses, the address validation system cannot determine the originally intended destination.

As the saying goes, garbage in, garbage out. The closer to USPS standards you can get initially, the more likely it is for an address to be cleanly validated, and the more likely it is for your mail to arrive at its proper destination. Even though our software is constantly updated and improved to handle and fix improperly structured addresses, it’s always best to strive for clean input data when possible.

Should you eliminate address line 2 from your online forms?

If you want to invite garbage in, by all means keep asking for an address line 2. If you’d rather cut the confusion and get cleaner data from the start, stop using address line 2. USPS doesn’t require it — and doesn’t necessarily know what to do with it.

Some end users don’t know that they need to enter apartment or suite numbers to the main address line 1. You can help make address input more obvious to end users by adding an optional field to the web form labeled “unit number.” You could then append the unit number to address line 1. End result: less confusion, more consistent address validation, and better deliveries.

The Problem With Bad Address Validation

Street, avenue, boulevard, and court are but a few of the many suffixes used in addresses. Add in Spanish or French variations like corte or rue and the list gets even longer. If you use the wrong suffix, such as Elm Street instead of Elm Avenue, your package may not arrive. While businesses use address verification services to avoid this problem, sometimes bad address validation backfires and changes a correct address to an incorrect one, costing businesses 

Recently, we received an email from a client needing advice about fixing a problem with her address. She said that when ordering packages on several occasions, the USPS had changed her address from what should have been a ‘Heights’ suffix to a ‘Road’ suffix. As a result, the Post Office deemed the address undeliverable because the address with the ‘Road’ suffix didn’t exist — and it returned all of her mail to the sender. 

It didn’t matter that she had entered the address correctly when ordering items online; the address would be changed to “Road” time and time again. She asked us how to fix the problem so she could properly receive packages in the future, wondering if she should call USPS or every company she orders from.

We ran her address through our address verification service and found that it would return the correct “Heights” suffix on the address. Therefore, the USPS has her correct address and is not the root of the problem. It turns out that other address verification services were changing “Heights” to “Road” when validating her address upon checkout. 

This caused the customer a great deal of inconvenience. Incorrect data in the address validation database also resulted in lost shipping costs on the business side and an erosion of trust. Businesses that repeatedly ship a package to the wrong address, despite repeated corrections, aren’t likely to earn that customer’s referrals or ongoing business.

Our data and expert algorithms allow for finding the correct address and specifically helped in this case. Not only is having address validation necessary, having the correct validation service — one that will both validate the address and confirm that it truly exists — will save both businesses and customers time and money.

Canadian Address Privacy Concerns

Canada has several privacy laws regulating the collection, use, and disclosure of personal information in the course of commercial activities. Under Canada’s private sector privacy laws, personal information is not allowed to be passed back and forth across the border unless the individual is notified. As alarming as this may sound if you’re a Canadian business using a US-based address validation service to validate customer addresses, rest assured that this is NOT an issue with Address Validation since address data does not fall in this category. 

Canada’s federal Personal Information Protection and Electronics Document Act (PIPEDA) applies in all provinces that lack their own substantially similar legislation. Currently, British Columbia, Alberta, and Québec all have substantially similar legislation covering private sector privacy issues. In general, personal information is defined as “information about an identifiable individual.” 

Service Objects has many clients in the US and Canada who call our real-time APIs to validate both USA and Canadian mailing addresses in order to improve deliverability rates and cut waste. Because privacy is always a concern whether there’s a law in place or not, they’re right to wonder if using address validation infringes upon their customers’ privacy. Rest assured, it does not.

We do not see or store the data in any way  

Among the finer points of the law is the distinction between “transfer for processing” and “disclosure.” According to the Office of the Privacy Commissioner, PIPEDA does establish rules governing transfers for processing. A transfer for processing is a “use” of the information; it is not a disclosure. Assuming the information is being used for the purpose it was originally collected, additional consent for the transfer is not required.” 

Thus, if you originally collected address information for delivering a product your Canadian customer ordered, having a US-based address validation service process that address to verify its deliverability is a use — as intended. It is not a disclosure. And again, we never see or store the data.

If you need to validate a Canadian or US address and want extra assurance that you are not compromising your customer’s privacy or running afoul of Canada’s private sector privacy laws, you could simply pass only the address. There’s no need to pass a name with the address.

We understand — and share — your concerns about customer privacy. It’s an issue we take seriously and proactively address.

Try out DOTS Address Validation – Canada 2 for free for 30 days and let us know what you think:

Origins of Contact Data

You have a database filled with contact information. Great! However, before you launch that next direct mail campaign, you may want to do some preliminary contact verification. Depending on where your data came from, your database could have a serious case of the poor data quality blues. How your data fares in terms of data quality depends on where it came from, how old it is, and how long it’s been since the list underwent address verification.

So, where did your contact data come from? Generally speaking, you can either have first party, second, or third party contact data, or a mix of the three.

What is First Party Data?

First party contact data is contact data provided directly from your customers and prospects. For example, when a customer orders a product from your website and supplies you with his or her name, phone number, email address, and shipping address. While presumably genuine and accurate, contact verification is still recommended for verifying first party data due to occasional typos, autocorrect errors, spelling errors, mistakes, and even concerns about fraudulent orders. In addition, due to frequent address changes, plan on using data quality software to verify and correct contact information on a regular basis.

What is Second Party Data?

Second party contact data is data sourced from indirect channels such as via a partnership with another business. Here’s how describes second party data: “…somebody else’s first party data.”

Like first party data, contract verification is important. While this data is presumably “clean” because your partner’s customers and prospects provided it directly, mistakes and errors are common and should be corrected and all addresses standardized. Data quality software makes this a snap. Plus, when was the last time your partner ran address verification on its list, and how old is that data? Again, you’ll want to run both an initial address verification check as well as cleanse the list on a regular basis to ensure you have the most current contact information possible.

What is Third Party Data?

Third party data, as the name implies, comes from a third party. It is generated externally from your company, and often aggregated from various sources. In fact, providers of third party data are frequently referred to as “data aggregators.” For example, when you buy demographic data or a mailing list from a data aggregator, that data is third party data. Though third party data has its place, it’s not necessarily as trustworthy as first party data. It really depends on the source.

Depending on the source, and depending on whether or not the data aggregator uses data quality software of its own, third party data could be filled with inaccurate contact information. Contact verification is an absolute must to clean up this data before you use it.

The Importance of Using Data Quality Software for Contact Verification
No matter how high quality your data may have been originally, as contact and demographic data ages, its quality degrades. People sell their homes and move away, business professionals move from one company to another, cities rename their streets, and so on.

So, a few mailers will come back as undeliverable; what’s the big deal? It’s not a big deal if you have a small list and are willing to manually correct addresses, but it becomes a big problem as your list size grows.

Service Objects’ real-time address verification API instantly corrects addresses and reduces costs, helping to ensure that your marketing dollars are well-spent and that you messages reach their intended audience. Whether you have first, second, or third party data, don’t you want that data to be current and accurate? Sign up for a free trial key and recover from the poor data quality blues.

No image, text reads Service Objects Tutorials

Infographic: Hit the Data Trifecta to Ensure Data Quality Excellence!

Last week we released our newest whitepaper – Hitting the Data Trifecta. To accompany it, we’ve created a guide to help you determine what type of contact validation tool you’ll need to help with different types of incomplete, incorrect or potentially fraudulent contact information.

With genuine, accurate and up-to-date contact data, you’re on the way to data quality excellence and hitting the Data Trifecta!

Data Quality Infographic

Introducing: The Data Trifecta

Data quality, or lack thereof, impacts businesses in many ways. Poor data quality, for example, wastes time, paper, and money. Poor data quality can also mean shipping delays, canceled orders, and fraudulent orders. Examples of poor data quality include: typos in addresses such as “Lem” Street instead of “Elm” Street, bogus names such as Donald Duck, missing or incorrect ZIP codes, transposed phone numbers, and IP addresses that don’t align to contact info.


In contrast, excellent data quality means that your business, marketing and operational efforts pay off. Your team won’t waste time calling wrong or non-existent phone numbers or sending expensive mailers to nowhere. In addition, ensuring data quality helps to catch potentially fraudulent orders before they are processed. Excellent data quality doesn’t happen by accident; you need to implement the right tools in order to hit the “Data Trifecta.”

Data Trifecta

What is the Data Trifecta?

The Data Trifecta contains three equally important data quality components: genuine, accurate, and up-to-date data.

Hitting the Data Trifecta is a worthy goal, and it’s easier to achieve than you may think. Learn more about the Data Trifecta and data validation by downloading our free whitepaper, Hitting the Data Trifecta, today.

5 Reasons Why Customers will Thank You for Using Contact Validation

Contact validation is commonly used to prevent fraud and build businesses. The business case for contact validation is well established, and these tools are essential to protect and build your business. However, did you know that your customers benefit from validation, too?

For example, showing your customers that they are protected reassures them, builds your credibility, and is helpful to both the sale and future visits. No one wants to be vulnerable to identity theft. No one wants their name spelled incorrectly and their packages shipped to an incorrect address.

Customer SatisfactionSo, is contact validation really a selling point? You bet it is! Below are five reasons why your customers will thank you for using contact validation:

1. Form validation protects customers and non-customers against identity theft and fraud. Most businesses first explore form validation as a means of protecting themselves from fraud. According to Javelin Strategy & Research’s 2014 Identity Fraud Report, credit and debit card fraud was an $11 billion problem for merchants in 2013. Individuals are concerned as well. After all, it’s their identities and credit and debit cards that are being stolen.

Whether someone is a customer or not, form validation protects an innocent party from identity or fraud theft should a fraudster enter your form or checkout processes. Form validation services can check the shipping and billing addresses against IP address and phone number, which can thwart criminals from placing orders.

Telling your customers and prospects that you perform contact validation can eliminate consumer fear and boost your credibility.

In addition, should your security be breached or your contact / customer information stolen, your system will not allow any customer information to be changed without sending warning flags. Form validation can serve as a second line of defense should a breach occur.

2. Address verification helps ensure faster shipping and guaranteed delivery. Fast shipping is a must in the era of mega-retailers that offer same day deliveries and free two-day shipping. Today’s customers expect to receive their packages right away and have little patience for shipping delays. At the same time, you want your package to arrive safely in order to reduce the likelihood of lost merchandise, cancellations, or additional shipping costs.

Address validation helps to ensure that your customers get their packages when promised — even if the customer inadvertently transposed a number or misspelled a street name in the shipping address. If the package doesn’t arrive, guess who the customer will blame despite their own data entry mistake?

By verifying addresses at the point of entry, you can correct incorrect address information, make sure the address conforms to US Postal Service standards, and ensure that the address is deliverable. Address verification is a valuable customer service tool that prevents unnecessary shipping delays and undeliverable packages.

Being able to accurately verify addresses, delivery dates, and delivery times from a perfectly standardized address demonstrates that you know what you are doing and are operating an efficient business. Instead of immediately blaming you when a package doesn’t arrive as expected, your customers may realize that the package may have been delivered (after all, your system verified and, even corrected, the address) and someone on their end may have forgotten to pass it along.

3. Name validation helps you to get your customers name right. A sure-fire way to offend someone is to spell his or her name wrong. Another way to offend someone is to assume you know his or her gender based on a first name.
For example, Pat, Chris, J.C, Dana, and Val could be men or women. It’s hard to tell based on names alone. Guessing could be a disastrous mistake.

If you offer gender-specific products, name verification tools can help you filter names that aren’t gender specific. Make sure you have your customer’s gender correct or neutralize your messaging, but never guess.

Getting your customers names and genders right helps to avoid offending them. It also helps them to feel valued and as if you know them. Even when doing business virtually, customers want personal service. They’ll return to businesses where they feel known and valued. Name validation can help you to build loyalty.

4. Email verification ensures timely communications via email. It’s not just about shipping packages; it’s also about communicating. Airplane flights, package delivery notifications, service notifications, event invitations, and other alerts all arrive via email. What happens if a customer accidentally forgets the dot before the “com” in their email address? What happens if a customer enters “gnail” instead of “gmail” in a gmail address? Your email messages will never arrive. Email verification checks the syntax, removes extraneous letters, and fixes common typos in level 1 domains.

Timely email notifications are as important as timely package delivery. Impress your customers with effective use of emails – they’ll thank you for it!

Email verification also helps detect possible fraud. For example, if a fraudster attempts to use a customer’s data but enters a bogus, catch-all, or disposable email address, warning flags will be raised. Your customers may never know about fraudulent attempts, but they’ll benefit nonetheless because of the extra security measures you have in place to protect them.

5. Demographic data helps customers receive customized product and service opportunities. Demographics targeting can be a valuable tool for businesses and customers alike. Using demographic data to match products and services to prospects is a fantastic way to build your business and help your customers to feel valued and known. Customers appreciate receiving relevant offers. Sending accurate, specific alerts about products and services to those who want, need, or would benefit from them isn’t just about increasing your sales; it’s also about connecting with them. Demographic targeting allows for greater personalization.

In addition to recommending products based on your customers’ interests, past purchases, location, and other demographic details, you can also promote content that speaks to your customers. If your content speaks to your customers, it probably also speaks to their friends. Thus, they may share your offers, helping to build your business through word of mouth.

Use demographics to dive deep into your customer database to spot trends that can help you focus on what your customers want and need. Look at age, gender, and income to discover what drives purchases in your sales area. Determine what to write about and what products and services to offer by evaluating news stories in conjunction with your demographic data.

Contact validation is just as important to your customers’ experiences with business as it is to internal protection and growth efforts. With the right contact validation tools in place, you’ll protect your customers from fraud, ensure prompt package and email delivery, build loyalty, and understand who your customers are. Everyone wins, and your customers will thank you for it.

Name Validation – The Most Important Data There Is

DOTS Name Validations 2

“Remember that a person’s name is to that person the sweetest and most important sound in any language.” – Dale Carnegie, “How to Win Friends & Influence People”

In today’s highly connected world, we have more opportunities to connect with people than ever before. But what if those opportunities are overwhelming not only to us but to our prospects as well? Companies are fighting hard to put themselves in front of customers and prospects in an ever-crowded marketing space.

One way to give your company a competitive advantage is to show your customers how important they are to you – not just as a revenue source, but as a unique individual.To accomplish this lofty goal, the first and most important step is to address your customers by their correct name and gender-specific title – whether over the phone, in an email or letter. What woman wants to get a letter addressed to Mr. Jane Doe? Do you know any men that want to be called “Miss Christopher Smith?”

A robust name validation service can help ensure that each contact name in your database is spelled correctly and aligns with the correct gender of the name. This will help you personalize your outbound communications, and show your customers that you care to know them at the most basic level.

A second critical step is ensuring that the name is “genuine” — why clutter your contact database with names like Mickey Mouse or Britney Spears? A reputable name validation service clears out bogus, vulgar and celebrity names, as well as garbled keystrokes. Removing disingenuous names allows you to focus on the real prospects that are interested in your products or services. Plus you’ll be reducing any waste caused by creating and preparing materials for bogus contacts, or follow-ups involved.

Often name validation is overlooked in overall data quality. If your company does not solve for this, you run the risk of reduced customer satisfaction. Learn how DOTS Name Validation 2 can be integrated into your existing systems. Our proprietary database of nearly 10 million names will help take your business to the next level.

Shakespeare once wrote, “What’s in a name? That which we call a rose/By any other name would smell as sweet.” The question is, would he have felt the same if he had received correspondence addressed “Dear Ms. Shacke Spear…”?

Email Append – The Good. The Bad. And the Ugly.

Because of the prevalence of multi-channel marketing, email append has become a widely used method for companies to build their in-house email database with permission-based addresses. It’s one of the most useful tools to get up and running. But it’s a service that is mired in controversy. And rightfully so.

The CAN-SPAM Act, a law that sets the rules for commercial email messages, gives recipients the right to put a stop to any incoming emails that are unasked for or undesired. This law insists that companies sending email make it easy for recipients to clearly understand how to opt out of receiving future emails.

Some in the industry say that appending is simply not an acceptable email marketing practice. That it is not permission-based and is not compliant with CAN-SPAM regulations. What is important to understand is that to use appended email address properly you must ensure that every recipient has, in fact, given their permission to receive emails and retains the right to opt out at any time.

DOTS Email AppendSM is great example of a modern email appending tool and an excellent way to build on an existing contact list. For example, a retail catalog company may decide to use email marketing, a method that is relatively inexpensive compared to direct mail. They already have their customers’ postal addresses and DOTS Email Append uses that list to append email addresses to their existing address data. It is now this company’s responsibility to send newly identified email recipients its own message, asking if they have permission to continue to communicate via email. Our DOTS Email Append requires all customers to take this or similar actions, thereby complying with CAN-SPAM.

Even with an extensive list of customer names and addresses, the catalog company in our example had no way to mine those for email marketing. With DOTS Email Append, they are able to do just that. Now after creating a permission-based email list, they can move forward and use this email list to help increase the effectiveness of all marketing and communications programs.

The bottom line? Used with CAN-SPAM compliance, email append is a great tool to give companies additional opportunity to skyrocket revenue and keep in closer touch with prospects and customers.

Updated DOTS Address Geocode – US Data

This week I’d like to discuss an important update to our DOTS Address Geocode – US Web Service. One of our many sources for geocoding US addresses is the TIGER/Line database, published by the Census Bureau. This particular database is updated and published twice a year, and we update our services with the new data as soon as possible. A typical update may take a week or two to implement and test.

Our regular update procedure was interrupted when the Census Bureau announced a new database format for the latest release. Due to our proprietary method of combining street data sources, we needed to rewrite much our DOTS Address Geocode – US service from the ground up in order to work with the new database format.

This was not an easy task–it took months of research, development, and testing to ensure we had done the job right. During the development, we took a fresh look at every step of the geocoding process and made dozens of changes. As a result, we can now locate even more addresses at the property level, and have substantially increased accuracy. At Service Objects we are always looking for ways to improve our DOTS Web Services!

We strive to keep our data sources up-to-date so you receive the best information available. Updating our DOTS Address Geocode – US service was time well spent, ensuring fresh data and faster updates in the future. We’re confident that these changes have added value to the service and will greatly benefit our clients.

Thank you for reading,

Alex P.

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