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.

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!

DOTS Lead Validation – International has been available for almost a year, and we have received great feedback from our customers on how they are using it. Using this feedback, we have compiled some general best practices to help you get the most from the service and learn how it helps your business.
There are two main uses for this service, prioritizing leads and regulatory compliance.

Lead Prioritization

When your business generates hundreds to thousands of leads daily, it is best to prioritize them based on their quality. One of the simplest ways to determine a lead’s value is using the two outputs from Lead Validation – International; OverallCertainty and OverallQuality. OverallCertianty is a value that comes back in the range of 0-100 and represents how likely the prospect could be contacted with the information they provided. The OverallQuality output shows whether a lead should be rejected, reviewed or accepted.

Each main component of a lead (name, address, email, phone, IP address, and business) is also scored this way. For example, the address component also has certainty and quality scores directly associated with it, AddressCertainty and AddressQuality. The purpose of these individual component values is to allow you to see how the components’ scores break down and make even more informed business decisions.

GDPR Compliance

The second major use we have seen for the Lead Validation – International service is determining if any component of your lead is from a country that falls under the General Data Protection Regulation (GDPR). We have made this simple to identify by providing an output, IsInGDPR, which simply identifies that your lead is covered by the GDPR. Our customers are using this to ensure they stay in compliance with the regulation and avoid its hefty fines.

Now that we’ve outlined its main uses, let’s focus on the three most important parts of the service: Inputs, Test Types, and Outputs and how they can be used.

Inputs

The more inputs you have, the better the returns will be. The service heavily cross-references the individual inputs for each component, which means the more data points you share with the service, the better we can analyze the data.

Some organizations simply do not collect all the data points, or the data they buy doesn’t include them. For these reasons, it is very common to have an abbreviated number of inputs for the service. But Lead Validation – International goes a step further and makes adjustments along the way to help maximize results when not all data points are available. If you are missing an IP address, company name, or another data point, Test Types have you covered.

Test Types

To avoid penalizing lead scores because of lack of data, TestType is a required field that works like a directive to the service, adjusting the algorithm itself to work with the data available. Using a test type is not only required, it is also just as important a consideration as the other input data. For example, attempting to validate business leads without using TestType=business will skew the results, leaving you scratching your head at the end of the day. Best practice is to match the following test type to your available inputs:

Standard Test Types

• normal1p/normal2p – Incorporates all the main components except the business component. The only difference between the two types is that normal2p allows for a second input phone number, where normal1p is limited to one.
• noip – Same as normal1p, but does not incorporate IP address input in the processing.
• nap – Simple but common test type that looks at name, address and phone components, a second phone number is optional.

Business Test Types

Designed for business-to-business leads, not having a business name in a business test type is allowed, but providing a business name returns better scores.

• business – Like normal2p, but adds the business component.
• business-noip – Like the business test type except it does not utilize the IP address component. While designed for data with a missing IP address input, this is NOT one of the more recommended operations. Having the IP address as an input for business to business leads provides strong links to connect to other data points and provides some useful flags for fraud.
• business-n-e-p – Checks name, email, and phone components.

Custom Test Types
Custom test types can be created for specific needs. In some instances, you may have a component that you don’t have much confidence in and want the system to be less strict in analyzing. Conversely, some organizations may have fields that are so critical that they want to scrutinize specific components over others. Most organizations fit into one of our predefined test types, but customizations are available to ensure unique business needs are met to maximize the results from our service.

Multiple test types
Some companies use multiple test types. It is less common to see multiple test types in the same process, because if a field is missing you likely want that lead to be penalized in OverallCertainty. However, you may have multiple processes fed by leads from several departments and various sources, so ideally you will match the test type to the process and available inputs.

Outputs

Lastly, you will want to pay attention to the OverallCertainty and OverallQuality fields when prioritizing your results. It all comes down to the higher the certainty, the better the lead. There are several factors to consider when thinking about prioritization. For instance, cost of leads, sales team bandwidth, or automated CRM lead scoring could all affect priority outside of validation. Your organization will make these considerations before making any final decisions.

The Notes field is helpful for tying everything together, and will help you understand how the return was generated. The service will output general notes about the validation such as IsNamePhoneMatch or IsPhoneAddressMatch, but also creates Notes about each individual component like IsBadStreet for address or IsPublicProxy for IP Address. Each component that can associate itself to a country can impact the output, IsInGDPR, indicating if the lead or a component of the lead falls under GDPR.

In closing, it is worth reiterating that the quality of the results from Lead Validation – International are predicated on the number of inputs and using the correct test types. This service helps you prioritize your leads, identify the weak and the strong points in your data, and stay in compliance when it comes to GDPR. If you’re working with international leads, reach out to our team to learn more about how our validation service can help your business.

The old saying “garbage in, garbage out” has been around since the early days of modern computing. Code for operator error or bad data, the adage implies that the output of a program is only as good as the input supplied by the user. With more data being collected, stored, and used than ever before, data quality at the point of entry should be a top priority for all organizations.

Now that data is informing more aspects of our businesses, it’s not difficult to imagine a future where data accuracy is vital. Think of delivery drones, which have been tested all over the US and UK in recent years. If a contact’s bad address information goes unchecked, it could feed a drone the wrong coordinates resulting in misdeliveries and lost products.

Data quality affects every aspect of your business, from sales and development to marketing and customer care. Yet a 2017 survey by Harvard Business Review found that “47% of newly-created data records have at least one critical (e.g., work-impacting) error.” So, what constitutes garbage input? It depends on the data and how it enters your system.

What Is Bad Data?

Of course, there are many kinds of data an organization may choose to collect, but here we will focus on one of the most critical – contact data. This includes a contact’s name, address, phone number and email, all of which are crucial to marketing, sales, fulfillment, and service.

Some common issues that make a contact record bad:

• Inaccuracies like bad abbreviations or missing zip code
• Typos caused by speed or carelessness
• Fraudulent information
• Moving data from one platform to another without appropriate mapping
• Data decay as contacts move, get new phone numbers, and change positions

So, how does a bad contact record make it into your database?

Contacts entering their data online, whether downloading a whitepaper or ordering a product, are usually the first to commit a data quality error. Filling out an inquiry form on a mobile device, rushing through a purchase, or providing inexact information (such as missing “West” before a street name) are all examples of bad data leading to inaccurate contact records.

Your sales and customer service team can compound poor data quality by manually updating information that looks incorrect and making mistakes in the process. Good business practices can help mitigate operator error, but if a record was poor to begin with that likely won’t matter – you already know what happens to garbage when it ages.

What Is the Cost of Bad Data?

Much like garbage, bad data only gets worse over time.

Poor data quality can cause an organization’s sales team to waste time and effort chasing bad leads. According to a 2018 study by SiriusDecisions, B2B databases contain between 10% to 25% of critical contact data errors. That means up to 1 in 4 leads could have bad phone or email information attached, so follow-up communications may never reach the intended contact.

The customer service department loses time and money first in dealing with unhappy customers – even if they provided poor contact information, they’ll still blame your business for a package that never arrives. Additional time is spent troubleshooting problems and clarifying bad information, leading to major inefficiencies and frustration.

Overall costs to businesses include reputation related losses that occur when upset customers take to the internet to air their grievances. Time is lost due to the hidden data factories that arise within an organization when individuals working with bad data take it upon themselves to make “corrections” without understanding why or how the data is incorrect. Lastly, poor data robs a business of the ability to take full advantage of business tools like marketing, sales automation systems, and CRM.

How Can My Business Fix Bad Data?

Tightening up business policies around collecting and managing data is a start, but implementing data validation services will help ensure your data is as genuine, accurate, and up-to-date as possible and keep contacts current through frequent updates. Contact data validation can be integrated in a number of ways to best meet the needs of individual organizations, including:

• Real-time RESTful API – cleanse, validate and enhance contact data by integrating our data quality API’s into your custom application.
• Cloud Connectors – connect with major marketing, sales, and ecommerce platforms like Marketo, Salesforce, and Magento to help you gather and maintain accurate records.
• List Processing – securely cleanse lists for use in marketing and sales to help mitigate data decay.
• Quick Lookups – spot-check a verbal order or cleanse a small batch.

Service Objects’ validation services correct contact data including name, address, phone number, and email and cross-checks it against hundreds of databases to avoid garbage input. The result: cleaner transactions and more efficient processes across all aspects of your business.

Contact our team to determine which of our services can help you collect and maintain the highest quality data and kick the garbage to the curb.

This week, October 1-5, was Customer Service Week: a nationally-recognized event first proclaimed by the US Congress in 1992. It was designed to recognize the work of customer service professionals in the United States – over 2.5 million nowadays, according to the Bureau of Labor Statistics – and educate people about the importance of customer service in business.

This is always one week where you hear a lot of people talking about customer service. Let’s be honest, if you were to ask any business leader whether customer service was important to them, they would all reply “of course.” But to us, good service is a little like a good athletic performance: it isn’t just an attitude you can summon on command, but rather the end product of having the right culture and practices every day.

As part of our Customer Service Week, our own team made a list of traits that define our approach to customer service, using the letters of S-E-R-V-I-C-E O-B-J-E-C-T-S as a guide:

This is actually a pretty good summary of who we are. Let’s look at how these terms break down in terms of our approach to our customers:

Data Ninjas: This was our favorite. We’re good at what we do, and we take lots of pride in our expertise. We aren’t the only company in this space, but we’ve provided enterprise-level data quality solutions for over 15 years – and everywhere from our development team to our 24/7/365 technical support, people have a healthy “ninja” mentality about being experts and continually learning.

Customer, Friendly, Exceptional: Let’s face it, customer service tends to have this smiling-person-with-headset stereotype. But if you’ve worked with us, you’ve probably noticed: we really are pretty friendly, with customers and each other. Whether it is our knowledgeable, low-pressure approach to sales, our technical professionals, or even (in all immodesty) our marketing team, you can tell that we like each other – and like working with you, too. This starts with being a cool place to work, and also springs from supporting people to do the right thing with our customers.

Accurate, Precise, Exact: Every great company has a fanaticism about something. With us – being in the data quality business – it is accurate results. People depend on us to provide accurate leads, contact data, tax rates, and a host of other real-time, mission critical information. So much like the bakery that goes the extra mile to make the perfect croissant, getting it right every time is our particular fanaticism.

Innovative, Creative, Advanced, Insightful: This industry doesn’t stand still, and we have a lot of fun leading the curve with new tools and capabilities. This year alone, for example, we have rolled out everything from API and service enhancements to our bundled Address Insight capabilities, as well as educational white papers and articles ranging from GDPR compliance to email marketing.

Effective, Authoritative, Global: This is the part of our service reputation we eventually grew into. When our CEO Geoff Grow first started this company in 2001, to correct contact addresses and reduce the waste stream of direct mail, few people envisioned Service Objects as the global company we are now. Today we serve over 2500 customers – including major firms like Amazon, Microsoft, Verizon and American Express – and proudly wear the mantle of an industry leader.

These are some of the reasons that every week is Customer Service Week for us, and why we have built so many long-term partnerships with customers. Last but not least, let us know what we can do to serve you too!

Enterprises are dealing with more data than ever before, which means that proper information architecture and storage is crucial. What’s more, the quality of the data you store affects your business more than ever nowadays. This goes double for your contact data records, because you need the most accurate and up-to-date lead and customer data to ensure that marketing, sales, and fulfillment all run smoothly.

Master Data Management, or MDM, involves creating one single master reference source for critical business information such as contact data. The goal of MDM is to reduce redundancies and errors by centrally storing records, as well as increasing access. No matter how well organized your database might be, the quality of its data will ultimately determine the effectiveness of your MDM efforts.

Why is Master Data Management Important?

Organizations look to MDM to improve the quality of their key data, and ensure that it is uniform and current. By bringing all data together in a hub, a company can create consistency in record formatting and ensure that updates are available company-wide.

MDM sounds simple in theory, but think of how (and how much) information is created and collected within an entire organization. Let’s take a single customer contact as an example. Over the course of a month, John Smith provides information to your company in three different instances:

1. First, he is an existing customer of your services division, and his data exists in their customer records.
2. Second, he visits your website and downloads a whitepaper, getting added to your marketing department’s database of leads.
3. Third, he calls the sales team for one of your specialty products, and gets added to their database of contacts.

In a typical organization with departmental “silos,” John Smith is now part of as many as three separate databases in your company, none of which have a longitudinal view of his relationship with you as both a customer and a lead. Worse, slight differences in contact records could even turn John into three separate people in a master database. If each of these touch points get assigned to different automation drips and your sales reps are calling and emailing, you have a real disconnect in your efforts and a high likelihood of spamming your contact.

Having good data collection and storage practices is the first step to a good MDM program, but that alone may not solve John Smith’s problem. Ensuring the data he provides is correct, current and most importantly consistent at the point of entry is what guarantees that the best quality contact information is stored as master data. Implementing a lead validation service could help solve this issue at the point of entry by cross-validating each contact record with multiple databases in real time, facilitating accurate merge/purge operations later.

Lead validation not only corrects and appends contact data, it can also feed into your CRM and automation tools to help you further qualify your leads, so your sales team is only dealing with the highest quality information and pursuing genuine prospects. Once your prospects become customers, their contact data records will be passed on to other departments to complete any transactions – and through your MDM they will also have the most up to date and accurate information to conduct their business.

The Costs of Poor Data Quality

In a 2018 study conducted by Vanson Bourne, 74% of respondents agreed that while their organizations have more data than ever, they are struggling to generate useful insights. Some say this is because they are not effectively sharing data between departments, but only 29% of respondents say they have complete trust in the data their organization keeps.

Every aspect of your organization can be impacted by poor data quality, especially if your contact data is lacking. If 71% of your sales team feel that their lead information is bad, how effectively can they do their jobs?

Here are just a few of the ways that bad data can hurt your business:

• Marketing – sending marketing materials to existing customers for discounts for new subscribers, spending extra money creating mailers for addresses that don’t exist
• Sales – Multiple sales reps calling the same lead, the same sales rep calling the same lead multiple times, wasting time on bogus leads
• Order Fulfillment – bad or incomplete address data causing failed deliveries and chargebacks
• Accounts Receivable – sending invoices to incorrect addresses or old business contacts, billing addresses not matching credit card records
• Business Development – making bad decisions for growth in a particular market based on inaccurate data

Each of these issues could be solved by creating a master data management system and making sure it is only fed validated contact data from the point of entry. Further, frequently updating the MDM system by validating name, address, phone, email, IP, and other key pieces of information ensures that each data record is as current as possible.

Finally, one major cost of poor data quality – and a key reason for the growth of MDM – is the compliance risk as new data privacy and security regulations have emerged in recent years. For example, the European Union’s recent General Data Protection Regulation (GDPR) and the US Telephone Consumer Protection Act (TCPA) both have severe penalties for unwanted marketing contacts, even when such contact is inadvertently due to data quality issues like bad contact data or changed phone numbers. Accurate, centralized data is now an important part of compliance strategies for any organization.

Trends in Master Data Management and Data Quality

The competitive advantages of consistent centralized data – together with the advent of cloud-based tools for data quality – have made MDM a growing trend for organizations of all sizes. Moreover, David Jones of the Forbes Technology Council predicts that increasing regulation and the rise of cybersecurity risks are converging to change the way data is managed at the business level. We now live in a world where things like validating contact data, rating lead quality, verifying accurate and current phone or email data, and other data quality tools have now become a new standard for customer-facing businesses.

Today, adding a contact data validation service to your processes before storing master data will improve overall data quality and increase efficiencies among all of your teams. Service Objects offers 24 contact data validation APIs that can stop bad data from undermining your master data management system. Want to learn more? Contact our team to see which API is best for your business type.

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.

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-certified^TM 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.

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 Realtor.com.) 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.