A quick online search of the US white pages shows that there are over 1500 real people named George Washington, more than 50 named William Shakespeare, and a surprising number of Steven Spielbergs. There is even a recent tongue-in-cheek commercial featuring a real person named Mac(kenzie) Book touting the benefits of the Microsoft Surface laptop.

When it comes to your contact database, however, fake or incorrect names can cost you real time and money – and can even make you vulnerable to fraud or damage your brand reputation. In this article, we will look at how validating first and last names can give your business the power to make sure you have genuine, accurate contact records for real customers and prospects.

Why the right name is important

There are several reasons why effective contact records start with having the right name:

• Getting the name – or gender – of someone wrong can leave a bad impression with customers and prospects.
• Fake names such as “Donald Duck,” often submitted to obtain free information from marketing campaigns, waste your time and increase your costs every time you run a campaign.
• Bogus or garbage names that cannot be traced to real people can be a flag for suspicious activity, such as fraudulent orders or marketing inquiries.

In addition to having valid names to protect your contact database integrity, learning more about these contact names can also lead to more profitable marketing efforts and customer relationships. For example, knowing a person’s gender, or whether a contact is a business or personal name, can help you target your contact activities more precisely. In this way, name validation gives you the ability to both verify and enhance your contact data assets.

How name validation works

So how does it work? DOTS Name Validation parses names from anywhere in the world into individual data fields, while checking them for accuracy and validity.

This service is easy to use: its input consists of a name string, together with some optional parameters for special cases. In response, it outputs a validated name where possible (or sometimes two names, if your input consisted of a string such as “Steve and Mary Smith”), as well as a wealth of associated data. In addition, Name Validation retains important accented characters often found in global names in the output of the service.

Here are some of the things we check for:

• Whether this name validates against a proprietary global database of millions of domestic and international names
• Individual data fields for the name’s prefix (Mr., Ms., etc.), first name, last name, and suffix (such as Jr. or Sr.)
• The suggested order of the name: for example, changing “Jones John” to “John Jones”
• Quantitative scores for the likelihood that this name consists of a vulgar, garbage or celebrity name, as well as common dictionary phrases such as “White House”
• The likely gender of this name, including a “Neutral” response for names common to both genders
• National origin of common names
• Whether this name is a business or a person
• Related names (such as Bill or Billy for William)

Perhaps most importantly, we indicate whether this name appears to be valid, as well as a “best guess” name for those that are unable to be validated. Armed with this information, you can flag suspicious names for removal or further processing and have a greater degree of confidence in names that pass validation.

Good marketing starts with knowing your customer

Aside from better data hygiene and contact quality, there is another very important reason for getting accurate customer name data: it is the key to personalizing your marketing efforts.

A recent survey of over 1000 consumers showed that personalization leads to larger purchases, increased revenue, and fewer returns. More important, it creates greater brand loyalty: forty-four percent of customers surveyed say they are more likely to return for more business after a personalized experience. And with the holiday shopping season nearly upon us, this can be an important competitive advantage for your marketing campaigns and customer outreach.

According to Dale Carnegie, the sweetest sound in any language is the sound of a person’s own name. With help of automated name validation capabilities, you can leverage accurate name data as a key component of building effective relationships with your customers and prospects.

Contact records are one of your most valuable assets. According to Salesforce.com, 70% of your contact records will change in one way or another each year. Making sure that they are accurate and up-to date ensures you are getting the most from them and resources are not wasted attempting to contact customers and prospects through bad or outdated information.

Fortunately, the process of validating and maintaining up-to-date contact information is increasingly easier and can be automated through contact record validation APIs.

Best practices for automating data validation:

Here are four best practices to consider when automating the validation of your contact records within your company.

1. Create a culture where everyone understands and values data quality

Contact records are one of your company’s major assets, touched by multiple departments with different needs and how they use the data. Everyone has a stake in trustworthy contact records. Adapting your company culture to value the importance of genuine, accurate and up-to-date contact details means every employee has a responsibility for improving data quality.

Establishing this philosophy early is important for getting buy-in for implementing and continued support for data validation automation.

2. Establish where the need is

Understanding how and when your contact records are used will drive your data validation needs. A simple exercise is to look at how each department interacts with a contact record and how they use it.

Marketing:

Marketing has two main use cases for data validation; when the prospect is initially captured and subsequent outreach marketing campaigns.

When initially capturing the contact’s information, the type of validation will be largely dependent on the data fields being captured. For example, a whitepaper signup might only require name and email address, whereas a free trial might require name, address, phone, and email. The good news is that there are different validation services to meet each need.

When launching new campaigns, it is best to check the prospect’s contact details for changes. This not only ensures better campaign success but also helps with compliance of privacy regulations, like Telephone Consumer Protection Act (TCPA).

Sales:

For the Sales department, accurate data is key to communicating with prospects quickly and efficiently. Improved contact rates results in increased sales.

Customer Care:

According to Forbes, businesses are losing over $62 billion per year due to poor customer service. For the customer care team to provide great service and timely resolution of issues, they require up-to-date contact information.

Finance:

For the Finance department, it is straightforward: cash flow. Returned invoices and payments due to incorrect addresses require additional resources to resolve and impedes forecasting and cash flow.

3. Validate often

As discussed, 70% of your contact records change over the course of the year. Using real-time data validation APIs to keep them up-to-date, after they are initially captured, allows each department to approach a contact record with confidence. This means no matter when a department reaches out to your contacts, they know the record is accurate.

4. Introduce a data steward

Just because you’ve automated data validation doesn’t mean you don’t need to check in on the process. A data steward can be essential to this process, owning responsibility for data validation.

A data steward is someone who ensures your automated validation processes are running smoothly, tests the data quality and develops front- and back-end checks that are tracked and reported on.

Starting with these best practices helps ensure early adoption and support for integrating automated contact record validation. Continuing to monitor and measure the impacts of these efforts will demonstrate the strong ROI associated with good data quality.

A little bit of summertime fun with the Bard and data quality.

“What’s in a NAPE?
That which we call a rose
By any other name would smell as sweet.”
-William Shakespeare, Romeo and Juliet

OK, Shakespeare said ‘name’ not NAPE. But the sentiment rings true for data quality. Whatever you call it, good data quality practices will make your marketing perform sweeter. For us, NAPE is a simple acronym we use to describe the four most important elements of a contact record, and where you want to make sure your contact data is accurate:

N – Name

A – Address

P – Phone

E – Email

It is pretty clear to see why, having someone’s name wrong is not a great way to start off a relationship and their address, phone and email need to be correct to ensure your messages reach them. Now, let’s look at why each of these NAPE categories is important to you, and see how our services can support them.

How Macbeth would handle your data problems

“Fair is Foul, Foul is Fair”
-William Shakespeare, Macbeth

This quote is a good metaphor for the life cycle of contact data and its quality, because good leads age over time (Fair to Foul), but our automated services can turn bad leads into good ones again, or flag them for removal (Foul to Fair).

Here are some of the ways we do this:

Name. Not every marketing lead or order you get has a legitimate name, for reasons ranging from fat-fingered data entry, sidestepping lead collection to committing fraud. Our DOTS Name Validation product flags possible fraudulent names – including William Shakespeare! – by providing individual scores for vulgarity, celebrity, bogus, garbage and dictionary names, as well as provides an overall quality score, Name Score.

Address. Bad address data can occur as a result of factors such as data entry error, fraudulent data, or the natural decay of contact data records over time. Knowing where a contact record is from is critical for global compliance issues such as the European Union’s GDPR. Our flagship Address Validation products for US, Canadian or international addresses will correct, validate and append mailing addresses from over 240 countries, to improve accuracy and increase customer satisfaction.

Phone. Contacting wrong or changed phone numbers wastes your time, annoys prospects or customers, and can lead to huge compliance fines in the wake of laws such as the recently updated Telephone Consumer Protection Act (TCPA). Our Phone Validation products can provide contact information for over 400 million US and Canadian numbers, as well as line type, porting and geocoding information for numbers around the world.

Email. Email validation improves deliverability, decreases bounce rates, helps preserve your sender reputation, and can be important for compliance issues such as the US CAN-SPAM act. Our DOTS Email Validation takes a five stage approach to validating email addresses, weeds out invalid, undeliverable, and bogus email addresses worldwide, while correcting for common domain errors.

Finally there is cross-validation between all of these items – for example, making sure your order for Stratford-On-Avon isn’t coming from an IP address in an obscure third-world country. Tools such as DOTS Lead Validation and DOTS Order Validation will check your leads or orders against more than 130 data points to return overall quality and confidence scores.

Of course, data validation tools like these have gone from being a luxury to a necessity in recent years, for reasons that include marketing cost-efficiency and yield, competitive factors, customer reputation, and regulatory compliance. If you ignore good data hygiene nowadays then alas, poor Yorick, you face consequences ranging from stiff penalties to loss of market share.

How to avoid a Shakespearean data tragedy

In The Merchant of Venice, the Bard penned, “I am not bound to please thee with my answers.” We take a very different approach. Our friendly technical staff loves to give answers to your questions and explore customized solutions with you, with no sales pressure at all. You can even test-drive our tools online, explore all of our documentation, or get a free trial key for up to 500 transactions. Contact us anytime and let us help you sleep, perchance to dream, better about your contact data.

If you do outbound marketing via telecommunications, the Telephone Consumer Protection Act (TCPA) has probably been part of your business agenda – particularly in recent years, as stiffer interpretations of these consumer privacy laws have led to multi-million-dollar judgments against major corporations and others. So what lies ahead for businesses in the next 12 months in terms of TCPA?

The short answer is twofold: in an era of increasing consumer privacy, TCPA isn’t going away any time soon – but as efforts to ease its impact on businesses are making their way through the courts, there is hope for less risk and more leeway in meeting the requirements of TCPA. We will continue to monitor these developments closely, as a key provider of tools for TCPA compliance, but here is a summary of what we are seeing so far.

Three key issues: equipment, consent, and third parties

In a recent video interview with text messaging vendor Tatango, TCPA attorney Ernesto Mendieta highlighted three key issues that are currently the subject of court cases:

• the definition of automated telephone dialing systems (ATDS)
• revocation of consent
• the definition of co-parties.

The ATDS issue is particularly important for many businesses. TCPA prohibits unsolicited calls made via automated dialing equipment; however, a much broader definition of ATDS introduced in 2015 included equipment that could store and dial numbers without human intervention, even if these capabilities were not used. This expanded definition was struck down by an appeals court in 2018, with new FCC guidelines expected in 2019. According to law firm Eversheds Sutherland LLP, businesses are hopeful that these new guidelines will provide a much clearer standard for these devices.

Another key issue for TCPA litigation revolved around whether consumers can revoke consent for contact via ATDS if they have previously agreed to such contact under the terms of a contract. Recent legal cases have tended to rule in favor of businesses, deciding that such contracts override a consumer’s right to revoke this permission, however, case law is not unanimous and further cases are expected to shed more light on this issue in 2019.

Finally, recent court decisions such as this one involving Taco Bell point to more clear boundaries about whether businesses are liable for TCPA violations on the part of third parties promoting their products or services. Here as well, case law is expected to evolve further in 2019.

In general, many of these legal efforts spring from a backlash from businesses affected by recent stiffer interpretations of TCPA, and its fallout in terms of penalties. For example, the National Association of Federally Insured Credit Unions (NAFCU) is publicly urging the FCC to reform TCPA to “separate bad actors who are harassing consumers with unwanted and potentially harmful robocalls from good actors like credit unions contacting their members with valuable information on their existing accounts.”

A new safe harbor for changed numbers

One other major change on tap for 2019 is a new way that businesses can protect themselves against inadvertent marketing calls or texts to numbers that have changed hands. In December 2018 the FCC issued an order calling for the creation of a national database of reassigned phone numbers, for the purpose of reducing unwanted contacts to consumers with these numbers. To encourage its use by businesses, this ruling also includes a TCPA safe-harbor provision for calls to reassigned numbers when the most recent version of this database is checked first.

It is important to note that this new database will not remove the need for good contact data hygiene, particularly the verification of contact phone numbers. Contacting a bad or mistyped number can still open businesses to liability. Given the high percentage of numbers that do change each year, it is still important for the sake of data integrity to verify contact numbers both at intake and before a campaign, using tools such as Service Objects’ DOTS GeoPhone Plus 2 service. However, this new database can help mitigate what has often been a common source of liability.

Summing it all up

The essential purpose of TCPA remains unchanged: businesses still can’t spam consumers via automated telecommunications, particularly wireless devices, without their explicit permission. But there is hope for well-intentioned businesses in 2019, with prospects ranging from clearer legal requirements to better tools and safe harbor provisions for inadvertent marketing contact.

Here at Service Objects, we will continue to keep abreast of how TCPA and its enforcement continues to evolve in 2019. In the meantime, we are always happy to consult with your business to help you find cost-effective solutions for TCPA compliance – contact us anytime.

Unless you’ve been living under a rock for the past couple of years, you know that data privacy and security laws have become a big thing worldwide. Between Europe’s GDPR regulation, Canada’s PIPEDA laws and others, consumer’s rights over their own personal data became one of biggest issues of 2018 for CIOs and CDOs who do business internationally. But what about here in the United States?

Now we have some numbers behind public opinions on this issue, thanks to a recent survey from software giant SAS. The results show that many of the same concerns that led to regulations such as GDPR are top-of-mind among Americans, and should inform the way data professionals look at their contact data assets in 2019 and beyond.

What the survey says

In July 2018, SAS surveyed over 500 adult US consumers from a variety of socioeconomic levels about their opinions on data privacy. Here are some of the key conclusions from this survey:

People are concerned. Nearly three-quarters of respondents are more concerned about data privacy than they were a few years ago, with more than two-thirds also feeling their data is less secure. The biggest areas of concern? Identity theft, fraud, and personal data being used or sold without consent.

They want more regulation. 67% of respondents felt that government should do more to protect data privacy, while fully 83% would like the right to tell an organization not to share or sell their personal information. A large majority would also like the right to know how their data is being used, and to whom it is being sold.

Consumers are more savvy about privacy. Roughly two-thirds of respondents (66 percent) acknowledge that primary responsibility for their data security rests with them, and a majority are able do things like changing privacy settings. Notably, close to a third of people have reduced their social media usage and online shopping over these concerns.

Trust must be earned. Trust in organizations for keeping personal data secure vary widely, from highs of 46-47% for healthcare and banking organizations to roughly 15% for travel companies and social media.

Age matters. Older consumers value privacy more than young ones and are least willing to provide personal information in return for something (36% for Baby Boomers versus 45% for Millennials). However, this does not mean that young consumers live in a post-privacy world, with 66% of Millennials expressing concern over the security of their personal data.

What this means for data privacy – and for you

One important take-away from this study is that, whether or not we have a US version of GDPR some day – a direction favored by these survey results – the trend is clearly toward increasing consumer concerns over data privacy and security over time. This means that data professionals need to prepare for the very real possibility of increased regulation and compliance issues on the horizon.

These survey results also mean that even in the absence of regulation, your organization’s data policies can have a very real and tangible impact on brand image and consumer trust, which in turn affect your bottom line. The fact that some people are reducing their social media use and online shopping, for example, should be a warning for everyone to start paying more attention to data privacy and security concerns.

Finally, these results are another sign that more than ever, businesses need to get serious about contact data quality in 2019. Tools from Service Objects such as address, email and phone validation can help ensure that your contact data assets are accurate, and prevent unsolicited marketing contacts to mistaken or bogus entities – and in the process, give you higher quality leads and contacts.

Want to learn more? Contact us to speak with one of our knowledgeable product experts about improving your data quality in the new year.

As a data validation company, we think a lot about how information is collected and stored – and we know that the right approach to data collection can ensure that you start off on the right foot. This blog shares some expert tips for channeling your data into your company’s data stores, in ways that give you the best chance to have this data corrected, standardized, and validated.

Let’s imagine a few of the most common data entry points. At the top of the list we find web forms, compiled datasets, and manual entry from locations such as Point-of-Sale (POS), phone calls, and written transcriptions. Each type of data entry is unique from an interface perspective, but there are still two key rules you can use to limit the chance for errors or garbage. Here they are:

1. Divide and conquer

First, break down your data into its most simple components. By collecting data in its simplest form you can ensure there is no confusion between what the data is supposed to represent and other fields. This is a principle we call separation of data, where each field only contains the most relevant data for its type.

In the best case, you have a collection of very specific fields with unique data types – as opposed to the worst case, where you have a group of identical fields collecting your data. Could a user enter, say, his grandmother’s name in the ZIP code field? If so, you still have some refinement to do here.

2. Set data constraints

Next, determine what characters are relevant to each specific field. For example, if you are collecting “Age” data, you know that the data field should be a number. It doesn’t make sense to allow for anything other than the numbers 0-9 (and please don’t get cute and allow words such as “thirty-five”). Extending your requirements further, you could even limit the “Age” field to positive numbers to prevent someone from claiming they are -5 years old.

Now, let’s put these two rules to work for two of the most common types of contact data: delivery addresses and email addresses.

United States delivery addresses

This is a case where a basic understanding of the data you are collecting will take you a long way. Here we are going to examine the anatomy of a typical US address, as shown in Wikipedia, and then split the individual components into different fields.

https://en.wikipedia.org/wiki/Address_(geography)#United_States

From this US address example, we can see the recommended USPS format. Within the address, we have the house number and street name (Address1), the name of town (City), the state abbreviation (State), and the ZIP+4 (ZIP/PostalCode).

Here are some good and bad examples of address data:

Ideal input

Field	Content	Description
Address1	27 E Cota St STE 500	Contains a mix of alphanumeric data pertaining to the mailbox # and street
Address2	c/o John Smith	Non-critical deliverability information
City	Santa Barbara	Contains only alpha characters
State	CA	Standard 2 character representation of a state chosen from a list of acceptable values
ZIP	93101	5 digit number without extraneous characters

Address 2 used incorrectly

Field	Content	Description
Address1	27 E Cota St STE 500	No issues
Address2	Santa Barbara, CA 93101	City, state and ZIP are not separated

Allowing abbreviations and local language

Field	Content	Description
Address1	27 E Cota St	No issues
City	SB	Abbreviating the city name is not ideal. Spell out full name or use ZIP to determine and populate this field
State	Cali	Informal spelling instead of California or CA. State should be selected from a data set
ZIP	93101abc	Should be a 5 digits with no alpha characters

Email addresses

Now let’s turn to the format of an email address, again from Wikipedia:

https://en.wikipedia.org/wiki/Email_address

Emails are a bit trickier, but constraints can still be placed on the point of entry. The set of allowed characters in an email is far more expansive than say, postal codes, but there are still limitations. By putting the restrictions in place you can still cut out some of the garbage that can be submitted.

In this case, you could examine the individual elements of an email and place restrictions on each. Since an email must consist of a local-part, “@” symbol, and a domain, it is safe to restrict your collected data to only email inputs that conform to the anatomy of an email. For example, an address such as “Input 1: 123ABCSt.foobar@domain.com Thirty-Five” does not end with a legal domain identifier, and also contains illegal spaces within the address and after the closing period.

General contact record data collection

The same techniques can be applied to all of the data that you collect. Some fields may be easier to apply constraints to, but any attempt to filter acceptable input and organize the data into manageable sections will benefit you down the line. We specialize in data validation and have spent over 15 years refining our methods for interpreting, standardizing, and validating data. If data is gathered in component parts we can at least gain context and, even if the data isn’t correct, apply our specialized knowledge to try and validate this information.

Finally, give some thought to how your data will ultimately be stored in a data store or database. Since this is the bottom level, it is crucial for database administrators to make educated choices about these data fields. If constraints aren’t placed at the database level, the information you have collected could be rendered useless. Smart choices in data type, accepted data length, and constraints can help ensure that your data is stored in its most sensible form.

As with most things in life, an ounce of prevention is worth a pound of cure when it comes to collecting and maintaining contact data accuracy. The techniques described above, in conjunction with Service Objects web services, will help provide you with the most genuine, accurate, and up-to-date data as possible.