6 More Thorny Data Problems That Vex B-to-B Marketers, and How to Solve Them

B-to-B data continues to challenge marketers, who need to identify and communicate with customers and prospects, but who run into thorny issues every day. Problems range from duplicates, to key-entry errors, to missing data elements, and beyond. Recently, Bernice Grossman and I worked with a group of savvy B-to-B marketers at a DMA conference to compile a list of difficult data problems. Here are six that will bring tears to your eyes—but don’t worry, we also offer some solutions.

B-to-B data continues to challenge marketers, who need to identify and communicate with customers and prospects, but who run into thorny issues every day. Problems range from duplicates, to key-entry errors, to missing data elements, and beyond. Recently, Bernice Grossman and I worked with a group of savvy B-to-B marketers at a DMA conference to compile a list of difficult data problems. Here are six that will bring tears to your eyes—but don’t worry, we also offer some solutions.

  1. How do I find out the names of individuals who visit my website?
    There are two ways to de-anonymize the website visit. First, add a registration invitation to your site. This could be an email sign-up, or a piece of gated content, like a white paper or research report, in exchange for providing important data elements like name, title, company name, address, phone and email.
    Second, use the IP address to identify the company from which the visitor arrived. This can be done by hand, using Google Analytics, or more easily by using any number of services that enable IP address look-up. Marketing automation systems are increasingly baking this option into their tools.

    But the IP address method will still not get you the name of the visitor. You can infer the visitor’s interests and, possibly, role by looking at the time spent on various pages. And you can drop a cookie and retarget the visitor with text or banner ads later.

  2. Job titles are increasingly inconsistent-and proliferating. Categories like marketing manager and financial analyst don’t seem to work anymore.
    Several companies offer job title standardization services, called something like title mapping, title translation or title beautification. A resource like that is a good first step.

    Then, consider sending an outbound email, perhaps with a follow-up phone call, positioned as a “contact verification” message. Invite the target to indicate his or her functional job title, from a list.

    After that, you will be left with a relatively smaller list of remaining titles. At that point, you need to decide on a default for the rest of them. For example, anything that sounds like IT will go in an IT functional bucket. And, depending on how often you query your customers, you can always gather answers to this question over time.

    Then, you are faced with the remaining issue, which is far more difficult, namely the crazy new titles that some people are using these days. We’ve seen bizarre titles like Chief Instigating Officer and Marketing Diva. With these, you have two options.

    • Force aberrant titles into your standards, by hand, using your best guess. Use a default code for anything you can’t really figure out.
    • Leave them as they are, and link them to a table of standardized job functions. But maintain the self-reported wacky title, too, so you can still address the person the way he or she wants to be addressed.

    You might also consider using forced drop-down menus for job function and job title, at the point of key entry.

  3. How should I handle job changes? When an employee leaves and goes to another company, does his or her history with my company go along?
    We are going to assume—a big assumption—that you actually know the person has gone to a new company. It’s more likely that you will not know. This is why it’s a good idea to do periodic de-duplications by functional title to get a sense of new names that have popped up at the companies in your database.

    When you know that there is a job change and you have the new information, you must move the contact to the new company in your database. It’s a good idea to send along behavioral data like communications preferences. You might also add a LinkedIn profile URL to the record. If you believe the prior behavioral data is important, then take it as a duplicate, and put it in a separate field, not attributing it to the new company record.

    The purchase history belongs with the original company, and should stay there. Indicate in the company record that the individual has left.
    As a general rule, in marketing databases, never overwrite. Keep everything data stamped.

  4. We want our sales people to be selling, and keep administrative tasks to a minimum. But these people are also the closest resources to our customers. How can we motivate them to capture important data about the customers and prospects they are interacting with?
    Boil down the mission to just one or two key data points that reps are asked to collect and report. Job title, buying role and email address are among the most likely to change, and perhaps the most important to keep current. Train and reward the reps on consistent reporting on the selected elements.
  5. In an effort to improve web-form response rates, we are asking for only name and email address. What’s the best way to create a company record in this situation?
    We recommend that you consider hiring a service that will fill in the company record on the spot, as a start. Or send the file out to a third party compiler to append the records you need.

    Another way is to parse the email address. Take the letters after the @ and before the .com. For example, if the email is formatted as firstname.lastname@hp.com, the meaningful letters are hp. Search for other emails with these letters in this position in your file, and build a business rule that every email with these letters shall be assigned that company name. If you have a standard record on your file, import it.

    If the email address is a generic one, like gmail.com or yahoo.com, it’s more difficult. Email the prospect and ask for more data. You could also consider preventing email addresses other than those from company domains from being accepted on the web form. But keep in mind that there is some evidence that individuals filling out web forms with personal email addresses tend to be more responsive over time.

  6. We need to get our international customer data under control. Where should we start?
    First, add country name as a required field in your web forms and other response vehicles, so that future data collection will be set. Use a dropdown menu to improve capture of a standardized country name. Prevent the record from moving forward until the country is specified.

    Then, look at what parts of the world you do business in. Estimate how many countries, and how many customer records in each country, so you can see how big an issue this is.

    Then, figure out which records in the database are non-U.S. This will take some effort. Many databases don’t have a non-domestic indicator. There is no easy way around it.

    Country names are increasingly important as laws change. Consider Canada’s onerous new email law, which requires proven opt in before emailing. You can’t assume that those email addresses ending with .ca are the only Canadian emails on your file. One suggestion is to update your web forms with a message like “If you are in Canada, opt in here.”

You can find more thorny data issues and solutions in our new white paper, available for free download. Please submit any other issues you may be facing, using the comments section here, and we’ll be happy to suggest some solutions.

6 Thorny Data Problems That Vex B-to-B Marketers, and How to Solve Them

B-to-B marketers are plagued by data problems. Business data is complex and fast-changing. Customers interact with us through a variety of channels, and often provide us with conflicting information. Our legacy databases are not as robust as we need. New tools and technologies emerge and must be evaluated. It’s a never-ending battle. To shed some light on B-to-B data problems, Bernice Grossman and I compiled a working list of problems and solutions. Here are some of the thorniest.

B-to-B marketers are plagued by data problems. Business data is complex and fast-changing. Customers interact with us through a variety of channels, and often provide us with conflicting information. Our legacy databases are not as robust as we need. New tools and technologies emerge and must be evaluated. It’s a never-ending battle. To shed some light on B-to-B data problems, Bernice Grossman and I compiled a working list of problems and solutions. Here are some of the thorniest.

  1. Data entered by our sales people ends up as mush. They don’t follow the rules; or there are no rules. That may be okay for the rep, but it’s not okay for the company.
    Here’s the best practice: Create a centralized data input group. Train and motivate them well. Give them objective rules to follow. Develop a simple method for testing the accuracy from this group as an ongoing practice. If this group cannot follow the rules, then the rules should be re-evaluated.

    Then, develop a very simple process by which reps pass their data to this group. Dedicate particular group members to certain reps, so the input person builds experience about rep’s behavior and communication style. The bonus: these two parties will team, build a valuable relationship, work together well, and improve data quality.

    Consider enabling the data input group with a real-time interface with a database services provider to prompt the standard company name and address. This can be an expensive, but very helpful, tool.


  2. How do I match and de-duplicate customer records effectively?
    Some approaches to consider:
    • Establish—and enforce—data governing rules to improve data entry, which will keep your matching problems under some semblance of control.
    • Find a solid software vendor with a tool specifically designed to parse, cleanse and otherwise do the matching for you. Test a few vendors to find the one that works best with your data.
    • Create a custom matching algorithm. As a place to start, ask several match/merge companies to show you examples of the results of their algorithm against your data.
  3. When data elements conflict in my house file, how do I decide which is the “truth”?
    The short answer is: by date. The most recent data is the one you should default to.

    But also keep in mind when importing data to enhance your records that appended data will always have its limitations, and is best viewed as directional, versus real “truth.” Be careful not to build targeting or segmentation processes that are primarily dependent on appended data.

    You could consider conducting an audit to validate the quality of your various append sources. (This is usually done by telephone, and it’s not cheap.) Then you can add a score to each appended element, based on its source, to manage the risk of relying on any particular element.

  4. Which corporate address should I put in my database? There’s the legal address and the financial (banking) address, which may be different. Or there may be a street address and a P.O. box address. Equifax and D&B often supply the financial address. The address to receive proxies is different from the address to receive advertising mail. How should I sort all this out?
    As a marketer, your concern is delivery. You care about a bill to and a ship to. Focus on the address where mail and packages are delivered.
  5. Measuring the impact of each touch in our omnichannel world is driving us nuts. Any ideas?
    The attribution problem has heated up recently, fueled by the rise of digital marketing. But it’s really nothing new. The traditional attribution methods of assigning the credit have long been either the first touch (the inquiry source medium) or the last touch (the channel through which the lead was either qualified or converted to a sale). Marketers are in general agreement today as to the deficiencies of either of these traditional methods.

    Digital marketers are experimenting with various approaches to the attribution problem, like weighting touches based on stage or role in the buying process, or by the type of touch—attending a two-hour seminar being weighted more heavily than a content download.

  6. How should I handle unstructured data, like social media content. All this “big data” stuff is getting bigger, and meaner, every day.
    User-generated social media content may offer valuable insights into customer needs and issues. But marketers first must think through how they will use the information to drive business results. First you must develop a use case. Then, you must develop a way to attribute the information to a record. For example, one method to allow the match is collecting multiple cookies to find an email address or other identifier. There may be situations where you want to track sentiment without attributing it to a particular customer but to a group, like large companies versus small. In either case, we suggest that you test the value of the data before you put a lot of time and money into capturing it in your marketing database.

You can find more thorny data issues and solutions in our new whitepaper, available for free download. Please submit your issues in the comments section here, and we’ll be happy to suggest some solutions.

A version of this post appeared in Biznology, the digital marketing blog.