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.

B-to-B Prospecting Data Just Keeps Getting Better

The most reliable and scalable approach to finding new B-to-B customers is outbound communications, whether by mail, phone or email, to potential prospects, using rented or purchased lists. B-to-B marketers typically select targets from prospecting lists based on such traditional variables as industry, company size and job role, or title. But new research indicates that B-to-B prospecting data is much more detailed these days, and includes a plethora of variables to choose from

The most reliable and scalable approach to finding new B-to-B customers is outbound communications, whether by mail, phone or email, to potential prospects, using rented or purchased lists. B-to-B marketers typically select targets from prospecting lists based on such traditional variables as industry, company size, and job role or title. But new research (opens as a pdf) indicates that B-to-B prospecting data is much more detailed these days, and includes a plethora of variables to choose from—for refining your targeting, or for building predictive models—to pick your targets even more effectively.

My colleague Bernice Grossman and I recently conducted a new study (opens as a pdf) indicating that B-to-B marketers now have the opportunity to target prospects more efficiently than ever before. In fact, you might say that business marketers now have access to prospecting data as rich and varied as that available in consumer markets.

To get an understanding of the depth of data available to B-to-B marketers for prospecting, we invited a set of reputable vendors to open their vaults and share details about the nature and quantity of the fields they offer. Seven vendors participated, giving us a nice range of data sources, including both compiled lists and response lists.

We provided each vendor with a set of 30 variables that B-to-B marketers often use, including not only company size and industry, but also elements like the year the company was established, fiscal year end, Fortune Magazine ranking, SOHO (small office/home office) business indicator, growing/shrinking indicator, and other useful variables that can give marketers insight into the relative likelihood of a prospect’s conversion to a customer. We learned that some vendors provide all these data elements on most of the accounts on their files, while others offer only a few.

We also asked the participating vendors to tell us what other fields they make available, and this is where things got interesting. In response to our request for sample records on five well-known firms, the reported results included as many as 100 lines per firm. Furthermore, two of the vendors, Harte-Hanks and HG Data, supply details about installed technology, and their fields thus run into the thousands. The quantity was so vast that we published it in a supplementary spreadsheet, so that our research report itself would be kept to a readable size.

Some of the more intriguing fields now available to marketers include:

  • Spending levels on legal services, insurance, advertising, accounting services, utilities and office equipment (Infogroup)
  • Self-identifying keywords used on the company website (ALC)
  • Technology usage “intensity” score, by product (HG Data)
  • Out-of-business indicator, plus credit rating and parent/subsidiary linkages (Salesforce.com)
  • Company SWOT analysis (OneSource)
  • Whether the company conducts e-commerce (ALC)
  • List of company competitors (OneSource)
  • Biographies of company contacts (OneSource)
  • Employees who travel internationally (Harte-Hanks)
  • Employees who use mobile technology (Harte-Hanks)
  • Links to LinkedIn profiles of company managers (Stirista)
  • Executive race, religion, country of origin and second language (Stirista)

Imagine what marketers could do with a treasure trove of data elements like these to help identify high-potential prospects.

Matter of fact, we asked the vendors to tell us the fields that their clients find most valuable for predictive purposes. Several fresh and interesting ideas surfaced:

  • A venture capital trigger, from OneSource, indicating that a firm has received fresh funding and thus has budget to spend.
  • Tech purchase likelihood scores from Harte-Hanks, built from internal models and appended to enhance the profile of each account.
  • A “prospectability” score custom-modeled by OneSource to match target accounts with specific sales efforts.
  • PRISM-like business clusters offered by Salesforce.com (appended from D&B), which provide a simple profile for gaining customer insights and finding look-alikes.
  • “Call status code,” Infogroup’s assessment of the authenticity of the company record, based on Infogroup’s ongoing phone-based data verification program.

We conclude from this study that B-to-B prospecting data is richer and more varied than most marketers would have thought. We recommend that marketers test several vendors, to see which best suit their needs, and conduct a comparative test before you buy.

Readers who would like to see our past studies on the quality and quantity of prospecting data available in business markets can access them here. Bernice and I are always open to ideas for future studies. We welcome your feedback and suggestions.

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

Amid Gloom, eBags Has a Happy Dec. 1

From an e-commerce standpoint, it’s hardly surprising that we can “officially” use the R-word (recession) now. Cyber Monday’s sales pace was considerably slower than it was last year, according to a bevy of reports, which, of course, is unprecedented.

From an e-commerce standpoint, it’s hardly surprising that we can “officially” use the R-word (recession) now. Cyber Monday’s sales pace was considerably slower than it was last year, according to a bevy of reports, which, of course, is unprecedented.

But for at least one e-tailer — eBags.com — there’s some good news to be found. Cyber Monday 2008 sales were up 6 percent over last year for the Greenwood Village, Colo.-based online seller of bags and accessories, according to Co-founder and Senior Vice President of Marketing Peter Cobb. In addition, traffic was up 23 percent, a company record. The early evening, in particular, was highlighted by three straight record sales hours.

Cobb attributes eBags.com’s success to several Cyber Monday marketing initiatives:

  • negotiated steep discounts with many of its product vendors; as a result, had more than 1,000 products with special deals beginning on Black Friday, dubbed “Web Busters”;
  • temporarily converted its homepage into a Web Busters page showing 15 deals and contained links to 1,000 other Web Buster offers;
  • offered 20 percent off all merchandise on the site on Cyber Monday;
    if customers used PayPal, they received an additional $10 cash back;
  • allowed visitors to view 125 product videos on its site and also promoted a humorous video eBags.com produced explaining Web Busters;
  • sent 1.1 million e-mails to its opt-in members prior to Black Friday promoting the Web Busters sales, Web Busters video and other special offers; and
  • secured homepage placement on CyberMonday.com, a Web site that features special Cyber Monday deals each year; in fact, a big eBags.com promotion was the exclusive deal on CyberMonday.com from 5 p.m. to 6 p.m. MST. Eighty-five percent of the CyberMonday.com site traffic was new to eBags.com, Cobb says.

“With all the negative press about the economy and the fact that Cyber Monday is five days later this season, it pushed us to think creatively about offers that would appeal to shoppers,” Cobb notes. “We have more planned to keep the positive momentum going through the holidays.”