What’s Your Marketing Data Management Type?

Marketers, what’s your type? No, not your dating type—save that for Match.com.

A B2B marketer wears many hats as our role evolves with new tools, processes, and technologies. The rise of marketing automation, for example, has forced many marketers to learn smart data management. Those who don’t do so risk harming their sender reputation, seeing low response rates, or missing revenue targets. Understanding the nuances of data management is critical to the success of lead generation programs. In fact, according to SiriusDecisions, companies that effectively manage data quality see a 66% increase in revenue.

So, where do you stand? Have you adopted the role of data management superstar? Or do you let data management fall to the back burner? Answer the questions below and record your answers to determine your data management type.

1. The typical contact database doubles every year. How do you decide when to add contacts to your data set?
   1. We grow and refresh the database based on factors such as quantity of names removed after a cleanse, how many names we’ll need based on response rates we’ve seen in the past, and coverage within our various segments.
   2. We tend to buy a new list before a big campaign, like a webinar or new product launch.
   3. When our sales numbers aren’t what we want them to be, we find some new names from a vendor to add to the database to try and make up for the missing revenue.
2. How often do you assess the deliverability of customer and prospect email addresses?
   1. We’re proactive, and ensure our email deliverability is at a consistent level at least once a quarter, removing hard bounces before we send any new email campaigns.
   2. We’re reactive, and rely on the hard-bounce reports after an email campaign to remove the contact information that we learn is incorrect.
   3. We don’t assess deliverability on an ongoing basis.
3. How would you describe the accuracy of the phone information in your database?
   1. Reliable. Once a quarter (or so) we evaluate the phone connectability with in-house resources or an outside vendor to keep phone information as up-to-date as possible.
   2. Mediocre. Sometimes sales complains they can’t reach prospects on the phone, and have to chase them down through a toll-free number or a phone tree. We eventually replace and update outdated numbers.
   3. No idea. Some contacts are missing numbers, but we have no way of knowing the accuracy of the existing numbers.
4. Which of the following describes your overall record completeness strategy?
   1. We’re on top of it. When leads come in with incomplete information such as job title or industry, we have partners and processes in place to append information quickly.
   2. We manually fill in missing fields or do spontaneous data appends to our database.
   3. It’s not a priority for us. Leads with missing fields are a fact of life, and we don’t have the resources in place to keep up and fill them in.
5. According to Janrain, 88 percent of buyers lie on a registration form.  What role does quality play in collecting form data at your organization (e.g. a white paper download form)?
   1. We use progressive profiling, or have teamed up with a vendor to automatically recognize (and remove) bogus information, and add fields such as industry and company size behind-the-scenes on our forms.
   2. We manually identify bogus information that comes in through forms every so often and stop it from entering our campaigns or sales follow-up queues.
   3. We get a lot of fake information from people who lie on registration forms, but we’ve learned to live with it because it’s too common to avoid.
6. How would you describe your relationship with sales as it relates to your data?
   1. We have an agreement and incentives in place to dictate data entry rules, such as entering a new lead with only complete information, and a method for reporting out-of-date contacts automatically through our CRM system.
   2. There’s a little disconnect. We do what we can with sales to ask them to stop entering blank fields into the CRM system, but lack a formal agreement in place and see little compliance.
   3. Sales has no say in data quality. They do complain about the quality of our lead data, often reaching incorrect numbers or wrong job titles, but they’re focused on selling.
7. Does your organization support investing in/budgeting for data management?
   1. We’ve built the business case for data management and can show direct improvements as a result of these efforts.
   2. We can find budget for data cleansing when we’re blacklisted or in serious trouble, but it’s not a line item we proactively plan for.  
   3. Not at all. It’s not seen as a priority by our management team.
8. When you do partner with a vendor to grow your database, how do you decide who to work with?
   1. We look for a reliable quality process, replacement guarantee, the ability to suppress existing contacts and only purchase net-new names, and seek highly specific targeting capabilities.
   2. We decide based on price and quantity: Who can get us the most names, for the lowest cost?
   3. We mostly don’t use one, but when we have to, we reply to the latest email from seemingly reputable data vendors.

If you chose:

[Mostly A’s] Data Management Royalty
Huzzah! The marketing community should erect a statue in your honor at the next industry trade show, with a cape and a plaque inscribed with “Data Management Royalty” underneath. Your efforts to keep a finger on the state of your constantly growing data set, implement data quality rules throughout your organization, enhance and grow your database as needed, and maintain quality are surely having a positive impact throughout your campaigns. You’re a model of data management; keep up the good work.

[Mostly B’s] Mediocre Data Manager
You’re trying! Your data management strategy is not DOA, but you may want to kick things up a notch to optimize the success of your campaigns. Maybe you’re more focused on stellar content and design than the data driving them. Once-in-a-while data cleansing or a list-buy before a big campaign is the right strategy if your goal is mediocre results. It’s time to get serious about data quality, before your organization suffers the consequences of a dirty, incomplete database. If you need to do more with less, start doing more about your data, and the rest will come.

[Mostly C’s] Data Debbie Downer
Ouch. It looks like your data management strategy is, well, non-existent. You might want to reevaluate your efforts before hard bounces lead to a poor sender reputation, your sales team stages a coup, or your campaigns are missing revenue targets. Don’t get discouraged: More than half of the companies in the U.S. are working with totally unreliable data, according to a study NetProspex conducted earlier this year. The best place to start is to learn where you stand. Assess the current state of your database in terms of quality, completeness, and coverage, and make an informed decision from there. Another suggestion is to make data quality a KPI for your marketing organization. Doing so could help rescue not only your database, but your career.

Lauren Brubaker is demand generation manager for NetProspex