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.
- 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.
- 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.
- 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.
Ruth P. Stevens consults on customer acquisition and retention, and teaches marketing at companies and business schools around the world. She is past chair of the DMA Business-to-Business Council, and past president of the Direct Marketing Club of New York. Ruth was named one of the 100 Most Influential People in Business Marketing by Crain's BtoB magazine, and one of 20 Women to Watch by the Sales Lead Management Association. She is the author of Maximizing Lead Generation: The Complete Guide for B2B Marketers, and Trade Show and Event Marketing. Ruth serves as a director of Edmund Optics, Inc. She has held senior marketing positions at Time Warner, Ziff-Davis, and IBM and holds an MBA from Columbia University.