New York’s Happiest B-to-B Database Marketer

Speaking at a BMA conference in New York recently, I posed a question to the audience: “Are any of you happy with your marketing data?” To my surprise, two hands shot up.

But syncing is a fundamental challenge if you don’t have predefined data rules. For example, which system “owns” a particular field and how do the systems talk to each other to ensure quality data is moving effectively from one system to the next. This is both a process and data challenge that needs to be planned and documented. We spend much time establishing the “rules of the data road” to ensure clients’ marketing and sales automation systems are working in synchronicity data-wise.

Q: B2B data degrades so fast. How do you keep the data clean and updated?

We apply rigorous manual management to syndicated data sources. Much of the data that we curate for our clients is acquired in bulk or via APIs, so our processes focus on data exception handling, versus normalization and consolidation. For our data team, this is a daily, weekly and monthly exercise.

Additionally, since we understand the industry, its structure, and the key relationships, we use our own data hierarchy, frameworks and fields to ensure data integrity for clients’ marketing and sales systems.

Q: What advice do you give your clients on how to acquire and maintain their data? 

My suggestions to clients are two-fold. One: Build your own “ideal state” data model. Two: Add intelligence to your data to make it actionable.

Let me explain. The key for successful data management at scale is knowing your ideal data model. Your model should consider data in three buckets:

  1. Contact information, like email, address and direct phone.
  2. Relationship information, like the corporate hierarchy.
  3. Profile information, persona-related data like industry segmentation and buyer profile.

When you build your data dictionary — from source and structure all the way down to the field level — you’ll develop a clear understanding of the gaps and what your data acquisition priorities should be. Also, this ideal data model will inform the way you build your data systems, your cleansing and curation processes, and the approaches you’ll take to data append. Even if the data doesn’t exist in your warehouse today, plan for it.

Your sales team can be your best data provider. But you need to provide them an easy way to update information, and you need to give them a reason to care. One strategy that we find successful is to provide sales teams with insight and intelligence beyond mere contact information. There are the subjective traits or relationships that influence buying decisions. Examples would be the innovation score discussed above, and current competitor information. By appending these fields, we make the sellers better, smarter and faster closers. In our world, I’ve seen up to a 25 percent improvement in deal speed — the number of days from open to won — by adding these fields.

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

Author: Ruth P. Stevens

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.

Ruth is a guest blogger at Biznology, the digital marketing blog. Email Ruth at, follow her on Twitter at @RuthPStevens, or visit her website,

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