7 Steps To Smart B2B Marketing Data

  • Written by John M. Coe,
  • Published in Demanding Views

John Coe headshotWe all have heard the buzz about data-driven marketing, data analytics and Big Data. For about 95% of B2B companies, none of these strategies are working because their data isn’t smart.

So now you’re asking, what’s smart data?  Simply it’s the combination of the most logical and available data that when integrated generates insights leading to actual result. Sound too basic?  Not really and here’s why. Most B2B data has been gathered from a variety of sources based on an even wider variety of sales and marketing sources. Common examples are, purchased lists, responses from marketing campaigns, qualified lead lists, visitors to trade show booths, webinar registrations, sales staff CRM inputs, inbound inquiries, survey results, customer service calls and of course the transactional sales records held in accounting. I’ll leave out unstructured social data, even though it exists.

With all these activities, there was no data strategy in play when the data was gathered. Data just came in based on the needs of each tactical activity. This data now resides in the capture system/software attached to the tactical activity, and sits there and decays over time.

This isn’t news. We also know that an integrated marketing and sales database in the hands of a data scientist (a new job description) would yield actionable insight, campaigns and results. So why haven’t B2B companies aggressively attacked the data problem to get smart?

Here are six reasons why their data remains “stupid.”

  1. It’s unexciting. Eyes glaze over when data is discussed plus nobody wants the data job.
  2. It’s unknown. No one on staff really knows or is educated about B2B data.
  3. It’s scary. People quickly divert all eye contact when RFM or CHAID are mentioned.
  4. It’s difficult to work with. You’ll even hear this from the IT department.
  5. It’s hard to justify the budget. Future results are hard to predict.
  6. But the most common reason is that there is no data strategy. It’s all about tactics, and not a longer term vision of what an actionable marketing and sales database would offer to both marketing and sales.

7 Steps To A B2B Data Strategy

When working with firms who have many prospects and customers, multi-channel marketing activities and data silos, we have found this seven step process effective in developing a data strategy and plan that gets both approved and funded.

Find a data captain. Gather a multi-functional team and elect a “data captain.” Someone has to have the responsibility and accountability or else the database assignment will be passed around like a hot potato and dropped. Hopefully, someone exists internally who knows the company’s business and market place.

Segment and sub-segment the market. There are many ways to segment and sub-segment the market, and this is a subject all by itself. The goal is to arrive at a clear view of the most important market sub-segments, and then define each using data descriptors. This process not only establishes what data is required for the database, but begins to make it “smart.” 

Determine data needs vs. wants. One of the biggest mistakes in a smart database development is accepting too many data requests from each department. This will result in a list of data elements that will drown the project. Prioritize what data is really needed to execute vs. what everybody wants. In other words, be a tough cop at the database door.

Identify data sources. Some data will only be available from internal sources, and some will be needed from outside vendors. Carefully research the most accurate and reliable outside data vendors and establish a relationship and costs with them. Be sure to also audit their data for accuracy and completeness as all data will have holes in it.

Agree on data quality and accuracy standards. Not only is some data inaccurate at the start, but it also decays at varying rates. This is particularly true for contact level data which decays at a 60% to 70% rate each year. For each data element, agree on an acceptable level of accuracy and value. Then establish the updating and cleaning processes in accordance with this value and accuracy standard. Communicate this standard internally to manage expectations, as many users unrealistically expect 100% accuracy, particularly sales.

Decide on internal vs. external database development. When first developing a smart database, only a few IT departments can handle the job. They usually say they can, but most often cannot. One good approach is to select a qualified B2B database service provider to develop the database with the understanding that eventually it will be transferred in-house. Then you have the option to do this or not. Also select a firm that is willing and capable to train the internal staff as well.

Find quick, easy and important wins. Don’t go for a budget approval without first identifying projects and/or results that are quick, easy and are important. Nothing sinks a smart marketing database project and funding faster than not being able to demonstrate value and results quickly.

Suffice to say, developing an actionable Smart marketing and sales database first requires a solid strategy. It’s not easy to get smart with your data.

John is Co-Founder and Partner of, a data service and consulting firm devoted to data-driven marketing and sales. His background includes experience in both sales and marketing. On the sales side, John was a field salesman, national sales manager and executive in charge of both sales and marketing for three major B2B firms. He can be reached at This email address is being protected from spambots. You need JavaScript enabled to view it. or by phone at 602-402-6588.