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Data Myopathy: Avoid Undercutting Yourself

Form fills, sales created contacts and accounts, event lists, D&B, and Zoominfo.

Form fills, sales created contacts and accounts, event lists, D&B, and Zoominfo. There are a lot of data sources out there and much like a periscope, those sources provide a myopic glimpse of a rapidly expanding data universe (data grows 2.5 quintillion bytes a day). Why myopic? In my last article where I discussed the cost of Data Decay, I wrote about the nature of data being akin to a snapshot in time but what if that snapshot was never complete, to begin with?

Think about something as simple as a form fill. From personal email addresses to fields being populated with QWERTY gibberish, forms often become dirty needles in a data workflow. Even if the form filler tried to provide correct information, titles can often differ from those displayed on LinkedIn which creates issues with creating or appending contacts. Regardless, firmographic, technographic, and financial data points are often required that cannot be derived from 1st party sources. Enter the data providers.

Likely if you’re reading this blog you are more than familiar with D&B and Zoominfo. Both maintain their own proprietary databases and both maintain proprietary systems like the DUNS number to manage their data. D&B has been around since 1841 and its core business was rooted in standardizing and streamlining credit information. In fact, the US government required the use of a DUNS number to obtain grants and only recently began an initiative to create their own identification system

The roots of these data providers are important because they explain a lot about the core products. D&Bs roots sprang from the credit world which explains why D&Bs firmographic and hierarchical data tends to be based on registered legal entities. Since legal entities and internal organizational structures can differ significantly, it is often difficult to assign granular data points like geography to both contacts and accounts. Without complete data on an enterprise company’s hierarchies, geographies, and separate entities buying centers remain invisible. 

Not being able to see a buying center has negative side effects far beyond missing upsell and cross-sell opportunities. As many of you out there have experienced, missing or incorrect geographic data can lead to internal competition between inside sales teams where your company effectively undercuts itself. This is not to say the data providers have bad products, rather that incomplete data can create serious issues. 

Returning to the “data is a picture analogy”, data points are like pixels that dictate the resolution of your image. An enterprise company like Berkshire Hathaway can have hundreds if not thousands of subsidiaries spread throughout the world. A single account like Berkshire can be assigned to an army of sales reps and the marketers that support them. If you want to improve how you sell into big accounts choose a small sample and think about the additional data points you might need to segment and assign territories. Next find, validate, and populate those data points. If you can programmatically create segments or assign territories based on your home brewed enrichment then you’ve got a recipe for success. 

Scalability may be an issue with my suggestion so if you’d like to learn more about how Zylotech approaches the problem, please get in touch. Otherwise, see you on the next blog. 


David Slavich

Gulliver would weep if he saw David’s mileage plus status, sixty-five countries, and counting. Before finding the divine light of Martech, David worked in China, India, and Hong Kong in the finance and infrastructure verticals. When he’s not herding JSON objects, you can find this “cyberjack” chopping wood or building a deck to enjoy the view from his little bungalow by the sea in Pacifica, CA.

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