Dun & Bradstreet, which has had a series of major product announcements over the past few weeks (the Avention acquisition, rebranding of its OneSource platform as D&B Hoovers, a Beneficial Ownership product), has quietly added powerful new functionality to their Workbench Data Optimizer platform. The new Profile capability features an automated profile builder, Total Addressable Market (TAM) analysis, and look-a-like prospecting based upon the Workbench profiles.
The new functionality helps marketers evaluate the size of targetable sub-markets, identify audiences with a high propensity to purchase, discover overlooked whitespace opportunities, and target new accounts and contacts. According to Alex Schwarm, Sr. Director of Marketing Analytics Products, “Profile enables our Workbench customers to begin to use data-driven, ABM-oriented Profiles based on their successful sales. These automated analytics allow you to quickly and easily identify the best whitespace opportunities and characteristics of your target audiences including those with the highest propensity to buy – no data scientist needed.”
Profile is a black-box analytics engine which clusters customer files without biases. Marketers upload a file of their customers’ data for a specific product or product family. Workbench standardizes, de-duplicates, and verifies the input file; matches and enriches it with Dun & Bradstreet’s WorldBase firmographics; and then provides segmentation and file health analysis. The Profile module identifies between two and eight distinct segments containing similar companies across multiple dimensions. The user can define the number of profiles or the system can automatically identify the optimal number of profiles based on the variation of the customer file. The marketer is not required to define the key segmentation variables. Instead, the system automatically performs affinity clustering (my term) to build the segments. Execution time is typically 5 to 10 minutes.
The results are displayed on a downloadable dashboard that provides a side-by-side firmographic analysis of the clusters. Results include company size, ownership (e.g. parent, branch), primary industries, cluster size, and average deal size (if revenue figures are also shared with Dun & Bradstreet). Thus, the system may identify segments with a lower average deal size but a larger number of prospects alongside clusters containing top customers with high average deal size but a small number of targetable opportunities.
While Dun & Bradstreet does not use the term “Ideal Customer Profile” (ICP) the system is basically identifying the attributes of a customer’s ICP, determining the average deal size, and sizing the overall market opportunity.
Dun & Bradstreet has two major assets in performing TAM analysis: The WorldBase file of global companies and trust built up over 170 years of credit research. WorldBase provides them with a consistent, global file of 260 million active and inactive companies for credit and supplier risk research, sales intelligence, and B2B marketing. The file includes broad global company linkages, corporate and location sizing, industry coding, Tradestyles, and D-U-N-S Numbers (the de facto global company numbering system). This intelligence provides the core reference file against which market sizing can be performed. But TAM analysis requires customer level revenue information against which company counts can be converted to market sizes. And here is where a strong credit analysis brand helps build confidence amongst marketers to share company revenue data. While they will be reluctant to share revenue details with most vendors, firms have been sharing private financial details with Dun & Bradstreet over the better part of two centuries.
Marketers can then take any of the profiles and immediately identify net-new similar companies as well as net-new contacts. The system also sizes potential target market audiences that can be reached programmatically through their Audience Solutions group.
While prospect scoring based upon these definitions is not yet supported, that is a likely future offering for the platform. Profile, along with a set of predictive scores and paired with D&B Hoovers’ business signals, represents a toe in the water of the predictive analytics space.
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