Infer makes its living by generating predictive scores about which individuals and accounts are likely to become or stay customers.
This week, the Mountain View, California-based company enlarged its capabilities with what it described as the industry’s first behavior-only predictive scoring for accounts.
To unpack what that means, first consider that Infer has focused previously on two basic models for its predictive scoring: Account Fit and Behavior.
The Account Fit model scores whether a business is a “good fit” as a customer, based on relatively stable data points like the technology vendors it uses, its job postings and public filings, its business model, its tech tools, and other such factors.
The Behavior model had been used by Infer primarily for leads (i.e., people), based on such time-based activities as pages visited on a client’s web site, downloading of a white paper on a specific product, responses to an email marketing campaign, and other actions.
But matching the two has been problematic, Senior Director of Product Marketing Sean Zinsmeister told me.
This is because the marketing automation platforms with which Infer is integrated and through which its behavioral web data is obtained — Marketo, Salesforce’s Pardot, and Oracle’s Eloqua — do not allow for an easy matching of leads’ behavior with customer-fit accounts in Salesforce’s customer relationship management system, the popular CRM that Infer emphasizes.
So, Infer developed a behavioral model for accounts with data about what identified leads at those companies do, by building its own system to match leads’ behavior (obtained via marketing automation platforms) with the businesses where those leads work.
The result is the first predictive scoring based entirely on account behavior, Zinmeister said, adding that other predictive scorers blend “fit” data with behavior to get their account-based ranking.
Infer isn’t blending the two for account scoring, but instead matches the two scores in a matrix (see below) and the highest combo is the company you want to pursue. That is, it matches the account’s Behavior Score that shows if it is “acting like a buyer of your product,” with the previous Fit Score that shows it “looks like a buyer”:
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Author: Barry Levine