How To: Getting Started with Net-New Profiles

Infer’s Net-New Profile Builder helps companies expand beyond their existing pool of prospects by analyzing these outside data signals to identify new leads and accounts that are not currently in their database. To get started with Infer's Net-New Profile Builder, email help@infer.com or for existing customers, your Account Manager.

Use Cases:

  • Account-Based Marketing (ABM) – Infer helps companies expand their total addressable market by filling the top of the funnel with new contacts and accounts that look like their best customers. For example, the marketing team could feed a profile for a new market or region directly from the Infer Net-New Builder into a Salesforce outreach campaign, while simultaneously launching a marketing campaign to the same account list via an ABM platform like Terminus in order to provide air cover for sales reps.
  • Lead Generation Optimization – By pulling all lead data into Infer Profile Management, marketers can score and de-duplicate records in order to compare quality across multiple vendors. As a result, they can easily optimize their list buys and content syndication strategies.
  • Sales SLA Governance – Companies can use Infer Profiles to initiate Salesforce tasks for reps on specific prospect lists. By doing so, they ensure that sales reps focus their follow up on accounts where they have the best chance at winning, and increase adherence with service level agreements.
  • Lead Effort Analytics – Infer’s closed-loop reporting allows sales and marketing leaders to monitor which accounts might be underserved, and where more work is needed to pursue top prospects. The platform pulls in lead activity data from Salesforce to track sales engagement with new account profiles – providing transparency into the success of those efforts.Infer-ABM-framework-graphic

Infer Profile Management can also leverage Infer’s statistically accurate fit and behavior models for greater predictive power and a deeper level of segmentation. Infer has built thousands of predictive models that analyze key signals – such as a company’s business model, technology vendors, relevant job postings, public filings, social presence, website activities, marketing automation data, product usage data, and other attributes – to produce around 1.5 billion account, contact and lead scores each year.

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