• August 17, 2017

SessionM Enhances Audiences Module

SessionM, providers of a customer engagement platform, has enhanced its Audiences Module to help marketers better understand behavior to prevent customer churn and calculate next-best offers.

SessionM customers can now go beyond simply defining and creating customer segments using generic demographics or attribute data filters, using more sophisticated data to target precise segments, like specific items purchased and customer spend thresholds.

The update also allows marketers to calculate each customer's recency of last purchase, frequency of purchases during a specific time period, and monetary spend. In addition, leveraging granular customer data, companies can use SessionM's product recommendation engine to deliver the next-best offer based on individuals' preferences and past purchasing behaviors.

"At the core of every data-driven engagement strategy is the ability to target individual customers with precision, in real time. Knowing how often customers interact with your brand, where they encounter your brand, and how much they spend across all channels allows marketers to drive intelligent interactions based on data, not conjecture," said Mark Herrmann, co-founder and chief product officer of SessionM, in a statement. "The enhanced SessionM Audiences Module now enables brands to segment their audiences across a huge spectrum of consumer attributes, allowing for smarter engagements and driving greater customer loyalty."

The Audiences Module includes the following:

  • ElasticSearch capabilities that give marketers a scalable and faster data environment to create and analyze audiences.
  • Real-time view into segments, showing companies their audience segments as they add or subtract required criteria for each campaign.
  • Introspection into audience sizing, giving companies a clear picture of their audiences as they acquire more customers over time.
  • Granular audience creation that allows companies to define audiences based on demographic and behavioral attributes associated with end-customer profiles without needing to specify the type of audience.
  • The ability to create audiences using customer purchase recency, frequency, and spend amount attributes, along with the ability to identify customers most likely to churn.
  • Clear understanding of audience behavior, including information on audience size, date/time created and when an audience was last processed.
  • A view into audience sizing over time, with a summary of created audience attributes.

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