eMetrics Marketing Optimization Summit, WASHINGTON, D.C., October 19, 2009 -- Quantivo, the leader in on-demand Behavioral Analytics, today announced Quantivo Enrich, an advanced data enrichment and integration solution that quickly creates a comprehensive view of customer  behaviors by connecting multi-channel actions, and by closing gaps in and adding important business metrics to the original data. This optional add-on to Quantivo allows marketers, web analysts and business analysts to more-effectively segment and target customers based on a complete and expanded view of their behaviors.
"Customers live in a fast-paced, multi-channel world and interact with companies in many different ways," said Brian Kelly, CEO of Quantivo. "Each customer interaction provides valuable insights, but only by combining these behaviors with enriched business data can marketers and business analysts make decisions based on complete views of customer interactions. Quantivo Enrich makes it fast, simple and inexpensive to 'fill in the blanks' and connect large-scale datasets to enable lightning-fast analysis of even the most complex customer behaviors."
Quantivo Enrich is an elastic, cloud-based solution that can process billions of customer interactions and data points. Its data integration platform combines one-to-one, one-to-many and many-to-many relationships, allowing for vertical or time-based connections as well as horizontal or look-up data connections. It can also compute and add complex customer behavior information, statistical calculations and instantly match recent and historical customer information.
Quantivo Enrich connects customer behaviors that occur vertically over time, during separate transactions or across multiple interactions, such as purchases or web sessions. These connections create detailed customer profiles that contain:
• Individual Customer Information – Customer behavior information by individual customers over a definable time period, for example, web content viewed in the past week, rather than behavior of an aggregated set of customers.
• Customer Session Information – On- and off-line session information within and across definable time periods, for example, market basket analysis within a single purchase or across several purchases.
• Backfill Information – Data that is captured after a specific action, but was initially missing, can be appended back to the earlier activities to ensure data completeness. For example, online customer activity before logging in can be tied to a customer profile, or cookie-deletion rates can be more-precisely calculated.
• Pre- and Post-Activity Information – On- and off-line data can be added at any time to provide a complete view of a particular customer behavior, such as web content viewed after a customer support call. (continued...)
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