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Solution Accelerator

Propensity Scoring

Pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook

Propensity Scoring
Deliver personalized customer experiences

Deliver personalized customer experiences

Consumers increasingly expect to be engaged in a personalized manner, but most retailers struggle to deliver. One of the first steps in the personalization journey is often the examination of sales data for insights into individual customer preferences. With this process, called propensity scoring, companies can estimate customers' potential receptiveness to an offer or to content related to a subset of products. Using these scores, marketers can determine which of the many messages at their disposal should be presented to a specific customer.

Get started with our Solution Accelerator for Propensity Scoring to build effective propensity scoring pipelines that:

  • Enable the persistence, discovery and sharing of features across various model training exercises
  • Re-evaluate customer preferences based on the latest information available 
  • Orchestrate overlapping processes and complex model deployments to deliver timely results

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Estimate Propensity with Real-Time Clickstream Data

In ecommerce platforms, the path to a purchase is not always as straightforward as we might expect. A customer may click on a product, put it in their cart, and immediately make a purchase, but more typically, especially with more expensive or complex items, the customer will browse, compare, leave the site for a while, return to give the product more consideration, and do all this multiple times before completing the purchase. Quite often, customers will engage in this process and never complete the pruchase, instead, abandoning the cart altogether, having either made a purchase through another channel or becoming disinterested in the product.

Get started with our Solution Accelerator for Real-Time Clickstream Propensity to better predict whether users will complete the purchase of a product with which they are interacting by

  • Enabling the operationalization of real-time insights
  • Leveraging live event data generated by an ecommerce website to predict whether users will complete the purchase of a product with which they are interacting

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