How can we utilize customer data from many sources to drive behavior?

Tracking customer behavior, purchases, support interactions, billing,and other attributes across multiple siloed systems is challenging. Further, the enormous data sets generated by aggregating this information are extremely powerful but difficult to utilize. Our users (retailers) need a way to gather customer data from several sources and offer personalized experiences based on that data.


Sales Data Correlation

  • Correlate sales data to customer types and product categories.

Customer Activity Overview

  • Quickly see customer buying activities over time.
  • Identify elite, key customers.

Behavior Trends Analysis

  • Identify user behavior trends and purchasing patterns.
  • Provide real-time personalized product recommendations.


1. Look at the data source.

Basic customer profile data, providing a baseline of information, including name, address and contact details

Sales transaction data, graph of customers, orders, and products by time

Support history data

Social media posts and comments that create a complete picture of customer preferences and sentiments

2. Slice data to gain insights.

Dominant Dimensions



Primary Entities

Buying activities

Support service

Social media occurrence