Customer Analytics

A deeper understanding of the customer has never been as important as it is today. Social media, open information, new business models, and ever increasing options make it paramount to understand the pulse of customers and predict their behaviors.
The core objectives of customer satisfaction, loyalty, and value remain the same, however, the means to the end are changing rapidly. Combining in-store and online behaviors along with social hearing and surveys is giving organizations a 360-degree customer view.
Analytics is helping organizations predict purchase patterns, customer behaviors, lifestyle preferences, and offering them hyper-personalized propositions. Data, technology, and predictive analytics are being used to redefine customer interactions.

Customer Journey – Key Objectives


  • Lead Scoring
  • Lookalike Modeling
  • Response Modeling


  • Customer Segmentation
  • Customer 360 View
  • Survey Analytics
  • Customer Experience


  • Pricing & Promotions
  • Personalization
  • Customer Lifetime Value
  • Up-sell/Cross-sell


  • Churn Modeling
  • Loyalty Analytics
  • Contact Center Analytics
  • Customer Service