
Overview
What we did
- Built a user model, leveraging Facebook ‘likes’ and client IDs as distinct features that would reveal customer preferences
- Provided insight into the optimal spend per channel for each user, which translated into actionable outcomes for the end client
Key Outcomes
Pythian’s data science team was able to identify several predictive customer data factors. A refinement of the models found an optimal dollar-to-point conversion, an optimal activity-to-point conversion, as well as other ways to optimize their loyalty programs.

Optimized loyalty programs with improved customer data segments and streamlined reports
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