Case study

Increased Effectiveness: SG Analytics Enables Clients to Target High-Propensity Customers for a Higher Conversion Rate

SG Analytics DA Fintech Case Study We built a Win Back Model for our Fintech client


The client engaged us to provide the Marketing team with customers with a higher propensity to be retained after they have unsubscribed.


  • We extensively looked at various attributes linked to user app registration, user journey through the app, user tenure in the app, and user action journey via the app.​
  • We gathered an unsubscribed user base within a specific tenure and collected all the attributes related to those customers for feature engineering.​
  • Once the features were transformed, we built a classification model and assigned win-back propensity scores to the user base, assisting the Marketing team in their efforts toward win-back campaigning.


We established a bi-weekly sprint framework where we utilized Jira boards provided by the client, which allowed us to effectively manage and prioritize tasks, ensuring the timely completion of deliverables.


  • We increased effectiveness in marketing campaign targeting.​
  • We reduced costs associated with win-back campaigns by more than 70%.​
  • We increased the win-back rate by up to 23% more when compared to random.​
  • We increased customer retention post-win-back by 11% over 90 days.


  • Customers identified by the model and those re-engaged with the client showed higher loyalty scores.
  • Developing the model led to changes in the established customer lifetime journey.

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