Summary
AI-Recommender Model - Target the Right Audience
Challenge
Objective: To use an AI/ML recommender model effectively to churn the crème-de-la-crème from our fanbase.and to decrease CPL.
Objective
With a brand like M&M where the CRM data base is huge, it becomes very important to target the right audience. By engaging The AI/ML Recommender model we began to recognize our core fans – Customers with a higher propensity for purchase. Targeting these fans would allow us to approach such customers and prospects for hyper personalisation and targeted marketing.
Strategy
From a strategic perspective, we arrived at an optimised solution that gave us a churn of the cream fanbase. By engaging The AI/ML Recommender model we began to recognize our core fans – Customers with a higher propensity for purchase. Targeting these fans would allow us to approach such customers and prospects for hyper personalisation and targeted marketing.
Data
The model was not just a one-off, campaign-specific solution. It paved the way for the future so we could outline more specific and target campaigns – Delivering economies of scale and significantly raising effectiveness through a pragmatic, demonstrated use of AI/ML.
Solution
Results
Thanks to the model, there was a significant drop of a whopping 43% in Cost Per Lead As compared to the average industry benchmark, we were witnessing a 2.5 X higher engagement ratio Potential business of 137 crore was generated
