Global Software Company Boosts Retention Rates with AI Churn Predictions
A global multimedia and creativity software company wanted to determine retention propensity for retail consumers who had contacted their call center with intention to cancel subscription.
Customer tenure and product subscription history was analyzed using a self-learning, multi-modeling prediction technology from Findability.AI
The proprietary algorithm ingested historical data to develop multiple prediction models to account for all possible scenarios in the dataset.
Customers were ranked by categorizing into deciles based on propensity to churn.
An additional retention of 40% over the base retention rate of 15% was observed in the highest rank customer segment.
The client could formulate a proactive outreach plan for customers who were most likely to be retained and could target remedial measures at others.