AI in Customer Success: Predicting Retention with Product Usage Data
How CS teams use AI to connect product usage to risk, expansion, and smarter account prioritization
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Customer Success teams are being asked to predict retention and drive expansion, but most still operate without a clear view of how customers actually use the product.
That’s the blind spot. Health scores, sentiment, and CRM activity tell part of the story. But the strongest signal of customer value lives in product usage and until recently, it’s been hard to connect that data in a meaningful way.
AI is changing that.
By combining customer signals with product behavior, CS teams can identify risk earlier, prioritize accounts with precision, and understand exactly where value is (or isn’t) being realized.
In this session, Sean Murray (Co-CEO, QuadSci) and Jared Block (Director of Customer Success, Gainsight) will break down how CS leading teams are:
- Identifying risk before it shows up in traditional metrics
- Using product data to prioritize accounts and guide engagement
- Predicting retention and expansion months ahead of renewal
- Reframing renewal conversations around price-to-value
- Aligning CS and product teams around a shared definition of customer value