As Customer Success functions take on more revenue responsibility, the ability to predict churn, forecast retention, and guide renewal outcomes is critical to hitting your GRR and NRR goals. Yet most CS forecasts are still built on gut feel (which isn’t scalable long-term), anecdotal signals, and scattered spreadsheets.
Despite having access to mountains of customer data, many teams struggle to translate it into a reliable, forward-looking forecast. That’s because the data is often fragmented, unweighted, or focused on lagging indicators. Without a unified, data-driven model, it’s hard to confidently answer key questions like:
Who’s actually at risk and why?
Where will we land this quarter?
What revenue is in danger if we don’t act now?
Below outlines how to shift to a data-driven forecasting model, one that uses health scores, retention probabilities, and account-level insights to deliver long-range predictability, precision, and control to increase your GRR/NRR.
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