Telemetry Over Talk: How AI Predicts Churn and Unlocks Growth

It's a familiar scenario: the quarter is closing, leadership wants a clear picture of revenue, and it's time to scrutinize the pipeline. What happens next is a mix of spreadsheets, long meetings, anecdotes, and messy CRM data — all with the goal of providing clarity for leadership, investors, and advisory boards.

For years, this was the only way to piece together a picture of revenue health. But there's a canyon between a "great meeting" and the CFO's renewal forecast, between optimistic health scores and actual product usage, and between a champion's enthusiasm and their ability to articulate value to leadership.

Today, buying decisions are centralized and often removed from daily product experience. If companies want to retain and grow accounts, they need to arm their champions with usage data that clearly connects product behavior to business value.

The Data Behind the Strategy

That's the foundation of the new study from SBI, The Growth Advisory, in partnership with QuadSci. The analysis of 9,100 SaaS accounts and 160 billion telemetry data points found that 80% of commercial outcomes are predicted by product usage. Not customer stories. Not gut feel. Product usage. The strongest indicator of retention and growth isn't what your CRM says — it's how your customers behave.

Across the industry, few teams are equipped to capitalize on that data to align CSMs and account executives around the same customer reality. The result: missed forecasts and preventable churn.

Gut Check

Most forecasts are stitched together from anecdotes and lagging indicators. That makes them reactive, not predictive. By the time pipeline health looks off or renewals soften, it's already too late to course-correct. Retention has quietly become the defining metric for SaaS valuation, yet many teams still can't explain why some customers expand while others churn.

"Growth doesn't hinge on luck or loyalty. It hinges on understanding signals."

From Intuition to AI-Driven Intelligence

Declining NRR isn't a sales problem. It's a data problem. Traditional forecasting frameworks look at revenue through a static lens — past performance, renewal history, or self-reported health scores — while customer reality shifts daily.

That's where QuadSci's AI-driven revenue intelligence changes the equation. By turning product usage, engagement, and sentiment data into actionable predictions, QuadSci enables GTM teams to detect early warning signs and growth opportunities months in advance.

90% Accuracy, 12 Months in Advance

In our work with enterprise SaaS companies, QuadSci predicts churn or expansion up to 12 months in advance with 90% accuracy. We run blind tests on customer data, training our Growth AI agent on 80% of telemetry while holding back 20% for validation, ensuring consistent predictive performance over time.

The result is a clear, early view at the account level — identifying churn risk and expansion potential based on actual usage patterns across every user. GTM teams can re-engage at-risk accounts before it's too late and guide healthy customers toward the features that will create new value and expansion in the future.