Churn deflection isn't a feature. It's an operating model. Our insights series translates billions of data points and years of operator experience into practical moves leaders can make now.
Usage consistency—not just usage levels—is the key metric for predicting customer churn and expansion. By analyzing 160 billion data points, researchers identified six distinct customer cohorts that enable teams to predict renewal and expansion outcomes with 90% accuracy up to a year in advance.
Read Full ArticleMove beyond reactive firefighting approaches to retention that arrive too late. Learn how to use predictive analytics and targeted interventions to identify and address at-risk customers 6-8 weeks before they decide to leave.
Read Full ArticleAI-powered predictive health scoring enables companies to identify at-risk customers 6-8 weeks earlier than traditional methods. Rather than relying on manual assessments and lagging indicators, use continuous data integration and machine learning to recognize behavioral patterns that precede churn.
Read Full Article58% of B2B companies have experienced declining Net Revenue Retention over the past two years, with average NRR dropping from 110.8% to 107.2%. Falling NRR reflects a misaligned commercial model rather than a customer success failure—learn the four key practices that market leaders use to reverse the trend.
Read Full ArticleA collaborative study analyzing 160 billion data points across 9,100 customer accounts reveals that usage behavior is the strongest predictor of renewals and expansions, accounting for 80% of commercial outcomes. The research identifies six behavioral patterns that can forecast renewal decisions with 90% accuracy up to a year in advance.
Read Full ArticleMove from reading to doing. Calculate your churn risk or book a diagnostic session with our team: