How QuadSci Predicts Churn and Growth

    Proven AI, trusted by market leaders, and entirely focused on how your customers use your software.

    Read the Behavioral Signals

    QuadSci reads the signals that precede churn and expansion months before they surface in a renewal conversation: usage decay, shifts in adoption depth, changes in seat activity, and account-level engagement patterns. These aren't health scores built on manual rules. They're model outputs trained on 11 trillion telemetry events, updated continuously as customer behavior evolves.

    From Signal to Motion

    When QuadSci identifies a risk or an opportunity, revenue teams see which accounts need attention, why the signal fired, and what action is most likely to change the outcome, whether that is a CS intervention, an expansion conversation, or a product adoption play. Intelligence surfaces in the workflows your team already uses, so the signal becomes motion.

    Proven Accuracy, 12 Months Ahead

    QuadSci delivers 90% predictive accuracy for churn and growth, with signals available up to 12 months in advance of the event. That lead time is the difference between a proactive conversation and a surprise on renewal day, giving CS, sales, and RevOps teams room to act while there's still time.

    How Customers Use QuadSci

    Revenue and customer success teams use QuadSci to answer the questions that drive their week — which accounts are at risk, where growth is forming, and where to focus finite time.

    Identify churn before it hardens

    CS, RevOps and account teams see which accounts are drifting toward risk months before a renewal conversation starts, with enough lead time to intervene while the outcome is still changeable.

    Surface growth that isn't in the pipeline

    AEs and CS leaders find expansion-ready accounts based on actual adoption depth and trajectory, not activity in the CRM. On average, 15% of ARR is found unpiped.

    Prioritize the book, not just the list

    Revenue leaders get a portfolio-level view of their entire customer base, ranked by risk, ARR, and renewal timing, so team capacity goes to accounts that can actually be saved.

    Ground the forecast in behavior

    Executives, RevOps and CROs replace opinion-driven pipeline reviews with a behavioral ARR forecast that connects to Salesforce, Clari, and Gainsight.

    Connect feature adoption to revenue outcomes

    Product leaders understand which usage patterns correlate with retention and expansion, giving roadmap decisions an evidence base tied to ARR rather than request volume.

    Build campaigns around behavior, not assumptions

    Marketing teams identify which behavioral cohorts are most likely to expand, find lookalike accounts based on the usage profiles of top customers, and build lifecycle programs grounded in how customers actually move through the product.

    Machine Learning + GenAI

    Transform your product telemetry and CRM data into accurate, evidenced-based churn and retention predictions grounded in customer behavior.

    Quantitative ML

    Our AI is rooted in quantitative ML algorithms that analyze customer behavior and predict outcomes.

    Q-Chat Agent Family

    Product & customer context aware agents help Sales, CS, Services & Marketing take action.

    Direct Deployment

    Integrate and access predictive intelligence in the GTM applications your team already use and prefer.