Identify which accounts are at risk of churning — before they tell you. Get your CS team acting on signals, not surprises.
Understand if your AI agents are actually delivering value. Measure adoption, detect friction, and prove ROI on your AI investments.
By the time a customer sends the cancellation email, the decision was made weeks ago. The signals were there — they just weren’t visible.
Predict connects your CRM and product usage data. Behavioral data from Pendo flows natively — you can also bring data from other analytics tools.
Predict identifies the behavioral patterns that precede churn in your specific customer base — no manual definition needed. It learns from your historical data.
Risk scores and recommended actions are surfaced directly in Salesforce and Slack — with context on what’s driving the risk and what to do about it.
Build dynamic segments by risk level to automatically trigger communication journeys and in-app guidance for accounts that need attention.
SalesforceHubSpot
Snowflake
Mixpanel
Amplitude
PendoYour team manages accounts reactively — you only hear about problems when they surface. Predict gives your team a prioritized list of at-risk accounts every week, with the context and recommended actions to intervene before it’s too late.
Churn is unpredictable. It kills forecast accuracy and surprises the board every quarter. With Predict, your revenue team has visibility into renewal risk weeks before the conversation — and the time to actually do something about it.
Account health data lives in three systems and nobody has the full picture. Predict consolidates product usage, CRM signals, and behavioral patterns into a single risk score — surfaced directly in the tools your team already uses.
You can see how many users open it. You can’t see if it’s actually solving their problems — or frustrating them into churning.
See what users ask, when conversations break down, and what types of requests your agent can’t handle.
Automatically surface the moments where users get frustrated — repetitive prompts, failed responses, dead ends.
Connect agent usage to retention, task completion, and support tickets. Prove the ROI of your AI investment.
See who uses your agent, how often, and for what. Spot the accounts that aren’t adopting before it becomes a churn signal.
Compare how long users take to complete tasks via your AI agent vs. traditional UI. Quantify the time savings.
Find the gaps between what users want and what your agent delivers. The clearest input for your product roadmap.
You shipped an AI agent. Your roadmap for it is based on support tickets and gut instinct. Agent Analytics gives you behavioral data behind every conversation — what’s working, what’s failing, and what users actually need from your agent.
You’re iterating on your agent but can’t measure the impact of each change. Connect agent usage to real outcomes — task completion, retention, support deflection. Know if your improvements are actually improving anything.
You invested in an AI feature to improve engagement. You’re not sure it’s paying off. Prove — or disprove — whether your AI agent is improving retention. Then use the data to optimize adoption across your user base.