Turn product usage data into predictions and actions your team can take to stop customer churn, before it’s too late.
Predict identifies at-risk and expansion-ready customers, then automatically triggers outreach and recommendations to help your team drive customer success.
Instantly alert sales reps when a customer’s risk changes (and why). Directly within Salesforce and Slack.
Each prediction comes with data-backed explanations and next steps, so you can understand what's driving churn and how to prevent it.
Predict helps you scale customer engagement with predictive, live segments and personalized communications journeys.
“Thebiggestdifferentiator[...]isthatPredictgivesrepstheintelligencewheretheyalreadyworkinSalesforceandSlack.Oncethatclickedinmyhead,therewasnootheroption.”
RevOps Leader @ Cybersecurity company
Pendo’s AI churn prediction tool scores opportunities and recommends actions, directly in your CRM. All so your team can rally around retention and act faster, within the flow of work.
Bring your own data
You don't need to be a Pendo customer to use Predict.
Predict connects with any analytics provider, so you get powerful, customized churn predictions.
Spot at-risk accounts before they give notice
Learn how to intervene and improve outcomes
Understand who is ready for expansion
See accounts ready to expand or churn
Know right when a customer's risk score changes
Get predictions directly within sales workflows
Deploy pre-built models trained on product engagement patterns
Eliminate manual model upkeep
Deploy insights directly into your business systems
See how you can tackle churn, expand revenue, and find opportunities hidden within your product usage data.
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Frequently asked questions
No, you don't need to Pendo in order to use Predict - we can use the product usage data from your existing product analytics provider.
Unlike traditional churn analysis platforms that rely on static data, Pendo Predict uses in-app behavioral insights and predictive analytics to detect churn and upsell signals—giving teams both visibility and actionability inside a single platform.
Pendo Predict applies AI models to your product usage data to forecast churn risk and upsell potential. It gives customer success and product teams clear, actionable insights so they can intervene before a customer disengages.
Yes. Core use cases include churn prediction and upsell detection, but Predict can also support other departments, for example Sales (opportunity scoring, account prioritization) and Marketing (lead qualification, PQL scoring)
No. Predict focuses on product usage and business context. Personally Identifiable Information (PII) is not processed.
The more data you have, the more accurate the predictions will be, as the models are constantly re-trained on your data, meaning accuracy improves over time. By leveraging real-time product usage data, Predict delivers highly explainable, up-to-date predictions with accuracy con
A predictive model uses AI and machine learning to forecast business outcomes — like churn or expansion. It analyzes product usage patterns and business data to surface risks and opportunities, helping teams act before it’s too late.
Churn prediction software uses machine learning and behavioral data to identify customers who are at risk of leaving. It helps teams understand churn signals—like declining engagement or feature usage—and take proactive action to retain customers.
To predict customer churn, AI models analyze usage patterns, frequency, and engagement data. Platforms like Pendo Predict integrate these models directly into your product analytics, surfacing churn risks in real time.
Yes. Predict supports 20+ out-of-the-box integrations with CRM, data warehouses and marketing automation tools. This includes leading platforms like Salesforce, Hubspot, Snowflake, and Amazon Redshift, Google Big Query.
Gain powerful product data and insights into how users move through your web and mobile applications. Track every feature interaction, session, and workflow to understand what drives retention—no manual event tagging needed.
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