Turn your product and CRM data into powerful predictive insights to retain and grow revenue.
Warn reps, early and often
Instantly alert sales reps when a customer’s risk changes (and why) directly within Salesforce and Slack.
Explain the "why"
Each prediction comes with data-backed explanations and next steps, so you can understand what's driving churn and how to prevent it.
Automate customer success
Scale customer engagement with predictive, live segments and personalized communications journeys.
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.
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
“Thebiggestdifferentiator[...]isthatPredictgivesrepstheintelligencewheretheyalreadyworkinSalesforceandSlack.Oncethatclickedinmyhead,therewasnootheroption.”
RevOps Leader @ Cybersecurity company
AI churn predictions,
in the flow of work.
Turn product usage data into predictions and actions your team can take to stop customer churn, before it’s too late.
Watch this 2-minute demo to see Pendo Predict in action.
Your data is safe with us. Pendo meets the highest standards in data protection, with certifications and compliance across SOC II, ISO 27001, CCPA, GDPR, and enterprise-grade security measures.
See how you can tackle churn, expand revenue, and find opportunities hidden within your product usage data.
Frequently asked questions
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.
Pendo Predict is built on 4+ years of applied statistics, ML modeling, and GenAI. It acts like a combination of an AI data analyst and data scientist: it combines data from many sources (Pendo usage data, CRM, data warehouse...) and gets to work to label, clean, normalize, and optimize your data for predictive modeling, ensuring only the relevant signals are used. You define your business logic, for example what churn looks like for your organization, and Pendo Predict is able to generate a custom AI model for your organization, which will be trained on your historical data, and constantly learn from new data to improve accuracy.
Most organizations go the route of building their own predictive models in-house with their data teams. This approach requires significant amount of data science resources to build and maintain, unlike Pendo Predict which is self-serve. Pendo’s ability to coach your teams directly inside the CRM with embedded guides also enables a unique combination of analysis and action, so you can prioritize early, decisive intervention.
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 is designed for business teams. It’s self-serve, letting RevOps, CS, and Sales Ops leaders build and deploy AI models in days for churn and other use cases.
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
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.
No. Predict focuses on product usage and business context. Personally Identifiable Information (PII) is not processed.