Pendo is a product analytics and digital adoption platform pairing usage data with in-app guides and NPS surveys, free for up to 500 monthly active users.
Pendo is a product analytics and digital adoption platform for teams that build or run software, and it answers one question: what do people actually do inside the application, and what should change because of it. Usage data, in-app guidance and user feedback sit in one place, so a product decision does not depend on stitching three tools together. Pendo is made by Pendo.io, Inc., an independent company in Raleigh, North Carolina. The same platform covers software sold to customers and software a company has deployed to its own staff. Product analytics auto-captures user interactions from the moment the snippet is installed, so pages and features can be tagged afterwards and still show history. Paths, funnels and workflows trace how people move through and across web and mobile applications, and session replay runs on the same data model, so a recording sits beside the behavior that raised the question. In-app guides deliver walkthroughs triggered by user behavior, time in app or a segment, and the same delivery carries NPS and CSAT surveys, in the product or by email. AI runs through the newer parts: Leo answers questions in plain language and surfaces adoption shifts in Pendo and in Slack, Pendo MCP Server opens the data to AI chat clients and development environments, Agent Analytics covers AI agents, Pendo Predict scores churn risk and Orchestrate coordinates journeys. Pendo suits product managers, product operations, customer success and digital adoption teams who need behavior data without waiting on engineering to instrument events. It fits software companies watching adoption of a release, and equally IT groups measuring whether software the business already bought is being used. Larger deployments are served by SSO and SAML sign-in, role based access and data governance controls. Pendo is bought as bundles scoped with a Pendo representative rather than from a price list, alongside a free tier for small applications. A product team opens Pendo to check whether a new feature landed, to build the onboarding tour that follows, and to read the survey responses the tour produced. Its segments are shared across analytics, guides and AI, so an audience defined once is reused everywhere. It works alongside the CRM, the data warehouse and the support desk an organisation already runs, and its MCP server hands the same product data to whichever AI client a team works in.
Features
- Included: Funnel conversion analysis
- Not included: Retention and cohort curves
- Included: User path and journey analysis
- Included: Behavioral cohorts by event history
- Included: Autocapture of clicks and pageviews
- Not included: Tracking plan with schema enforcement
- Included: Session replay attached to product events
- Not included: Warehouse-native event import and export
- Included: Account-level group analytics
- Not included: Built-in experiments with feature flags
- Included: Alerts on product metric changes
- Included: In-app guides and surveys
- Not included: Native SDKs for web, iOS and Android
- Not included: Identity resolution across devices
- Not included: Cohort sync to marketing and ad tools
- Not included: EU data residency option
- Included: Free tier with monthly event allowance
Additional Features
- Automatic capture of user interactions on install
- Retroactive page and feature tagging
- Paths funnels and workflows reports
- Multi application portfolio analytics
- Session replay on the same data model
- In-app guides triggered by behavior time in app or segment
- Guide delivery by email
- NPS and CSAT surveys inside the application
Best for
- Product teams at software companies tracking feature adoption
- Product managers who want usage data without engineering instrumentation
- Customer success teams running in-app onboarding
- IT and digital adoption teams measuring internally deployed software
- Teams replacing separate analytics, guide and roadmap vendors
- Companies shipping AI agents that need usage and outcome data
- Small applications that fit inside a 500 monthly active user free tier
- Buyers who are comfortable negotiating a quote rather than self-serving
Use cases
- Measuring feature adoption after a release
- Onboarding new users with in-app walkthroughs
- Running NPS and CSAT surveys inside the product
- Finding where users drop out of a workflow
- Watching the session replay behind a drop off
- Announcing a new feature to one segment
- Collecting and theming product feedback at scale
- Tracking how employees use internally rolled out software
- Comparing usage across several applications in a portfolio
- Answering product usage questions in plain language
- Exposing product data to an AI assistant or IDE
- Flagging accounts whose usage points to churn risk
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