Case Study: Pushpay achieves better natural language search and clearer user intent insights with Pendo Agent Analytics

How Pushpay unlocked real user intent and improved natural language search with Pendo Agent Analytics

Pushpay partnered with Pendo and used Pendo Agent Analytics to better understand how users were interacting with its natural language search agent. The team’s challenge was that prompt data was fragmented and their early assumptions about user needs were wrong, leaving them unsure how to prioritize roadmap improvements or guide users effectively.

Using Pendo Agent Analytics, Pushpay analyzed prompt-level metrics, rage prompts, replay data, and user feedback to uncover real intent, refine prompts, improve result transparency, and redesign filter labeling and search guidance. With Pendo, Pushpay turned its agent from a risky pilot into a trusted product pattern, using daily insights to continuously improve the experience and better align results with user expectations.

Pushpay

Paul Frank

Staff Product Manager