Optimize Your Product Search with Real User Insights

Search is often the first interaction users have with your product catalog—and when it doesn't work well, you lose sales, engagement, and trust. This Product Search Feedback Form helps SaaS and eCommerce teams capture detailed, actionable feedback on search relevance, filter usability, and ranking accuracy directly from the people using it every day.

Whether you're a product manager refining search algorithms, a UX designer improving filter UX, or a developer troubleshooting relevance issues, this template gives you structured feedback that goes beyond "search isn't working." You'll understand what users searched for, what they expected to find, and where the experience broke down—so you can prioritize fixes that actually move the needle.

What This Template Captures

• Search query and intent: What users typed and what they were hoping to find
• Result relevance scoring: How well the top results matched their needs
• Filter and sort feedback: Which filters were helpful, missing, or confusing
• Ranking accuracy: Whether the most relevant results appeared first
• Feature requests and bugs: Open-ended insights on what's broken or missing

Why Paperform for Product Feedback?

Paperform makes it easy to embed this form directly into your app, send it via email after a search session, or trigger it conditionally using Stepper workflows when users exhibit low engagement with search results. With conditional logic, you can ask follow-up questions only when users report poor relevance or missing filters, keeping the form short for satisfied users while diving deeper with frustrated ones.

Once responses come in, use AI Insights to summarize recurring themes—like "users can't filter by price range" or "brand search returns irrelevant results"—and export data to tools like Notion, Airtable, or your product management platform via native integrations or Stepper automations.

Trusted by 500K+ teams worldwide and SOC 2 Type II compliant, Paperform gives product and engineering teams a fast, flexible way to close the feedback loop and ship search improvements users actually want.