E-commerceEngineering

Search result accuracy

Tracking how many "no results found" errors users get.

Who is this for?

Engineering and merchandising teams improving search relevance and discovery.

What problem does it solve?

Reduce failed searches and improve product discovery to increase conversion.

AI-Powered Insights

Ask Questions, Get Answers Instantly

See how Mitzu helps you analyze this use case directly in Slack or your favorite tools.

#analytics
Scroll to see the animation
Questions You Can Answer

Key Insights & Dashboards

Ask these questions in natural language and get instant, AI-powered insights from your data warehouse.

Question

Failed search rate?

Insight

8.4% of searches return no results - costs an estimated $240K/month.

Question

Top failed terms?

Insight

'blue dress' fails but 'navy dress' works - synonym mapping needed.

Question

Impact on conversion?

Insight

Users with failed searches convert 67% less than those with results.

Business Impact

Expected ROI

Organizations using this use case typically see measurable improvements in these areas.

Reduce failed searches by 80%

Increase search conversion by 35%

Recover $2.4M annually

Data Requirements

What You'll Need

To use this analysis, ensure your warehouse contains the following data. Mitzu will automatically detect and map these fields.

  • Search query events
  • Search result counts
  • Subsequent user actions
  • Purchase conversion data
Schema Mapping
user_id→ required
timestamp→ required
event_type→ required
properties→ optional

Ready to try this use case?

Connect your warehouse and start analyzing in minutes. Our AI will help you get insights fast.