# Ecommerce Search and Discovery Analytics

> Measuring onsite search performance requires tracking search usage, result count, refinement, product selection, cart, conversion, net sales, contribution and exits. Reviewing performance by query intent, device and inventory state reveals whether problems are caused by catalog gaps, relevance failures, filtering issues or tracking errors.

- Type: Merchant guide
- Level: Intermediate
- Reading time: About 6 minutes
- Audience: Written for store owners, builders, and designers refining high-performance ecommerce stores.
- Last updated: 2026-11-04
- Canonical page: https://academy.getzenbasket.com/merchant-questions/ecommerce-search-and-discovery-analytics/
- Part of: [Merchant Questions](https://academy.getzenbasket.com/merchant-questions/) on ZenBasket Academy

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## What you need to know

### How should onsite search performance be measured?

Measure search usage, result count, refinement, product selection, cart, conversion, net sales, contribution and exits. Review performance by query intent, device and inventory state.

### What is search conversion rate?

Search conversion rate is purchased by search users or search sessions divided by eligible search users or sessions. Label whether any purchase or only a search-related product counts.

### What is zero-result rate?

Zero-result rate is searches returning no eligible products divided by all valid searches. Exclude test and malformed requests and review high-volume terms individually.

### Which search terms generate revenue?

Connect normalized search terms to downstream purchased items and net revenue within a documented session or attribution window. Avoid claiming the query caused by purchases outside that rule.

### Which searches lead to abandonment?

Identify queries followed by no product selection, rapid exit, repeated reformulation or no purchase. Review result relevance, stock, price, spelling and filter state for the highest-volume failures.

### How do filter interactions affect conversion?

Compare shoppers who use each filter with similar eligible shoppers and inspect product discovery, exits, cart and conversion. Filter users often have stronger intent, so simple correlation overstates the filter's effect.

### How do I measure product-discovery success?

Discovery succeeds when qualified shoppers find relevant available products and progress without unnecessary effort. Combine search, navigation, selection, cart, purchase and no-result or dead-end measures.

### A quick store check

Review top searches, zero-result terms, refinements, exits and purchases and assign an owner to the most costly failure.

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## Frequently asked questions

### Is a zero-result search always a catalog problem?

No. It may reflect spelling, synonyms, filters, unavailable inventory or tracking errors.

### Should search success be measured only by conversion?

No. Product discovery, refinement, exits, revenue and customer intent provide necessary context.

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## Related learning path

- **Ecommerce Merchandising Analytics**
- **Ecommerce Customer Analytics**
- [ZenBasket Build Guide](https://help.getzenbasket.com/zenbasket-builder/)