Ecommerce

Ecommerce Site Search: Plan Results for Specific Product Questions

Onsite search should help a shopper move from a phrase to a relevant product or a useful next step. Plan the experience around catalogue execution detail, query differences, filters and recovery when no results are found.

5 min readBy 760 StudiosPublished Updated
Hand-drawn editorial illustration supporting Ecommerce Site Search: Plan Results for Specific Product Questions, using the 760 Studios ink, warm paper and bright accent colour style.

Identify what shoppers are trying to find

Search queries may contain a product name, model number, use case, material, problem or a misspelling. In a June 2026 Shopify Community post, a store owner said several products with JM-XL stock codes used to appear for the partial query ‘jm-xl’, but now appeared only when the exact code was entered. A separate 2022 Shopify Community post described a product-title query returning a no-results message. These are two self-reported store cases, not supporting detail of typical frequency or current Shopify defaults; use them as prompts to test the searches your own customers use. Where analytics is available, group repeated patterns instead of treating one search as a trend.

Map common terms to product fields and synonyms. A customer may use a phrase that differs from the supplier's catalogue label. Keep the mapping controlled so search improvements do not silently create false matches.

Make product data searchable before tuning ranking

Check that the product title, identifier, description, category, attributes and variant labels are complete enough for the search engine to retrieve a relevant result. Fix inconsistent spelling, duplicated manufacturer copy and missing compatibility data at the source.

Decide how the store should handle exact model numbers, partial terms, plurals and common misspellings. Test one query for each behaviour and record the expected result. Search tuning cannot compensate for product data that is absent or contradictory.

Design useful results and a no-result recovery

A result card should show enough detail to distinguish products: plain name, useful image, price where available, key attribute and stock state where reliable. Filters should reflect the available catalogue data and make selections easy to remove.

When no result matches, explain that clearly and offer recovery: check spelling, remove a filter, browse a relevant category or contact support. Avoid displaying a generic error that gives the shopper nowhere to go.

  • plain query field and submitted phrase
  • Relevant result count and sort controls
  • Meaningful filters and active selections
  • Useful no-result suggestions
  • Accessible focus and keyboard behaviour

Review search data without exposing personal information

Measure queries, no-result and no-click searches, result clicks and useful downstream actions if the platform supports them. Shopify's Search & Discovery reports include query, no-result, no-click, click and purchase activity on search-results pages; they exclude predictive-search interactions, and the app shows the last 30 days. Shopify's full behaviour reports can include longer date ranges, but search data may be delayed by up to 72 hours. Check the platform's definitions and tracking before comparing results.

If search logs contain personal data, collect only the fields needed for a stated purpose and periodically review and delete records that are no longer needed. Assign an owner and retention rule. Use aggregate patterns to improve catalogue labels or merchandising, and do not describe search activity as a conversion result unless the measurement connects it to an outcome.

Test with a small query set after each change

Maintain a representative list of known product names, model numbers, broad needs, misspellings and queries with no match. The examples below are illustrative: replace them with terms from the store's own catalogue and agree the expected products before testing.

Google notes that its search generally does not submit searches into a site's search box. Keep important category and product pages reachable through ordinary links instead of relying on onsite search as the only discovery path.

Illustrative ecommerce search test set; replace each query and expected result with catalogue-specific examples
Query typeExample queryExpected result to recordCheck
Exact identifierJM-XL1The product or variant with that exact identifier appears.Confirm the identifier is in a field the search system uses.
Partial identifierJM-XLAll intended products sharing the prefix appear if partial-code search is a requirement.Record whether the behaviour applies to predictive search, submitted search or both.
Synonym or use casewaterproof walking shoesRelevant waterproof products appear even if the catalogue uses a different shopper-facing phrase.Check the mapped synonym and product attributes.
Misspellingstainles steel bottleThe intended product appears, or the shopper gets a useful correction or recovery option.Test only the typo behaviour the platform or configuration is meant to support.
Broad needsmall hallway tableA useful set of matching products appears with plain ways to narrow the choice.Check the relevance and usefulness of the first results.
No matchlantern refill xyzA plain no-result message keeps the query available and offers a sensible next step.Try spelling help, removing a filter, browsing a category or contacting support.

Sources and related reading

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