E-commerce
June 26, 2026
Internal search reveals what customers want to find, in their own words. If they type "gift under 50 euros", "refill", "fragrance-free" or "iPhone 15 compatible", the site must understand their intent.
Searchandising consists of improving results, synonyms, filters and product promotion. Support conversations can supplement queries to identify missing words and criteria.
This guide shows how to optimize internal search to help the customer find the right product faster.
Summary
Why is internal search strategic?
A customer who uses search often expresses strong intent. If they find nothing or irrelevant results, they may leave even though the product might exist.
Internal search must therefore understand customer words, not just exact catalog names.
An effective internal search transforms a clear intent into a visible product.
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Which signals should be analyzed?
Analyze queries with no results, searches with low click-through rates, reformulations, trending words, spelling mistakes, synonyms, filters used, and products viewed after a search.
Support conversations add another layer: they explain why the customer could not find what they were looking for.
How to manage synonyms?
Customers do not always use internal vocabulary. They may say "charger" instead of "adaptor", "waterproof" instead of "water-resistant", or "gift" instead of a product category.
Synonyms must be tested and maintained to avoid inconsistent results.
How to highlight the right products?
Searchandising can prioritize products that are available, popular, highly rated, adapted to the query, or strategic. However, it must remain relevant to the customer.
Highlighting an unsuitable product can damage trust and increase returns.
How to handle searches with no results?
A zero-result page must offer alternatives: synonyms, nearby categories, compatible products, support contact, or a chatbot. It should not simply display a failure.
Each frequent search without result must become a catalog or content signal.
The chatbot can complement this page by asking what the customer was really looking for, then proposing a nearby category or product. These exchanges then become signals to improve search.
A frequent search without result must be treated as a customer request, not as a simple lack of technical match.
Which flow to follow?
The flow must connect query and intent.
Analyze queries, zero results, clicks, conversions, reformulations, and filters used.
Add synonyms, corrections, redirections, and attributes according to customer words.
Prioritize relevant results according to availability, compatibility, reviews, and needs.
Use support conversations to understand uncovered intents.
Measure conversion, clicks, zero results, drop-offs, and related support questions.
Which examples should be used?
A "fragrance-free" search may require an ingredient attribute. A "gift for dad" search may lead to a guide page. An "old reference" search may redirect to the new model.
These adjustments must be based on reliable data, not just merchandising intuition.
When not to force a result?
It is better not to display a product if the match is too weak, if compatibility is uncertain, or if the product is unavailable without a clear alternative.
A bad result can be more frustrating than a zero-result page with good guidance.
Which KPIs should be monitored?
Track zero-result rates, post-search clicks, conversions, reformulations, filters used, out-of-stock products, support requests, and revenue generated from search.
These KPIs show whether search truly serves the customer's choice.
Which mistakes should be avoided?
Avoid prioritizing only high-margin products, ignoring synonyms, leaving frequent zero-result pages, or failing to connect search and support.
Search should help the customer find, not just organize the catalog.
How can Qstomy help?
Qstomy can connect the chatbot to the catalog, filters, product quizzes, return policies, internal search, support answer bases, and escalation rules to respond clearly, and then transfer sensitive cases with an actionable summary.
The chatbot helps the customer move forward without inventing a recommendation, compatibility, return rule, search result, or support answer that has yet to be confirmed by a reliable source.
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Key takeaways
Key Takeaways
Searchandising improves internal search using queries, synonyms, filters, availability, conversations, and customer intent.
What the customer needs to understand
The customer must find relevant results even if they do not use the exact words from the catalog.
The right limit for the chatbot
The chatbot can bring up uncovered intents, but the results must remain reliable and relevant.
Enzo
June 26, 2026
