Understand the search question
Combine exact signals with query understanding and semantic matching where that adds value.
AI Search →Follow the core flow of Findoviq: understanding what someone is looking for, building a useful result experience, directing commercially, measuring behavior and improving it in a controlled manner.
Combine exact signals with query understanding and semantic matching where that adds value.
AI Search →Search field, autocomplete, results, filters, mobile and zero-result searches together form the search experience.
Search UX →Use ranking rules, campaigns, banners, stock and other signals with clear guardrails.
Merchandising →Track search KPIs and link orders only when the attribution is sufficiently substantiated.
Analytics →Use query sets, judgment and regression tests before rolling out changes widely.
Search Quality →Monitor latency, index freshness, event health, releases and incidents.
Search Operations →Use brand, SKU, category, natural-language and problem queries from your own shop to assess relevance.
Demo evaluation →Check which fields, variants, identifiers and updates are needed to enable good results.
Product data →Agree in advance how CTR, zero-result searches, conversion and other signals are defined and compared.
Analytics overview →Assess who can adjust ranking, synonyms, campaigns and releases and how changes remain verifiable.
Merchandising →A good demo shows how the parts work together. The final choice becomes stronger when you use the same test set, criteria and definitions for each solution.
Include your most important queries, platform, catalog and desired KPIs in the conversation.