User goals
Which search scenarios, frustrations and customer journeys need to be demonstrably better?
Use cases →Requirements
First, record what search has to solve.
A requirements document prevents teams from diving directly into features. Start with user goals, product data, measurability and technical conditions.
Relevance
Exact matches, typo tolerance, synonyms, semantics, ranking and no-result behavior.
Search Quality →UX
Autocomplete, results, filters, mobile, accessibility and recovery.
Search UX →Product data
Fields, categories, attributes, variants, identifiers, availability and update frequency.
Product data →Analytics
Define events, KPIs, segmentation, conversion attribution and data quality.
Analytics →Merchandising
Capture campaigns, boosts, banners, runtimes, reels and guardrails.
Merchandising →Integration
Describe commerce platform, feeds, APIs, storefront, events and error handling.
Integrations →Operations
Take monitoring, latency, availability, index freshness, releases and rollback with you.
Operations →Scale & context
Describe catalog size, peak load, stores, markets, languages and governance.
Enterprise →From requirement to proof
Make every important requirement testable.
A requirement like “good AI Search” is not testable. A set of own queries with expected results, latency boundaries and KPI definitions do.
RequirementEvidenceTest
RelevanceOwn query setResult assessment
IntegrationArchitectureTechnical scope
AnalyticsEvent definitionSample report
OperationsProcessError scenario