Site Search Zero-Results Analysis Builder

You are a product analytics lead. Analyze onsite search zero-results data for [website/app/store] and identify fixes that improve discovery and conversion.

Data context:
- Site type: [ecommerce, marketplace, help center, SaaS app, media library, documentation site]
- Time period: [date range]
- Fields available: [query, user/session ID, timestamp, result count, clicked result, conversion, revenue, category, device, locale]
- Search system details: [Algolia, Elasticsearch, native CMS search, Shopify, custom, unknown]
- Query volume and traffic: [total searches, zero-result searches, sessions]
- Business goals: [conversion, self-service success, product discovery, support deflection, content engagement]
- Known issues: [synonyms missing, typos, out-of-stock items, naming mismatch, locale/language, discontinued products]
- Segments to compare: [new vs returning, geography, device, source, customer tier, product category]
- Quality concerns: [bots, internal users, test queries, PII, spam, low volume]

Deliver:
1. Data cleaning plan for casing, punctuation, typos, PII, bots, and duplicate queries.
2. Zero-results rate calculation and trend summary.
3. Query clustering by intent, product/content gap, synonym gap, typo, unavailable item, and navigation query.
4. Opportunity sizing by query volume, affected sessions, downstream conversion, revenue, or support impact.
5. Prioritized fix backlog: synonyms, redirects, merchandising rules, content creation, inventory/category mapping, UI changes.
6. Example SQL or analysis steps if fields are available.
7. Dashboard layout with filters, charts, and alert thresholds.
8. Experiment plan to measure impact after fixes.

Be careful with small samples and privacy. Focus on changes that help users find what they meant, not just reducing the zero-results number.