PRD Template for Search

Example: "Our workspace contains an average of 2,400 documents per team. Users report spending 15+ minutes per day searching for existing content, with a 34% success rate on first search attempt. The current search only matches document titles, missing content within documents, comments, and attachments. Internal surveys show search frustration is the #2 reason for churn among teams with 50+ documents."

Example: "Primary: Achieve 80%+ search success rate (user clicks a result in the top 3) within 90 days, up from 34%. Secondary: Reduce average search-to-result time from 15 seconds to under 3 seconds. Comprehensiveness: Support full-text search across documents, comments, ticket descriptions, and file names. Latency: Return results within 500ms for workspaces with up to 50,000 documents."

Example: "As a PM, I want to search across all project documents by content so that I can find a specific requirement even when I do not remember which document contains it. Acceptance criteria: full-text search returns results within 500ms; results show the matching text in context with highlighted search terms; results are ranked by relevance with most recent documents boosted; search works across PRDs, tickets, comments, and context sources."

Example: "FR-1: The system must index document content, titles, comments, ticket descriptions, and file names. FR-2: Search must support exact phrase matching using quotes (e.g., 'user onboarding'). FR-3: Results must be ranked by a relevance score that considers term frequency, document recency, and user interaction history. FR-4: Users must be able to filter results by content type, date range, author, and project. FR-5: Autocomplete suggestions must appear after typing 2+ characters, showing top 5 matches within 200ms."

Example: "NFR-1: Search queries must return results within 500ms at p95 for indexes up to 100,000 documents. NFR-2: New content must be searchable within 30 seconds of creation. NFR-3: Search results must respect access controls — users must only see results from documents they have permission to view. NFR-4: The search index must not exceed 20% of the primary database storage size. NFR-5: Index rebuilds must complete within 2 hours for a full workspace re-index."

Example: "Metric 1: Search success rate (click in top 3). Baseline: 34%. Target: 80%. Metric 2: Zero-result query rate. Baseline: 22%. Target: under 5%. Metric 3: Median time from search to result click. Baseline: 15s. Target: under 3s. Metric 4: Search usage rate (% of active users who search daily). Baseline: 28%. Target: 60%. Metric 5: Repeat search rate (same query within 5 minutes). Baseline: 31%. Target: under 10%."

Example: "For our current scale (under 100K documents), we will use PostgreSQL full-text search with tsvector columns and GIN indexes, avoiding the operational overhead of a separate search cluster. If we exceed 500K documents or need advanced relevance features (learning-to-rank, semantic search), we will migrate to Elasticsearch. Indexing will be asynchronous via a background job that processes document changes from a queue. Access control will use a pre-filter approach — the search query includes a WHERE clause limiting results to documents the user can access."

Example: "Risk: Search returns irrelevant results, causing users to abandon search and browse manually. Likelihood: High (initially). Impact: Medium. Mitigation: Implement a feedback loop — track which results users click and use this to tune ranking. Provide a 'not helpful' action on results. Risk: Access control leak — search returns titles or snippets from documents a user cannot access. Likelihood: Low. Impact: Critical. Mitigation: Apply permission checks as a search pre-filter, not post-filter. Test with automated access control verification suite."