Documentation reference
Research Repository
A research repository stores studies, notes, findings, evidence, decisions, and opportunity tags in a way that product, design, marketing, and leadership can actually reuse.
Overview
What this document is
A research repository stores studies, notes, findings, evidence, decisions, and opportunity tags in a way that product, design, marketing, and leadership can actually reuse.
Fit signals
When to use it
- Research notes are spread across Docs, Notion, recordings, and slides.
- Teams repeat research because past findings are hard to find.
- Product decisions need traceable evidence.
- A growing team needs shared customer knowledge.
Audience and ownership
Who uses it
Product teams, agencies, founders, and UX researchers who need reusable evidence instead of scattered research notes.
Before and after
Where it fits in the build chain
Gather before writing
Inputs required
- Study index schema
- Insight card template
- Evidence and source-linking checklist
- Repository ownership and maintenance rules
Core contents
Recommended structure
- Study index and participant records
- Finding cards with evidence and confidence
- Tags for product area, segment, pain, and opportunity
- Decision links and source traceability
- Contribution and maintenance workflow
What each part should cover
Section-by-section guide
Studies
Describe the studies clearly enough that a founder, teammate, or AI agent can use it without needing hidden context.
Participants
Describe the participants clearly enough that a founder, teammate, or AI agent can use it without needing hidden context.
Findings
Describe the findings clearly enough that a founder, teammate, or AI agent can use it without needing hidden context.
Evidence
Describe the evidence clearly enough that a founder, teammate, or AI agent can use it without needing hidden context.
Tags
Describe the tags clearly enough that a founder, teammate, or AI agent can use it without needing hidden context.
Decisions
Describe the decisions clearly enough that a founder, teammate, or AI agent can use it without needing hidden context.
Practical workflow
How to create and use it
- 01Create a study index with goals, methods, participants, and date.
- 02Store findings as reusable insight cards linked to evidence.
- 03Tag findings by segment, product area, journey stage, and confidence.
- 04Review repository health and archive stale or duplicated insights.
Copy into your workspace
Starter template
- 01Define study, participant, finding, evidence, and decision records.
- 02Create tags for segment, product area, journey stage, and confidence.
- 03Document contribution rules and review cadence.
- 04Link insights to PRD, roadmap, and design decisions.
Make the draft usable
Weak vs strong examples
Research question
Weak
Do users like the idea?
Strong
What causes operations teams to abandon spreadsheet-based onboarding, and what evidence would make them trust a shared client portal?
Participant criteria
Weak
Talk to business users.
Strong
Interview 8 operations leads at service businesses with 10-100 employees who currently manage client onboarding across email, spreadsheets, and shared drives.
How to know it is useful
Quality checklist
- 01Every insight links back to supporting evidence.
- 02Tags make findings discoverable by product area, segment, and journey stage.
- 03Ownership and contribution rules are documented.
- 04The repository supports decisions, not just storage.
Before you hand it off
Document readiness checklist
- The research repository has a named owner and approval path.
- The business or product decision this document supports is explicit.
- Inputs, assumptions, and open questions are separated from confirmed facts.
- Scope boundaries and non-goals are clear enough to prevent silent expansion.
- The document can be handed to a teammate, agency, or AI agent without hidden context.
- Every insight links back to supporting evidence.
- Tags make findings discoverable by product area, segment, and journey stage.
- Ownership and contribution rules are documented.
Generate the first draft
AI prompt
Design a research repository system for this team. Include study index, participant records, finding cards, evidence links, quote storage, tags, confidence levels, decision links, ownership model, contribution workflow, and maintenance cadence.
Avoid these
Common mistakes
- Dumping raw notes without synthesis.
- No tags, taxonomy, or owner.
- Insights without source evidence.
- Building a repository nobody knows how to contribute to.
Use this after the draft
Handoff assets
- Repository schema
- Tag taxonomy
- Insight card template
- Maintenance owner and cadence
Suggested build path
What to create before and after
Before
PRD
Keep this connected so the build stays traceable.
Current
Research
Use this page to create the working draft.
After
IA
Keep this connected so the build stays traceable.
Zenith CTA
Need this shaped for your business?
Zenith can turn rough notes into a founder-ready research repository.
Bring your idea, current docs, users, constraints, and open questions. We will help make the next decision clear.