Customer Interview Repository Setup: How to Store, Tag, and Reuse Transcripts

A customer interview repository is a shared place where you store transcripts in a consistent format, tag them with helpful metadata, and control access so anyone can find evidence fast. Set it up by choosing one “source of truth,” using a simple folder structure, naming every file the same way, and publishing each new transcript through a short SOP. With these pieces in place, your team can reuse quotes, validate decisions, and avoid re-interviewing customers for the same answers.

Primary keyword: customer interview repository

Key takeaways

• Pick one system to be the “source of truth” and standardize how transcripts enter it.
• Use a predictable folder structure and a strict file naming convention.
• Capture metadata (tags) that match how people search: persona, company size, topic, date, and interview type.
• Limit access with roles (view, edit, admin) and protect sensitive data with clear rules.
• Publish every transcript with the same SOP so search stays reliable over time.

What a “good” customer interview repository looks like

A good repository lets a teammate answer: “Do we have evidence for this claim?” in minutes, not hours. It works even when the person who ran the interview is out of office.

It should be:

• Searchable: by keyword and by filters like persona, topic, and date.
• Consistent: every transcript follows the same structure and naming rules.
• Secure: only the right people can access sensitive interviews.
• Reusable: quotes and insights can be copied with context (who/when/why) and a link back to the source.

Most teams fail on consistency, not tooling, so start with rules before you add new software.

Choose your “source of truth” and decide what files you will store

Pick one place where the final transcript lives, then link to it everywhere else (roadmap docs, research reports, tickets). This avoids duplicates that drift over time.

What to store for each interview

• Transcript file: the final, cleaned transcript (text or doc format).
• Recording link: a link to audio/video stored securely (or the file if your policy allows).
• Metadata: stored in the file header and/or in your system’s properties (tags).
• Consent note: where consent is recorded (or where your consent form is stored).
• Summary: a short “what we learned” paragraph plus 3–5 bullets for key points.

If you handle personal data, set a retention rule and a redaction rule before you start scaling storage. Keep this simple and written down so you can follow it consistently.

Where to store it (practical options)

• Shared drive (Google Drive/OneDrive): easy to start, strong permissions, good full-text search.
• Research repository tools (Notion/Confluence): great for pages + tags, but make sure file naming stays consistent.
• Dedicated research platforms: strong tagging and clips, but you still need naming, permissions, and an SOP.

Whatever you choose, document: “This is where the final transcript lives,” and enforce it.

Folder structure that stays usable at 20 interviews or 2,000

Your folder structure should match how you manage work, not how you search it. Search should come from metadata tags, while folders keep things orderly.

Recommended folder structure (simple, scalable)

• /Customer Research
  • /00_README (rules, templates, SOP)
  • /01_Transcripts
    • /2026 (year)
      • /2026-01 (month)
      • /2026-02
    • /Archive (old formats, deprecated)
  • /02_Summaries (one-pagers, synthesis docs)
  • /03_Consent (templates, signed forms, policy notes)
  • /04_Requests (intake forms, “evidence needed” asks)

Use dates to keep it neutral across teams and products, then rely on tags for product, persona, and topic.

When to add more folders (and when not to)

Add a new top-level folder only when it changes permissions or ownership, like “Legal-reviewed interviews” or “Partner interviews.” Avoid product-based folder trees because products change names and teams reorganize.

Naming conventions that make transcripts easy to scan and hard to misfile

A strict naming convention is the fastest, cheapest upgrade you can make to your customer interview repository. It helps with sorting, duplicates, and quick sharing.

A naming template you can copy

• YYYY-MM-DD__InterviewType__CompanyOrSegment__Persona__Topic__InterviewerInitials

Example:

• 2026-02-10__Discovery__SMB-Healthcare__Ops-Manager__Onboarding-friction__JL

Naming rules (keep them short and enforceable)

• Use ISO dates (YYYY-MM-DD) so files sort correctly.
• Use double underscores to separate major chunks; avoid special characters like “/” and “&”.
• Pick controlled vocabulary for InterviewType (Discovery, Usability, Win/Loss, Churn, Beta, Support).
• Use a segment label when company names are sensitive (e.g., “ENT-Fintech” instead of a company name).
• Do not include a participant’s full name in the filename.

Put the full details inside the transcript header, not the filename.

Metadata tags: what to capture and how to keep tagging consistent

Folders help you store transcripts, but tags help you find them. The best tags match the questions people ask when they search for evidence.

Core metadata fields (start here)

• Interview date: YYYY-MM-DD
• Interview type: Discovery, Usability, Win/Loss, Churn, etc.
• Product area: Billing, Onboarding, Reporting, API, Mobile
• Persona / role: Admin, Manager, IC, Buyer, Champion
• Customer segment: SMB, Mid-market, Enterprise (or your own tiers)
• Industry: Healthcare, Fintech, Education, etc.
• Topics: your “tag set” for pain points, jobs-to-be-done, and features
• Region/language: if relevant for market differences
• Status: Draft, Final, Redacted

Optional fields (use only if you will actually filter by them)

• Recruiting source: sales-led, in-product, panel
• Account tier: if you have a clear definition
• Lifecycle stage: trial, new, active, churned
• Consent scope: internal only, anonymized, usable for marketing (if you track this)

How to prevent “tag chaos”

• Use a controlled vocabulary: one approved list for interview type, persona, and segments.
• Limit topic tags: start with 15–30 and expand only when needed.
• Use prefixes for topics: like Pain:, JTBD:, Feature:, Competitor: so search results group well.
• Write tag definitions: one sentence each in your README folder.
• Assign a librarian: one owner who can merge duplicates and fix misspellings.

Transcript header template (paste into every transcript)

• Title:
• Date:
• Interview type:
• Interviewer:
• Participant: (anonymized ID)
• Company/Segment:
• Persona:
• Product area:
• Topics (tags):
• Recording link:
• Consent location/scope:
• Summary: 3–5 bullets

This header makes the transcript readable even when it gets copied into another doc.

Permissions and privacy: who can see what (and why it matters)

Customer interviews often include sensitive information, so your repository needs clear access rules. Set permissions at the folder level where possible, then handle exceptions with subfolders.

Simple role model for access

• Admins (Research Ops / lead): manage structure, permissions, retention, and templates.
• Editors (Researchers/PMs/Designers): publish transcripts and add tags.
• Viewers (Broader team): read and search, but cannot edit source files.

What to restrict by default

• Raw recordings (audio/video), especially if they include names, screens, or contact details.
• Consent forms and any files with direct identifiers.
• Interviews tied to legal issues, HR topics, or regulated data.

If your interviews include personal data, your internal policies and local laws may apply, so involve your privacy or legal partner early. For general background on privacy principles, see the GDPR overview as a starting point for concepts like data minimization and access control.

Redaction and anonymization basics

• Replace full names with participant IDs (e.g., P-0142).
• Remove contact details, addresses, and account numbers.
• Mask screenshots or screen-share text if you store clips or images.

Decide whether you will keep a separate “key” that maps IDs to identities, and restrict it to admins only.

SOP: publishing a new transcript (repeatable process)

This SOP keeps your repository clean and searchable even when different people add content. Put it in your /00_README folder and link it in your research intake form.

Publishing SOP (10–15 minutes per interview)

• 1) Confirm consent and scope. Note whether the transcript is internal-only or can be quoted externally.
• 2) Create the transcript file using the naming convention. Start from your header template.
• 3) Clean the transcript lightly. Fix obvious speaker labels, remove filler only if it changes meaning, and mark unintelligible sections.
• 4) Add metadata. Fill in the header fields and apply the repository tags in your system (if supported).
• 5) Redact sensitive details. Replace names with IDs and remove contact info.
• 6) Add a short summary. Write 3–5 bullets that a busy teammate can skim.
• 7) Link the recording. Use a stable, permission-controlled link and verify access.
• 8) Save to the correct folder. Usually /01_Transcripts/YYYY/YYYY-MM.
• 9) Update the index. Add one row to your “Interview Index” (sheet/table) with key fields and a link to the transcript.
• 10) Announce if needed. Share the summary and link in your research channel with the top tags.

Minimum “Interview Index” fields (for fast filtering)

• Date
• Interview type
• Persona
• Segment
• Product area
• Top 3 topic tags
• Link to transcript
• Link to recording (if allowed)
• Status (Draft/Final/Redacted)

If your drive search is weak, this index becomes your main search surface, so keep it mandatory.

Quick guide: finding evidence fast (in 5 minutes)

When someone asks for proof, your job is to find the most relevant quotes with enough context to trust them. Use this flow to avoid getting lost.

Step 1: Translate the question into tags

• Who matters? (persona, segment, industry)
• What area? (product area)
• What theme? (topic tags like Pain:Onboarding, JTBD:Reporting)
• How recent? (last 6–12 months, or since a product change)

Step 2: Filter in your Interview Index first

• Filter by persona + product area.
• Narrow to 5–10 interviews by date and segment.
• Open the best 2–3 transcripts and use in-document search (Ctrl/Cmd+F) for the keywords.

Step 3: Pull quotes with context

• Copy the quote plus 1–2 lines before and after it.
• Record the transcript link, date, persona, and interview type next to the quote.
• Note any constraints (e.g., “beta user,” “churned customer,” “admin role only”).

Step 4: Sanity-check before sharing

• Is the quote still valid after a recent product change?
• Does it represent one person or a pattern across multiple interviews?
• Is the consent scope internal-only?

If you share evidence in product docs, consider linking to the transcript instead of pasting large sections, so readers can verify the source.

Pitfalls to avoid (so the repository doesn’t rot)

Repositories fail when they become inconsistent, over-permissioned, or full of duplicates. These are the most common problems and fixes.

Pitfall: too many tags, too soon

• Fix: keep topic tags small and add new ones only when you see repeated searches that fail.

Pitfall: transcripts live in personal folders

• Fix: make publishing part of “done,” and block research readouts until links point to the source of truth.

Pitfall: inconsistent speaker labels and messy formatting

• Fix: set a standard (Interviewer / Participant) and require a quick cleanup pass before “Final.”

Pitfall: unclear permissions lead to oversharing

• Fix: default to restricted recordings and anonymized transcripts, and document exceptions.

Pitfall: no owner

• Fix: assign a repository owner (even part-time) to keep templates, tags, and access clean.

Common questions

• Should we store audio/video recordings, or only transcripts?
  Store transcripts as the default and link to recordings when you have consent and a secure place to keep them.
• How detailed should our tags be?
  Tag to support real search needs: persona, segment, product area, and 3–8 topic tags usually beat 30+ tags per interview.
• What if we interview in multiple languages?
  Store the original transcript and an English version if your team needs it, then tag both with language and link them together.
• How do we handle names and sensitive info in transcripts?
  Use participant IDs, redact direct identifiers, and restrict access to any mapping file or consent docs.
• How do we keep the repository updated when teams change?
  Write the SOP, keep templates in one place, and give one role ownership for structure, tags, and permissions.
• Can we use AI tools to search and summarize transcripts?
  Yes, but keep the original transcript as the source of truth, and review summaries before you treat them as evidence.

Where transcription and formatting fit in

A repository is only as good as the text inside it, so transcripts should be readable and consistent. If you use automated transcription, plan time for cleanup and standard speaker labels, or send the text for a proofreading pass using transcription proofreading services.

If you need a mix of speed and cost control, you can start with automated transcription and then publish only “Final” transcripts after review.

Once your customer interview repository is in place, the biggest win comes from using it weekly: linking evidence in decisions, reusing quotes in research readouts, and reducing repeated questions across teams. When you need help turning recordings into consistent, searchable transcripts, GoTranscript provides the right solutions with professional transcription services.