I recently needed to turn ten customer interviews into actionable insights in under a day. I didn’t have time to export to Miro or run a full research sprint, so I used Notion for a rapid qualitative synthesis with an affinity mapping approach. It’s straightforward, low-friction, and—surprisingly—works really well when you keep the process tight. Below I’ll walk you through exactly how I do it, including setup, hands-on steps, templates, and the small rituals that make the output usable for product and growth decisions.

Why I use Notion for affinity mapping

Notion isn’t a visual board first, but its databases and flexible pages make it ideal for fast, collaborative synthesis when you care about traceability and follow-up. I can link quotes back to interviews, add tags and properties, filter by user segment, and then export or share polished findings with stakeholders. For quick workshops where people might not be comfortable on a whiteboard, Notion lowers the onboarding friction.

What you need before you start

  • Audio recordings or transcripts of 10 interviews (even rough timestamps are fine).
  • A Notion workspace with a dedicated page for the project.
  • A short template for interview notes (copy-paste friendly).
  • 1–3 collaborators for the synth session—more can be noisy for rapid mapping.
  • Blocks of 2–3 hours for the hands-on synthesis once notes are in Notion.
  • Quick setup: Notion structure I create

    I build a tiny research database and a few views so everything is filterable and traceable. Here’s the structure I use:

    Notion elementPurpose
    Interviews (database)Each interview is a row with properties: participant, date, segment, recording link, transcript link, raw notes.
    Insight snippets (database)Every interesting quote, observation, or pain point becomes a row. Key properties: interview ref, theme tags, sentiment, priority, certainty.
    Affinity board (Board view of snippets)Used for clustering snippets into groups (themes/opportunities).

    Template for interview notes (paste into Notion)

    I use a compact structure so note-taking is fast:

  • Participant: [name / anon id]
  • Segment: [power user / new user / churn risk]
  • Top tasks: [what they want to do]
  • Pain points: [bullets of pain]
  • Quotes:
  • - “...” — timestamp
  • - “...” — timestamp
  • Ideas / immediate implications: [quick thoughts]
  • How I extract snippets quickly

    Go through each interview one by one and paste short snippets into the Insight snippets database. The goal is brevity: each row should contain a single idea or a single quote. I aim for 6–12 snippets per interview—enough to capture variety without overwhelm.

  • Use the transcript search to grab exact quotes and add timestamps.
  • If you don’t have transcripts, use short paraphrases and mark them as paraphrased in a property.
  • Add the interview row as a relation so every snippet links back to the source.
  • Affinity mapping workflow inside Notion

    Once you have 60–120 snippets (10 interviews x ~6–12 snippets), switch to a Board view of the snippets database and create a handful of default columns like “Unsorted”, “Needs validation”, “Pain”, “Desired outcome”, and “Opportunity”.

  • Drag snippets from Unsorted into clusters. Try to group by problem or user need rather than solution.
  • Rename columns as themes emerge (e.g., “Onboarding confusion”, “Billing friction”).
  • Keep clusters focused: if a column becomes too broad, split it into sub-themes.
  • Timeboxing the session

    For 10 interviews I usually run a 2.5–3 hour session:

  • 30–45 minutes: rapid reading and extracting snippets (I do this solo or with one other person).
  • 60–75 minutes: collaborative clustering and naming themes.
  • 30–45 minutes: write insight statements, opportunities, and next steps.
  • Writing useful insight statements

    After clusters form, I convert them into short insight statements. I use a simple template:

  • Observation: What we heard (include 1–2 quotes).
  • Why it matters: Behavior or metric it might impact.
  • Opportunity: A possible hypothesis or design direction.
  • Example: Observation — “Users don’t know where to find discount codes” (“I never looked in billing for promo codes” — P4). Why it matters — could reduce conversion rate during onboarding. Opportunity — surface codes earlier in the signup flow; A/B test change and measure conversion.

    Prioritizing insights into experiments

    Turn opportunities into experiments using three quick properties in Notion: Impact (high/med/low), Effort, and Confidence. I then prioritize by highest impact and lowest effort. For each top opportunity I add:

  • A short hypothesis (“If we X, then Y will increase by Z%”)
  • Primary metric to measure (e.g., onboarding completion, activation rate)
  • Owner and a rough timeframe (1–2 sprints)
  • Tips and tactics that speed things up

  • Use emojis and color names in column titles for quick scanning—visual cues are surprisingly helpful.
  • Keep quotes short. Long paste-ins slow down the board and make clustering noisy.
  • Mark paraphrased items so you know which need transcript verification.
  • Limit participants in the cluster session to 3–4. Too many people create discussion tangents; the goal is grouping and naming, not debating every quote.
  • Export to stakeholder-friendly formats using Notion’s export to PDF or copy the insight statements into an async report with a short executive summary.
  • Common questions I get

  • Is Notion as good as Miro for affinity mapping? For visual exploration Miro is great. For traceability, tagging, and turning insights into tracked work, Notion wins. I often start in Notion; if a team wants a visual board for stakeholders, I export selected clusters to Miro.
  • How many snippets per interview? Aim for 6–12. Fewer than 5 risks missing nuance; more than 15 becomes noise unless you plan a full analysis.
  • How do you handle conflicting quotes? Capture both. Add an insight that highlights variance (“Users are split on X”) and treat it as a testable hypothesis—segmentation often explains the split.
  • Quick reference: timeline template

    StepGoalTime
    Extract snippetsCreate 60–120 concise snippets linked to interviews30–45m
    Affinity clusteringGroup snippets into themes60–75m
    Write insightsProduce insight statements + opportunities30–45m
    PrioritizeCreate shortlist of experiments15–30m

    If you want, I can share a Notion template (database properties and a prebuilt board view) you can duplicate into your workspace. It’ll save you the setup time and makes the process repeatable across projects. Tell me how you run interviews (audio vs transcript vs notes) and I’ll tailor the template to suit your workflow.