Interview Synthesis

Interview Synthesis Skill

Interview piles get "synthesized" two bad ways: the highlight reel (the quotes that confirmed what the team hoped) and the mush ("users want simplicity" — twelve hours of conversation flattened into a poster). Honest synthesis is mechanical before it's interpretive: code the notes (what did each person actually say, tagged), count the themes (a theme is something multiple people said — with the number attached), preserve the divergences (the two dissenters are data, not noise), and size every claim to the sample — twelve interviews support "we repeatedly heard," never "users want."

Not quite this? Use user-interview-synthesis when the interviews are product-discovery research with users.

What This Skill Produces

• The coded pass — each interview's statements tagged to emerging codes, traceable back to the speaker
• The theme table — themes with counts (7/12 raised unprompted; 3 more agreed when asked — the prompted/unprompted split matters)
• The divergence report — who disagreed with each theme and why; the outliers examined, not deleted
• The claims, sample-sized — findings phrased at what N interviews can carry, with the quotes that illustrate honestly

Required Inputs

Ask for these if not provided:

• The notes/transcripts — the actual material; synthesis of summaries synthesizes the summarizer's biases
• The questions the interviews served — what the study was trying to learn; themes get organized against them (plus the "unexpected" bucket, often the best one)
• The sample's shape — who these people are, how selected (12 enthusiastic volunteers ≠ 12 representative users — the selection shapes what claims are legal)
• What the team already believes — stated up front as hypotheses; the synthesis marks confirms/contradicts explicitly (the contradicts are the expensive-to-lose ones)

Framework: The Synthesis Rules

1. Code before theming: pass one is mechanical — each substantive statement tagged (needs-integration, pricing-confusion, workaround-X) with speaker attribution. Themes emerge from tag frequencies, not from memory — memory promotes the vivid, and vividness isn't prevalence.
2. Count, and split prompted from unprompted: every theme carries its number ("8/12"), and unprompted mentions outweigh prompted agreements — "seven raised pricing before we asked" is a finding; "everyone agreed pricing matters when asked" is politeness. The counts keep the highlight reel honest.
3. Divergence is data: the two who disagreed get examined — different segment? Different workflow? Their why often reveals the theme's boundary condition ("the theme holds for teams over ten; both dissenters were solo"). Deleting outliers manufactures consensus; bounding themes with them manufactures insight.
4. Quotes illustrate counted themes — never substitute for them: each theme gets 1–2 verbatim quotes chosen for representativeness (the middle of the distribution, not the spiciest take), attributed at the agreed anonymity level. A vivid quote for a 2/12 theme is cherry-picking with production values.
5. Size claims to the sample and selection: twelve interviews earn "a recurring pattern among [who we talked to]" — not "users want," not percentages ("58% of users" from n=12 is numerical cosplay). The confidence line states sample, selection, and what would harden the finding ("survey to size it" — the survey-design-basics handoff).