customer-interview-synthesizer

name

customer-interview-synthesizer

description

Synthesizes raw customer interview transcripts into themes, quotes, Jobs-to-be-Done (JTBD) signals, force-of-progress diagrams, and actionable opportunity hypotheses with confidence levels. Use after a round of discovery, switching, win-loss, or churn interviews; when preparing a research readout; when aligning a team on what the customer signal actually says; or when feeding inputs into an Opportunity Solution Tree (OST).

Customer Interview Synthesizer

Turns hours of qualitative interviews into a tight, evidence-anchored set of opportunities.

What this skill is

A structured workflow for synthesizing interview transcripts: code utterances, theme them, score saturation, extract Jobs-to-be-Done (JTBD) signals and forces of progress, identify opportunity hypotheses, and produce a readout that distinguishes evidence from interpretation. Designed to remove the analyst's narrative-fitting bias and keep the customer's voice central.

What it solves

• "What did we learn?" readouts that summarize whichever interview was freshest
• Cherry-picking quotes that support a pre-existing hypothesis
• No theme saturation check (claiming a theme on a sample size of one)
• Conflating what the customer said with what the analyst inferred
• Failure to translate findings into prioritized hypotheses with confidence levels

When to invoke

• Concluding a discovery or generative interview round
• Synthesizing switching interviews after a churn wave
• Win-loss analysis from a sales cycle
• Sensemaking after a competitive deep-dive
• Feeding the Opportunity Solution Tree (OST) with fresh evidence

Phase 1: Catalog the corpus

For each interview, log:

• Participant pseudonym, segment, role
• Date, duration, interviewer
• Recording or transcript location
• Recruitment source (and any selection bias)
• Whether incentives were offered
• Whether the participant is current, former, or prospective customer

Minimum saturation guideline: 5-8 interviews per segment for generative discovery; more for major decisions.

Phase 2: Code the utterances

Read each transcript line by line. Tag passages with codes - short labels for the topic discussed.

Two-pass approach:

1. Open coding - generate codes inductively from the data
2. Axial coding - group related codes into categories

Each code must include:

• A verbatim quote from the transcript
• Interview Identifier (ID) and timestamp
• Whether it's a report (something they did or experienced) or opinion (something they said they'd do)

Reports far outweigh opinions in predictive value. Flag the distinction.

Phase 3: Theme the codes

Group codes into themes. For each theme:

• Theme title in the customer's voice
• Definition
• Number of participants who mentioned it (saturation count)
• 3-5 representative verbatim quotes
• Segments where the theme is strongest
• Disconfirming evidence (interviews where the theme didn't appear)

Saturation rule: a theme appearing in less than 30% of interviews in a segment is a hypothesis, not a finding.

Phase 4: Extract JTBD signals

For passages describing what the customer was trying to accomplish:

• Write the job statement: When [situation], I want to [motivation], so I can [outcome].
• Classify functional / emotional / social
• Identify the job stage (Define / Locate / Prepare / Confirm / Execute / Monitor / Modify / Conclude)

Phase 5: Forces of progress

For switching, churn, and win-loss interviews, map the four forces per participant:

Force	Evidence from interview
Push of current situation	What was broken or frustrating?
Pull of new solution	What did they hope for?
Anxiety of new solution	What worried them about switching?
Habit of old	What kept them on the old solution?

Aggregate across interviews to identify which force dominates the decision.

Phase 6: Generate opportunity hypotheses

Convert themes into opportunity hypotheses:

We believe [customer segment] experiences [pain or unmet need] when [situation], because [evidence].

Confidence: [High / Medium / Low] based on [number of interviews] and [type of evidence].

If we solved this, we'd expect to see [observable outcome].

Each hypothesis links back to:

• The theme(s) it came from
• The verbatim quotes that support it
• The disconfirming evidence (where it didn't show up)

Phase 7: Separate observation from interpretation

The synthesis output has two tiers, clearly labeled:

• What we heard (verbatim, quoted, sourced) - high confidence
• What it might mean (analyst interpretation) - explicitly labeled as inference

Never blur the line. Stakeholders will treat them as the same unless you separate them.

Output

• Coded transcript library (referenceable for any future synthesis)
• Theme list with saturation counts and supporting verbatims
• JTBD inventory: functional, emotional, and social jobs by segment
• Forces-of-progress diagram for switching or churn signals
• Opportunity hypothesis register with confidence levels and source evidence
• 1-page readout with the 3 most decision-grade findings
• Explicit list of disconfirming evidence
• Recommended next-round research questions

Operating rules

Always

• Quote verbatim before paraphrasing
• Distinguish reports from opinions
• Score theme saturation (count of interviews / total interviews per segment)
• Surface disconfirming evidence explicitly
• Label observation versus interpretation

Never

• Claim a theme from a single interview
• Cherry-pick quotes that confirm a hypothesis
• Use the analyst's words as if they were the customer's
• Skip the recruitment-bias note
• Merge wildly different segments into one theme