Asb Interview Report

Interview Report: What You Know, What You Think

A round of interviews ends and the learning scatters: a hypothesis file only its author can decode, debriefs nobody rereads, teammates asking "so what did we actually find?" This skill closes the method by distilling all of it into one report — what is now known (including what got disproved), what is merely thought, and what remains untested — every claim carrying its evidence, in the customers' own words, organized so the people doing positioning, ideal-customer, pricing, marketing, and product work can act on it.

The mental model

The report is the bridge from evidence to action

The interview method runs goals → hypotheses → questions → interviews → learning. Its output is validated facts: hypotheses confirmed, overturned, or tuned by real customer voices. Those facts are the raw material of strategy — but there is no mechanical procedure that turns "what customers said" into "what to do next." Humans do that combining, and they can only do it if the facts arrive organized, honest about their strength, and traceable to their sources. That package is this report. It is deliberately NOT the strategy itself: it delivers the evidence and names the decisions the evidence raises, and stops there.

Two readers, one document

The report serves both at once:

• The human skimmer reads only the top. So the report opens with a summary that is as brief as possible without losing anything salient — and each line is exactly three things: the status mark, the crisp claim, the F-number. Nothing else. No citations or quotes; no commentary or interpretation; no history of the finding — no "which cuts against what we assumed," no "unlike our original hypothesis," no "ambiguous between X and Y." The status mark IS the entire confidence-and-history a summary line gets; how the finding evolved, what it contradicts, and what it might mean all live in the body. Numbers may be part of the claim ("…one lost job ($300–800)"); explanations may not. If a summary line grows a "which…" clause or an em-dash explanation, cut the clause and put it in the finding.
• The deep reader — a teammate doing the positioning work, or an LLM assisting any downstream exercise, which reads everything regardless of length — gets the reference sections below: every finding with its voice-count, its debrief citations, and verbatim quotes. In the body, ALWAYS quote and ALWAYS cite, with multiple examples when multiple exist: the citations are simultaneously the proof that a claim is correct and the trail for finding out more.

The finding-numbers (F1, F2, …) are the hinge between the two: a summary line ends with its F-number, and the F-entry below carries the evidence. The rule of thumb: when brevity is the goal, examples are bloat; everywhere else, examples are the proof — they make a claim believable, hard to counter, and easy for the reader to research further.

Epistemic honesty is the product

The single way this report fails is by stating things more strongly than the evidence supports — then every decision built on it inherits the inflation. So every finding wears its status:

• ✓ Validated — a clear pattern across several conversations confirmed it. Knowledge.
• ✗ Disproved — a clear pattern overturned it. Also knowledge — negative knowledge is often the most valuable kind ("customers will NOT pay extra for security" redirects an entire roadmap), so disproved beliefs are stated prominently as things now known, never buried as embarrassments.
• ~ Directional — supported but thin: few voices, or a single revelation that reframed thinking but hasn't been re-tested. Stated with its depth ("one voice, marked a revelation") and with what would settle it.
• 👀 Watch — heard once or twice, noticed, parked. Imported from the hypothesis file's watch section ("That's funny" items) and from lone debrief observations.
• ? Untested — a goal, hypothesis, or question the interviews never actually resolved: never asked, question misfired, segment never reached. Named plainly, because knowing what you don't know is what keeps downstream work honest.

Two more honesty obligations: sampling bias (who the interviewees were, how they were recruited, who's missing — "all referrals, no churned customers" changes what the findings mean) and "no pattern" findings (when answers genuinely scattered, that's a finding — knowing a pattern doesn't exist prevents building on a false one).

And state strength in numbers, never probability words. "Probably," "likely," "most," "often" mean wildly different things to different readers — the differences between individual interpretations are larger than the differences between the words — while "7 of 9" means the same thing to everyone. Every tally is exact; if a directional finding needs a confidence, be brave and put a number on it.

Splits are choices, never averages

When the evidence splits — five voices at $40, five at $300 — the report never averages it into a mid-point nobody asked for. "It's a balance" is usually a refusal to decide wearing the costume of moderation. A split is either an emergent segment (report both claims, each naming whom it's about, plus the markers that sort them) or a genuine no-pattern finding (reported as such); the downstream decision it raises is a choice, and the report names that choice without making it. Related caution for readers, worth a line in the product brief when relevant: tallies establish facts — where an objectively true answer exists and individual errors cancel out — but votes cannot design; averaging contradictory desires produces the bland thing nobody hated enough to veto, not the thing anyone loves.

What the downstream work needs

Each per-area brief marshals findings for a specific exercise, in that exercise's own terms:

• Ideal customer: keystone candidates (what the best interviewees valued extremely — enough to drive a purchase by itself), deal-breaker candidates (what disqualified the product regardless of fit), the inciting-event stories actually heard (the specific trigger moments that turned someone into an active buyer — quoted, because these are collected precisely by interviewing), sorting markers (behavioral and attitudinal characteristics that separate best-fit from poor-fit — never mere demographics), and best-vs-worst differentials.
• Positioning & messaging: the customers' exact vocabulary (what they call themselves, the problem, the product category — their words are the raw material of copy), the higher-level outcome they are actually buying (what they said the product is for, one level above what it does), the alternatives they compare against (including do-it-yourself coping), and the vivid specifics — real numbers, real emotions, real events — that make claims land.
• Pricing & packaging: willingness-to-pay bands with segment attached, the anchors customers reason from ("that's what the text-blast services cost"), budget and approval mechanics (whose money, who signs, what threshold).
• Marketing & sales: where these customers discover and buy, whom they trust, buyer vs. user vs. approver, the qualifying and disqualifying signals heard.
• Product priorities: pains ranked by evidence (how many voices, how hot the language), how customers cope today, unprompted feature pulls, and what moved willingness-to-pay when mentioned.

Vocabulary

• Finding (F1, F2, …) — one distilled claim with a status mark, evidence tally, debrief citations, and [H]/[G] references (an emergent finding that maps to no hypothesis or goal carries no tag). Numbers freeze when the report is finalized.
• Summary — the top section; salient claims only, F-numbered, citation-free.
• Vocabulary bank — the customers' verbatim words and loaded