# Voice-of-Customer Miner — Worked Example All companies, quotes, URLs, and figures are **fictional** — including the verbatims, which are invented here purely to show the format. (In a real run, an invented verbatim is the cardinal sin; in a fictional worked example, the fiction is declared.) Same scenario as the suite's other examples: Fieldlight, expanding into FSM, needs to know whether quoting is really the right lead move — and what Wrenchline's customers are angriest about. **Invocation:** `Mine voice-of-customer for Wrenchline and DispatchCrow — informs whether quoting is the right first module for our FSM expansion. Open sweep, but flag anything about quoting.` --- # Voice-of-Customer Snapshot ## 1. Scope **Products mined:** Wrenchline, DispatchCrow **Decision supported:** whether quoting is the right first module for Fieldlight's FSM expansion **Sources swept:** two B2B review sites (skew: negative, ops-manager heavy), both iOS/Android app stores (skew: technician anger after updates), one trades-owner forum (skew: owner-operators, small shops) **As-of date:** 2026-07-31 ## 2. Need Themes ### Theme: quote the job before leaving the driveway - **Frequency:** recurring — across both review sites and the forum, 20+ mentions in 6 months - **Verbatim:** "my guy finishes the walkthrough and then sits in the truck for 25 minutes building the quote on his laptop" — [review site, URL] - **Verbatim:** "if I don't get the quote out same-day I lose the job to whoever does" — [forum thread, URL] - **Who says it:** owners and office managers at 10-50 tech shops — **Inference** (reviewer titles where shown) - **Reading:** speed-to-quote is a revenue event, not an admin task — **Inference**; a quoting tool that starts from the scheduled job's data (already in the calendar) attacks the delay directly. ### Theme: techs need the app to survive a parking lot - **Frequency:** recurring — dominant complaint cluster in both app stores - **Verbatim:** "three taps to close a job became seven after the update. my techs just stopped closing jobs" — [app store review, URL] - **Verbatim:** "works great in the office wifi. useless in a parking garage" — [app store review, URL] - **Who says it:** field technicians directly (app stores are the one source where techs, not buyers, speak) — **Fact** (reviewer context) - **Reading:** the buyer evaluates the dashboard, but the tech decides adoption — **Inference**; app-store voice is the adoption early-warning channel the review sites miss. ### Theme: getting money in without chasing it - **Frequency:** concentrated — one long forum mega-thread, some review-site echo - **Verbatim:** "the work is done in June, the check clears in September" — [forum thread, URL] - **Who says it:** owner-operators — **Fact** (forum section) - **Reading:** invoicing/payment friction reads as a cash-flow problem, not a software feature — **Inference**; supports payments as the follow-on to quoting, but the concentration (one thread) caps confidence. ## 3. Competitor Weak Points - **Wrenchline:** "my techs won't use it" — recurring, 40+ reviews since January across both review sites — [URL] (consistent with the snapshot's weakness read; now in customers' own words) - **Wrenchline:** implementation pain — "we paid for eight weeks of setup and still did the data import ourselves" — recurring — [URL] - **DispatchCrow:** dispatch depth at scale — "fine until we hit 40 techs, then the board falls over" — concentrated in upmarket-switcher reviews — [URL] ## 4. Switching Triggers - **Push (off Wrenchline):** a failed update or forced tier migration is the named event in most switch stories — **Inference** (review mining, 8 switch narratives) - **Pull (to DispatchCrow):** "we were live the same afternoon" — same-day self-serve start recurs as the pull — **Fact** (their reviews, URLs) ## 5. So What? - **Opportunity hypotheses:** 1. Shops lose winnable jobs in the gap between walkthrough and quote — **Inference**, confidence: high (recurring across source types) 2. Tech-app usability decides adoption before any feature comparison does — **Inference**, confidence: high 3. Cash-flow pain makes payments the natural second module — **Inference**, confidence: low (single-thread concentration) - **Battle-card-ready weaknesses:** 1. Wrenchline tech-app resistance — evidence quality: high (recurring, two source types) 2. Wrenchline implementation pain — evidence quality: medium (recurring but review-site only, and reviewers skew negative) - **Assumptions to validate in real interviews:** 1. The quote delay is caused by data re-entry (not by pricing judgment, which software can't fix) 2. Techs actually influence purchase/renewal decisions the way app-store anger implies 3. The cash-flow thread generalizes beyond owner-operators --- ## Why this example works - **Theme names contain no features.** "Quote the job before leaving the driveway" — not "quote builder." The need framing leaves discovery room for solutions the reviews never imagined (voice quoting? photo-to-line-items?). - **Each source's skew is named and *used*.** App stores skew toward technician update-anger — and that's exactly why they're the one channel where the tech, not the buyer, speaks. Bias notes aren't disclaimers; they're reading instructions. - **Frequency honesty changed a conclusion.** The cash-flow theme is vivid but concentrated in one mega-thread, so the payments hypothesis ships at *low* confidence — one articulate thread is not a theme. That's the discipline the Common Pitfalls warn about, applied. - **The output lands as hypotheses, not verdicts.** The decision ("is quoting the right lead?") gets strong support, but the last section routes everything to real interviews — the bridge from competitive intelligence to discovery that this skill exists to build.