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    Voice of Customer Intelligence OS

    1

    Turn interviews, reviews, calls, and support conversations into evidence-traced messaging and offer decisions.

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    Voice of Customer Intelligence OS

    Voice of Customer Intelligence OS

    Example session with this skill installed

    Analyze this six-source sample for a project-management SaaS:
    S1 interview: "I spend Monday morning rebuilding the same status report."
    S2 support ticket: "Our executives won't log in; I need a PDF."
    S3 sales call: "Can it prove where every number came from?"
    S4 interview: "Setup took too long, so the team went back to spreadsheets."
    S5 review: "The dashboard is clean, but client exports are too basic."
    S6 sales call: "We need SSO before procurement will approve it."
    Build a VOC insight pack without treating this small sample as market prevalence.

    • Read your context and instructions
    • Compiled the voice of customer
    • Generated the data export

    Voice of Customer insight pack

    Sample boundary: This analysis covers six qualitative sources. It identifies signals and hypotheses; it does not estimate market prevalence or statistical demand.

    ThemeEvidenceSource diversityConfidence
    Executive/client-ready reportingS2 needs a PDF; S5 says exports are too basicSupport + reviewMedium
    Repetitive status workS1 rebuilds the same report every MondayOne interviewLow
    Traceability of numbersS3 asks where every number came fromOne sales callLow
    Adoption frictionS4 returned to spreadsheets after slow setupOne interviewLow
    Enterprise procurementS6 requires SSO for approvalOne sales callLow

    Buyer-language bank

    • “I spend Monday morning rebuilding the same status report.” — repeated-work pain, S1.
    • “Our executives won't log in; I need a PDF.” — stakeholder-access constraint, S2.
    • “Can it prove where every number came from?” — trust and auditability requirement, S3.
    • “Setup took too long” — time-to-value objection, S4.
    • “Client exports are too basic.” — external-deliverable gap, S5.
    • “We need SSO before procurement will approve it.” — enterprise gate, S6.

    Messaging hypotheses

    Primary: Client-ready reports with traceable numbers, without rebuilding updates by hand. Support: S1, S2, S3, S5. Confidence: Medium.
    2.

    Adoption: Reach the first useful report before the team falls back to spreadsheets. Support: S4. Confidence: Low.
    3. Enterprise: Reporting workflows that are ready for procurement requirements. Support: S6. Confidence: Low.

    Objection and proof map

    ObjectionProof neededCurrent evidence gap
    Setup may take too longTime-to-first-report demonstrationOnly one setup-friction source
    Exports may not satisfy clientsSample executive PDF and configurable exportNo detail on required export fields
    Numbers may be hard to trustVisible source lineage for every metricNo usability evidence for audit trails
    Procurement may block adoptionClear SSO/security documentationProcurement context appears once

    Offer opportunities

    Executive Reporting Sprint: a guided setup that produces a traceable executive PDF quickly. Validate with S1, S2, S3, and S5-type buyers before packaging.

    Migration Confidence Review: map setup steps, likely delays, and spreadsheet fallback risks. Validate with at least five recent evaluators.

    Contradictions and unknowns

    No direct contradictions appear in this small sample. Unknowns include company size, role, buying stage, export requirements, acceptable setup time, and whether SSO is common outside enterprise deals.

    Validation backlog

    Interview 8–10 buyers across agency, mid-market, and enterprise contexts. Ask for the last status report they created, who consumed it, how long it took, what proof was challenged, what blocked setup, and which procurement controls were mandatory. Keep every new claim linked to a source ID.

    voice-of-customer-intelligence-os.csv

    CSV · data export

    Generated

    Example file from a real run - the skill writes it into your workspace.

    Connects securely to your tools. The creator never sees your data.

    What you get

    Build a language bank of direct buyer quotes for high-conversion copywriting.Map the buyer journey from initial trigger to product adoption signals.Extract an objection taxonomy from sales calls to improve closing rates.Develop evidence-based customer segments rooted in behavior, not demographics.

    About this skill

    The problem

    Strategists often rely on gut feel or generic personas because manual analysis of raw customer transcripts, reviews, and survey data is slow and prone to bias. It is difficult to transform hundreds of scattered data points into actionable messaging without losing the original buyer's voice.

    What it does

    • Synthesizes transcripts, reviews, and survey data into evidence-traced buyer language and segments.
    • Extracts atomic units of evidence including triggers, pain points, objections, and desired outcomes.
    • Maps the buyer journey from initial trigger through to retention signals based on real qualitative data.
    • Generates a language bank and objection taxonomy using direct quotes and specific buyer phrasing.
    • Identifies contradictions and unanswered questions to prevent overconfidence in narrow data sets.

    Why this beats prompting it yourself

    General prompts often hallucinate personas or fabricate market demand when data is thin. This skill enforces a strict evidence-ledger methodology that distinguishes between direct quotes and analyst interpretation, ensuring every recommendation cites specific source IDs and maintains a clear audit trail.

    Use cases

    • Synthesizing dozens of sales call transcripts into a high-converting message architecture.
    • Auditing product reviews to identify specific workarounds and unmet feature needs.
    • Building evidence-based segment cards for product marketing teams.
    • Developing sales talk tracks and proof hierarchies grounded in actual customer objections.

    Known limitations

    Does not perform quantitative market sizing or statistical prevalence analysis. Requires raw qualitative data inputs to function; it will not fabricate insights from zero data.

    How to install

    Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.

    ~30 seconds
    1. 1

      Download the ZIP

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    2. 2

      Unzip into your skills folder

      Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.

    3. 3

      Ask your agent to use it

      Restart the agent if it was already running. It picks the skill up automatically - no config needed.

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