Insight / MOD.02 / v2.0.0

China Voice of Customer Analysis Template

Use a China voice of customer analysis template to preserve source language, code evidence consistently, compare segments and platforms, and turn themes into testable actions.

Chinese interview synthesisReview analysisSocial listening synthesisDemand clustering

MODULE STATUS READY TO INSTALL

VERSION: 2.0.0
UPDATED: 2026-08-01
LICENSE: MIT
FILES: 04

INSTALL / voice-of-customer-synthesisREADY

npx skills add fffffrost/market-skills --skill voice-of-customer-synthesis

CHINA VOICE OF CUSTOMER ANALYSIS

Preserve the customer's words before you compress the pattern.

VOC synthesis becomes unreliable when quotes lose their source, loud channels stand in for the market, or themes are named before coding. Keep original language and context attached, compare patterns across segments, and show how much evidence supports each decision.

01 / DECISION

Define the decision

State what the analysis must inform, the target segment, time window, included sources, exclusions, and sampling limits.

Which decision will this evidence change?

02 / SOURCE

Preserve source context

Retain original Chinese wording, date, channel, segment, journey stage, consent or access status, and stable source reference.

Can a reviewer return to the original context?

03 / CODE

Apply a consistent codebook

Code jobs, triggers, pains, desired outcomes, objections, alternatives, language, intensity, and evidence quality.

Would another reviewer assign the same code?

04 / COMPARE

Compare before merging

Separate roles, regions, customer stages, channels, and source types before describing an overall pattern.

Where does the pattern hold, and where does it break?

05 / THEME

Build evidence-backed themes

Attach representative quotes, counterexamples, frequency, intensity, coverage, confidence, and material unknowns.

Does each theme have support and a visible limit?

06 / ACTION

Convert insight into a test

Map themes to messaging, product, content, sales, or research actions with owners and validation signals.

What can the team test instead of merely believing?

TEMPLATE / COPY AND COMPLETEAn evidence ledger for customer language and decisions

CHINA VOICE OF CUSTOMER ANALYSIS TEMPLATE

DECISION AND SAMPLE
Decision to inform:
Priority segment:
Time window:
Included sources:
Exclusions:
Known sampling bias:

SOURCE RECORD
Source ID | Original wording | Date | Channel | Segment | Journey stage | Context / access

CODEBOOK
Job / desired progress:
Trigger:
Pain / friction:
Desired outcome:
Objection / risk:
Alternative:
Customer language:
Intensity / evidence quality:

THEME TABLE
Theme | Supporting sources | Counterexample | Coverage | Confidence | Unknown

SEGMENT COMPARISON
Segment / region / stage | Shared pattern | Difference | Implication

ACTION MAP
Theme | Messaging / product / sales / research action | Owner | Test | Signal

REVIEW
Reviewer disagreement:
Missing voices:
Next research need:
Decision date:

SYNTHETIC VOC TRACE

Four safeguards against turning comments into folklore.

This is a research pattern, not a representative China consumer finding. Production analysis must disclose sample and access limits.

SOURCEQuote plus context

Keep original wording, channel, date, role, and journey stage attached to every excerpt.

SAMPLECoverage without false representativeness

State which voices are overrepresented, absent, or inaccessible before generalizing.

THEMEPattern plus counterexample

Show frequency, intensity, coverage, and contradictory evidence instead of selecting only vivid quotes.

ACTIONInsight with a test

Turn the theme into a message, research, product, or sales hypothesis with a decision owner.

MINIMUM INPUT

Chinese research materials
Source metadata
Audience segments
Decision question

OUTPUT

Evidence-backed themes
Verbatim quotes
Segment differences
Action matrix

BOUNDARY / NOT FOR THIS

Know where the workflow must stop.

Cannot generalize a small or convenience sample to the China market
Does not replace quantitative research or continuous social listening
Must not process personal data without an appropriate basis

FAILURE MODES

These conditions distort the result.

Translation removes the original customer wording before analysis
Platform audience and customer stage are mixed into one theme
Findings are counted without preserving source and sampling boundaries

Report a skill problem ↗

EXECUTION PROTOCOL

How the skill works

01Define the China decision
02Preserve source and language context
03Code observations
04Compare platform and segment patterns
05Build evidence-backed insights
06Convert insights into tests

PACKAGE CONTENTS

Inspect the source before installing.

Instructions, templates, compatibility, and dependencies remain in one open directory.

├─SKILL.md
├─agents/openai.yaml
├─listing.yaml
├─references/voc-template.md

View source on GitHub ↗