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Voice Of Customer

CommunityPopular
cbrock84
voice-of-customer

Builds the loop from what customers say to what gets changed — collecting feedback, distinguishing signal from noise, routing it to owners, and closing the loop back to the customer. Use this to set up a feedback program, design or interpret CSAT/NPS, decide what customer feedback deserves action, get product to act on recurring issues, or diagnose why feedback is collected but nothing changes.

Overview

Publishercbrock84
Repositoryheadcount
Skill namevoice-of-customer
Stars
1.6K
Forks
237
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cbrock84 on GitHub. Read the source before you install it.

Installation

Install the Voice Of Customer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cbrock84/headcount.git /tmp/headcount
mkdir -p .claude/skills
cp -r /tmp/headcount/plugins/customer-experience/skills/voice-of-customer .claude/skills/voice-of-customer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Voice Of Customer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Voice Of Customer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Voice Of Customer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Voice of customer

Most feedback programs collect diligently and change nothing. The collection is the easy half; the loop is the whole value.

Sources, weighted honestly

  • Support contacts — the highest-volume and least prompted source, and the most under-used. People contacting you have a real problem nobody asked them about. But the sample is strongly self-selected: it excludes everyone who silently churned, worked around the problem, or would never contact you. Treat it as operational evidence to be normalized per active account and triangulated against churn and behavioral data — never as representative of the customer base.
  • Churn and loss reasons — the most valuable and most under-sampled. People leaving have no reason to be polite.
  • Interviews — depth, small n, best for understanding why something in the data is happening.
  • Surveys — breadth, and only meaningful once you know what to ask.
  • Public reviews and forums — biased toward extremes, useful for what people say when you are not in the room.

Anything a customer built a workaround for outranks anything they merely said in a survey.

On CSAT and NPS

Both are useful as trends and misleading as targets. The moment a team is measured on a score, the score improves faster than the experience does — asking at the favorable moment, coaching for the rating, excluding difficult segments.

Treat the score as a prompt for the free-text answer, which is where the information is. Segment before concluding: an overall score is an average of experiences that have nothing in common.

Never target a number without also watching the behavior it is supposed to predict.

Turning feedback into change

The failure is not collection, it is triage. Feedback needs:

  • Categorization against a stable taxonomy, so volume per cause is countable across periods.
  • Quantification. "Several customers mentioned" loses every argument. "Eighty-one contacts this quarter, four percent of active accounts, twelve of them on enterprise plans" wins.
  • A named owner per theme, outside the feedback function. A theme owned by the team collecting it goes nowhere.
  • A standing review where product, support, and success look at the same list together.

Distinguish requests from problems. Customers describe solutions; your job is to recover the problem underneath, because the request is often not the best fix for it.

Closing the loop

Tell the customer what changed and that they prompted it. Almost nobody does this, which is exactly why it works — it converts a complainer into someone who reports the next issue instead of leaving.

Also close it internally: show the support team what shipped because of what they escalated, or they stop escalating.

Tooling

Survey and feedback: Qualtrics, Medallia, Delighted, SurveyMonkey, Typeform, and similar.

In-product feedback and micro-surveys: Pendo, Sprig, Chameleon, and similar — usually a better signal than emailed surveys because they reach people mid-task rather than after the fact.

Aggregating unstructured feedback across tickets, calls and reviews is where the platforms differ most. Whatever collects it, the theme has to be traceable back to individual verbatims, or nobody downstream will believe the count.

Never

  • Report themes without volume.
  • Let one loud enterprise account set the roadmap without checking how widely the problem is shared.
  • Run a program with no mechanism for anything to change as a result. That is a survey habit, not a feedback loop.

Frequently asked questions

What does the Voice Of Customer AI skill do?

Builds the loop from what customers say to what gets changed — collecting feedback, distinguishing signal from noise, routing it to owners, and closing the loop back to the customer. Use this to set up a feedback program, design or interpret CSAT/NPS, decide what customer feedback deserves action, get product to act on recurring issues, or diagnose why feedback is collected but nothing changes.

Why use Voice Of Customer on TypingMind?

Because you install it once and use it with any model. Voice Of Customer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Voice Of Customer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cbrock84/headcount/tree/main/plugins/customer-experience/skills/voice-of-customer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Voice Of Customer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Voice Of Customer?

As many as you like. As long as a model supports skills, you can use Voice Of Customer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Voice Of Customer AI skill free?

Yes. It is published on GitHub by cbrock84 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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