customer-language-bank

Name: customer-language-bank
Availability: InStock
Author: nugiwabot

Extract recurring buyer phrases from reviews, tickets, and calls and compare them against current messaging.

Updated Aug 28, 2026

Search Tags:#messaging #personas #positioning #copywriting #customer research #voice of customer #review analysis

Ready to run

npx skills add https://github.com/nugiwabot/marketing-branding-selling-ads-skills --skill customer-language-bank-nugiwabot

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: customer-language-bank
Source: https://github.com/nugiwabot/marketing-branding-selling-ads-skills/tree/main/.agents/skills/customer-language-bank
Command: npx skills add https://github.com/nugiwabot/marketing-branding-selling-ads-skills --skill customer-language-bank-nugiwabot

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Marketing copy is often written in internal company language that does not match how buyers actually describe their problems and desired outcomes. This Skill reads large volumes of voice-of-customer material and surfaces the exact words customers use, so messaging can be aligned with real market language instead of assumptions. ## Core Features & Use Cases - Bulk Voice-of-Customer Analysis: Reads hundreds of reviews, support tickets, and call snippets in one pass and clusters recurring language into frequency-ranked themes. - Messaging Gap Comparison: Maps buyer vocabulary against your current messaging to show where your words and the market's words diverge. - Persona Signals: Identifies language differences by segment or role when the source material supports it. - Use Case: Before a website copy refresh, feed in G2 reviews, support tickets, and sales call notes to get a swap list of phrases your copy should adopt to sound like your customers. ## Quick Start Analyze our G2 reviews and support tickets to build a customer language bank and show where our homepage messaging uses different words than our buyers.

Frequently Asked Questions about customer-language-bank

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I analyze customer reviews to find the words buyers actually use?▼

Gather reviews, support tickets, and call snippets, then read them in bulk to extract recurring phrases for the problem, trigger, desired outcome, and product descriptions. Cluster these into themes ranked by frequency, keeping raw quotes with their sources.

What is a voice of customer analysis used for in marketing?▼

Voice of customer analysis reveals the exact language buyers use for their problems and desired outcomes. Marketers use it to refresh messaging, write copy that matches market vocabulary, and build personas grounded in real customer phrasing.

What sources should I include in a customer language analysis?▼

Include product reviews from G2, Capterra, app stores, or Trustpilot, support tickets and chat logs, sales and onboarding call snippets, community posts, survey free-text, churn reasons, and social mentions when available.

Can I run voice of customer analysis if I have too many reviews to read at once?▼

Yes. Process the material in batches of a few hundred items, produce a themed phrase list per batch, then merge and re-rank the lists in a final pass to get the overall frequency ranking.

Why should customer quotes not be paraphrased in a language bank?▼

Paraphrasing converts buyer language into marketing language, which defeats the purpose. Every phrase must be a real quote with its source noted, and frequency counts must come from the material or be labeled as estimates.