Take raw customer inputs — interview transcripts, survey responses, Slack quotes, support tickets, review excerpts — and generate a structured case study draft with problem/solution/result narrative, pull-quotes, metric callouts, and multi-format outputs (full case study, one-pager, social proof snippet, sales deck slide). Pure reasoning skill. Use when a product marketing team has customer signal but no time to write the story.
npx gooseworks install --all # then, in Claude Code, Cursor, or Codex: /gooseworks use the customer-story-builder skill
Turn raw customer signal into a polished case study — plus every derivative format you need. One input (messy transcript or quote), all outputs (case study, one-pager, social snippet, deck slide).
Core principle: The best customer stories already exist in your support tickets, Slack channels, and call recordings. You just need to extract and structure them.
From the raw inputs, identify and extract:
Pull the 3-5 strongest verbatim quotes from the raw input:
# [Headline: Outcome-driven, not product-driven]
*[Subhead: Customer name + one-line result]*
---
## About [Customer]
[2-3 sentences: company, industry, size, what they do]
## The Challenge
[2-3 paragraphs: What was the problem? Why did it matter? What had they tried?]
> "[Problem quote]"
> — [Name], [Title] at [Company]
## Why [Your Product]
[1-2 paragraphs: How did they find you? What made them choose you?]
## The Solution
[2-3 paragraphs: How did they use the product? Which capabilities mattered most?]
> "[Solution/experience quote]"
## The Results
[Results summary with metric callouts]
### Key Metrics
- **[Metric 1]:** [Number + context]
- **[Metric 2]:** [Number + context]
- **[Metric 3]:** [Number + context]
> "[Result quote]"
## What's Next
[1 paragraph: Future plans, expansion, what they're excited about]
---
**Industry:** [X] | **Company size:** [X] | **Use case:** [X] | **Product:** [X]# [Customer Name]: [Headline Result]
**Challenge:** [2 sentences]
**Solution:** [2 sentences — what they use and how]
**Results:**
- [Metric 1]
- [Metric 2]
- [Metric 3]
> "[Hero quote]"
> — [Name], [Title]
[CTA: Learn more / Request a demo]For website testimonial section:
"[Short, punchy quote — max 2 sentences]"
— [Name], [Title] at [Company]
[Result: X% improvement in Y]For LinkedIn post:
[Customer Name] just shared their results:
→ [Metric 1]
→ [Metric 2]
→ [Metric 3]
"[Quote]"
Here's their story: [link]For cold email insert:
[Company in their industry] saw [key metric] after switching to [Product].
"[Short quote about the result]" — [Name], [Title]Slide title: "[Customer] — [Key Result]"
Left side:
- Challenge: [1 line]
- Solution: [1 line]
- Result: [1 line with metric]
Right side:
> "[Hero quote]"
— [Name], [Title]
[Customer logo]For website or marketing collateral:
[BIG NUMBER]
[Label — e.g., "hours saved per week"]
— [Customer Name]Generate 2-3 of these from the strongest metrics.
Before finalizing, verify:
Save all assets to clients/<client-name>/product-marketing/customer-stories/[customer-slug]/:
case-study-full.md — Complete case studyone-pager.md — Sales leave-behindsocial-snippets.md — All social proof formatsslide-content.md — Deck slide contentraw-inputs.md — Original source material (for reference)| Component | Cost |
|---|---|
| All story generation | Free (LLM reasoning) |
| Total | Free |
None. Pure reasoning skill. Takes raw text input and produces structured outputs.
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Turn TikTok, Instagram, YouTube, Facebook, X, LinkedIn, Reddit, or Rumble transcripts into timestamped hooks, claims, objections, proof, calls to action, sponsorship signals, and reusable content atoms. Use directly for transcript analysis or as support for creator, competitor, trend, demand, and repurposing work.
Produce a decision-ready brief of current brand, product, category, and competitor conversations across social platforms, including sentiment drivers, questions, risks, and growth opportunities.