case-study-writing

B2B case study writing with STAR framework, data visualization, and research. Covers structure, customer quotes, metrics presentation, and distribution…

INSTALLATION
npx skills add https://github.com/inference-sh/skills --skill case-study-writing
Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

$27

The STAR Framework

Every case study follows: Situation -> Task -> Action -> Result

Section

Length

Content

Purpose

Situation

100-150 words

Who the customer is, their context

Set the scene

Task

100-150 words

The specific challenge they faced

Create empathy

Action

200-300 words

What solution was implemented, how

Show your product

Result

100-200 words

Measurable outcomes, before/after

Prove value

Total: 800-1200 words. Longer loses readers. Shorter lacks credibility.

Structure Template

1. Headline (Lead with the Result)

❌ "How Company X Uses Our Product"

❌ "Company X Case Study"

✅ "How Company X Reduced Onboarding Time by 60% with [Product]"

✅ "Company X Grew Revenue 340% in 6 Months Using [Product]"

The headline should be specific, quantified, and state the outcome.

2. Snapshot Box

Place at the top for skimmers:

┌─────────────────────────────────────┐

│ Company: Acme Corp                  │

│ Industry: E-commerce                │

│ Size: 200 employees                 │

│ Challenge: Manual order processing  │

│ Result: 60% faster fulfillment      │

│ Product: [Your Product]             │

└─────────────────────────────────────┘

3. Situation

  • Who is the customer (industry, size, location)
  • What relevant context existed before the problem
  • 1-2 sentences of company background

4. Task / Challenge

  • Quantify the pain: "spending 40 hours/week on manual data entry" not "had data problems"
  • Show stakes: what would happen if unsolved (lost revenue, churn, missed deadlines)
  • Include a customer quote about the frustration

5. Action / Solution

  • What was implemented (your product/service)
  • Timeline: "deployed in 2 weeks" / "3-month rollout"
  • Key decisions or configurations
  • Why they chose you over alternatives (briefly)
  • 2-3 specific features that addressed the challenge

6. Results

  • Before/after metrics — always quantified
  • Timeframe — "within 3 months" / "in the first quarter"
  • Unexpected benefits beyond the original goal
  • Customer quote about the outcome

Metrics That Matter

How to Present Numbers

❌ "Improved efficiency"

❌ "Saved time"

❌ "Better results"

✅ "Reduced processing time from 4 hours to 45 minutes (81% decrease)"

✅ "Increased conversion rate from 2.1% to 5.8% (176% improvement)"

✅ "Saved $240,000 annually in operational costs"

Metric Categories

Category

Examples

Time

Hours saved, time-to-completion, deployment speed

Money

Revenue increase, cost reduction, ROI

Efficiency

Throughput, error rate, automation rate

Growth

Users gained, market expansion, feature adoption

Satisfaction

NPS change, retention rate, support tickets reduced

Data Visualization

# Generate a before/after comparison chart

belt app run infsh/python-executor --input '{

  "code": "import matplotlib.pyplot as plt\nimport matplotlib\nmatplotlib.use(\"Agg\")\n\ncategories = [\"Processing Time\", \"Error Rate\", \"Cost per Order\"]\nbefore = [4, 12, 8.50]\nafter = [0.75, 1.5, 2.10]\n\nfig, ax = plt.subplots(figsize=(10, 6))\nx = range(len(categories))\nwidth = 0.35\nax.bar([i - width/2 for i in x], before, width, label=\"Before\", color=\"#ef4444\")\nax.bar([i + width/2 for i in x], after, width, label=\"After\", color=\"#22c55e\")\nax.set_ylabel(\"Value\")\nax.set_xticks(x)\nax.set_xticklabels(categories)\nax.legend()\nax.set_title(\"Impact of Implementation\")\nplt.tight_layout()\nplt.savefig(\"results-chart.png\", dpi=150)\nprint(\"Chart saved\")"

}'

Customer Quotes

What Makes a Good Quote

❌ "We love the product." (vague, could be about anything)

❌ "It's great." (meaningless)

✅ "We went from processing 50 orders a day to 200, without adding a single person to the team."

   — Sarah Chen, VP Operations, Acme Corp

✅ "Before [Product], our team dreaded Monday mornings because of the report backlog.

    Now it's automated and they can focus on actual analysis."

   — Marcus Rodriguez, Head of Analytics, DataCo

Quote Placement

  • 1 quote in the Challenge section — about the frustration/pain
  • 1-2 quotes in the Results section — about the outcome/transformation
  • Always attribute: full name, title, company

Quote Formatting

> "We went from processing 50 orders a day to 200, without adding anyone to the team."

>

> — Sarah Chen, VP Operations, Acme Corp

Research Support

Finding Industry Context

# Industry benchmarks

belt app run tavily/search-assistant --input '{

  "query": "average e-commerce order processing time industry benchmark 2024"

}'

# Competitor landscape

belt app run exa/search --input '{

  "query": "order management automation solutions market overview"

}'

# Supporting statistics

belt app run exa/answer --input '{

  "question": "What percentage of e-commerce businesses still use manual order processing?"

}'

Distribution Formats

Format

Where

Notes

Web page

/customers/ or /case-studies/

Full version, SEO-optimized

PDF

Sales team, email attachment

Designed, downloadable, gated optional

Slide deck

Sales calls, presentations

5-8 slides, visual-heavy

One-pager

Trade shows, quick reference

Snapshot + key metrics + quote

Social post

LinkedIn, Twitter

Key stat + quote + link to full

Video

Website, YouTube

Customer interview or animated

Social Media Snippet

Headline stat + brief context + customer quote + CTA

Example:

"60% faster order processing.

Acme Corp was drowning in manual fulfillment. 4 hours per batch. 12% error rate.

After implementing [Product]: 45 minutes per batch. 1.5% errors.

'We went from 50 orders a day to 200 without adding headcount.' — Sarah Chen, VP Ops

Read the full story → [link]"

Writing Checklist

  • Headline leads with the quantified result
  • Snapshot box with company, industry, challenge, result at top
  • Challenge is quantified, not vague
  • 2-3 specific customer quotes with attribution
  • Before/after metrics with timeframe
  • 800-1200 words total
  • Skimmable (headers, bold, bullet points)
  • Customer approved the final version
  • Visual: at least one chart or before/after comparison

Common Mistakes

Mistake

Problem

Fix

No specific numbers

Reads like marketing fluff

Quantify everything

All about your product

Reads like a sales pitch

Story is about the CUSTOMER

Generic quotes

No credibility

Get specific, attributed quotes

Missing the "before"

No contrast to show impact

Always show the starting point

Too long

Loses reader attention

800-1200 words max

No customer approval

Legal/relationship risk

Always get sign-off

Related Skills

npx skills add inference-sh/skills@web-search

npx skills add inference-sh/skills@prompt-engineering

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