---
id: sm-case-study-writing
name: "case-study-writing"
url: https://skills.yangsir.net/skill/sm-case-study-writing
author: inferen-sh
domain: writing
tags: ["technical-writing", "business-writing", "storytelling", "content-marketing", "customer-success"]
install_count: 6455
rating: 4.50 (258 reviews)
github: https://github.com/inferen-sh/skills
---

# case-study-writing

> 撰写引人入胜的案例研究，通过真实故事展示产品或服务的成功应用，增强客户信任。

**Stats**: 6,455 installs · 4.5/5 (258 reviews)

## Before / After 对比

### 高效撰写专业案例研究报告

## Readme

# case-study-writing

# Case Study Writing

Create compelling B2B case studies with research and visuals via [inference.sh](https://inference.sh) CLI.

## Quick Start

Requires inference.sh CLI (`infsh`). [Install instructions](https://raw.githubusercontent.com/inference-sh/skills/refs/heads/main/cli-install.md)

```
infsh login

# Research the customer's industry
infsh app run tavily/search-assistant --input '{
  "query": "SaaS customer onboarding challenges 2024 statistics"
}'

```

## 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
infsh 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
infsh app run tavily/search-assistant --input '{
  "query": "average e-commerce order processing time industry benchmark 2024"
}'

# Competitor landscape
infsh app run exa/search --input '{
  "query": "order management automation solutions market overview"
}'

# Supporting statistics
infsh 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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---
*Source: https://skills.yangsir.net/skill/sm-case-study-writing*
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