case-study-writing

case-study-writing

Case Study Writing

Create compelling B2B case studies with research and visuals via inference.sh CLI.

Quick Start

Requires inference.sh CLI (infsh). Install instructions

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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