Skill: okaris/case-study-writing (version 0.1.5)

--- name: case-study-writing description: "B2B case study writing with STAR framework, data visualization, and research. Covers structure, customer quotes, metrics presentation, and distribution formats. Use for: customer success stories, portfolio pieces, sales enablement, marketing content. Triggers: case study, customer story, success story, b2b case study, client testimonial, customer case study, portfolio case study, use case, customer win, results story" allowed-tools: Bash(infsh *) --- # Case Study Writing Create compelling B2B case studies with research and visuals via [inference.sh](https://inference.sh) CLI. ## Quick Start ```bash curl -fsSL https://cli.inference.sh | sh && infsh login # Research the customer's industry infsh app run tavily/search-assistant --input '{ "query": "SaaS customer onboarding challenges 2024 statistics" }' ``` > **Install note:** The [install script](https://cli.inference.sh) only detects your OS/architecture, downloads the matching binary from `dist.inference.sh`, and verifies its SHA-256 checksum. No elevated permissions or background processes. [Manual install & verification](https://dist.inference.sh/cli/checksums.txt) available. ## 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 ```bash # 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 ```markdown > "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 ```bash # 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 ```bash npx skills add inference-sh/skills@web-search npx skills add inference-sh/skills@prompt-engineering ``` Browse all apps: `infsh app list`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)