case-study-plan
# ClaudeWave: case-study-plan The case-study-plan skill generates a comprehensive blueprint for developing marketing case studies and success stories. It collects client engagement details, challenges, solutions, and measurable results, then produces an interview framework, data visualization strategy, multiple format variations (PDF, web pages, presentations, video testimonials), and distribution recommendations. Use this skill when building portfolio pieces, sales enablement content, or client testimonial-based proof points that demonstrate tangible business outcomes and credibility to prospective customers.
git clone --depth 1 https://github.com/indranilbanerjee/digital-marketing-pro /tmp/case-study-plan && cp -r /tmp/case-study-plan/skills/case-study-plan ~/.claude/skills/case-study-planSKILL.md
# /digital-marketing-pro:case-study-plan
## Purpose
Generate a structured case study creation plan with interview framework, data visualization approach, format variations, and distribution strategy. Produces a complete blueprint for building compelling proof-of-results content that drives sales enablement and builds credibility.
## Input Required
The user must provide (or will be prompted for):
- **Client or project to feature**: The specific client engagement, campaign, or project that will be showcased
- **Challenge or problem addressed**: The business problem, market pressure, or growth obstacle the client was facing before the engagement
- **Solution implemented**: The services, campaigns, strategies, or tools deployed to address the challenge
- **Results achieved**: Quantitative outcomes (revenue lift, traffic growth, conversion improvement, cost reduction) and qualitative outcomes (brand perception, team capability, process improvement)
- **Timeline of engagement**: Duration of the project or campaign — start date, key milestones, and current status
- **Permission status**: Whether the client has approved public use of their name, data, and story — or if anonymization is required
- **Target audience for the case study**: Who will read or watch it — prospects in the same industry, C-suite decision-makers, marketing managers, procurement teams, or general audience
- **Desired formats**: Which output formats are needed — PDF white paper, website page, presentation deck, video testimonial, social media snippets, or sales one-pager
- **Industry vertical**: The client's industry for contextual benchmarking and relevance targeting
- **Competitive context**: What alternatives the client considered and why they chose this approach
## Process
1. **Load brand context**: Read `~/.claude-marketing/brands/_active-brand.json` for the active slug, then load `~/.claude-marketing/brands/{slug}/profile.json`. Apply brand voice, compliance rules for target markets (`skills/context-engine/compliance-rules.md`), and industry context. **Also check for guidelines** at `~/.claude-marketing/brands/{slug}/guidelines/_manifest.json` — if present, load restrictions and relevant category files. Check for custom templates at `~/.claude-marketing/brands/{slug}/templates/`. Check for agency SOPs at `~/.claude-marketing/sops/`. If no brand exists, ask: "Set up a brand first (/digital-marketing-pro:brand-setup)?" — or proceed with defaults.
2. **Structure the CSR narrative**: Build the Challenge-Solution-Results framework with sub-sections — situation overview, specific pain points, goals at project start, strategic approach, tactical execution, implementation timeline, quantitative results, qualitative impact, and future outlook. Identify the emotional arc that makes the story compelling, not just informative.
3. **Develop client interview questions**: Create 15-20 interview questions organized by section — background and context (company size, industry pressures, previous attempts), challenge deep-dive (symptoms, root causes, business impact of inaction), solution experience (selection criteria, onboarding, collaboration quality), results and impact (measurable outcomes, unexpected benefits, team reaction), and forward-looking (ongoing plans, what they would tell peers).
4. **Plan internal team interview questions**: Draft 10 questions for internal team members who worked on the engagement — strategic rationale, technical approach, challenges encountered during delivery, key turning points, and lessons learned that could inform future engagements.
5. **Identify data points and visualizations needed**: Map every quantitative result to a visualization type — before/after bar charts, timeline growth curves, funnel improvement diagrams, ROI waterfall charts, and comparison tables. Specify which data needs to be collected, verified, and approved by the client before publication.
6. **Design format variations**: Create specifications for each requested output format — PDF white paper (4-6 pages, designed layout with pull quotes and charts), web page (SEO-optimized with structured data markup), presentation deck (8-12 slides for sales meetings), video testimonial script (2-3 minute interview-based script outline), social media snippets (pull quotes, stat cards, carousel posts), and sales one-pager (front-and-back summary for leave-behinds).
7. **Create distribution strategy**: Plan where and how the case study will be published and promoted — website case study library, sales enablement materials, email nurture sequences, social media campaigns, PR outreach, paid promotion, conference presentations, and partner co-marketing opportunities.
8. **Build approval workflow and permission checklist**: Define the full approval process — internal review (legal, marketing, account team), client review (point of contact, legal, executive sign-off), data accuracy verification, quote approval, logo and brand usage permission, and timeline for each review stage.
9. **Write draft executive summary**: Compose a 150-200 word executive summary that captures the full story arc — who the client is, what they faced, what was done, and what resulted. This summary serves as the foundation for all format variations and distribution copy.
10. **Plan visual assets needed**: Specify all visual elements required — client logo (with usage permissions), data visualization charts, photography (team photos, office shots, product images), branded design templates, infographic elements, pull quote cards, and video b-roll if applicable.
## Output
A structured case study creation plan containing:
- **CSR narrative framework** — Challenge-Solution-Results structure with detailed sub-sections, emotional arc mapping, and story flow outline
- **Client interview question set** — 15-20 questions organized by narrative section (background, challenge, solution, results, forward-looking) with follow-up prompts
- **Internal team interview questions** — 1Design a statistically rigorous A/B or multivariate test plan — If/Then/Because hypothesis, control and variant specs, required sample size per variant (absolute vs relative MDE via sample-size-calculator.py), test duration, guardrail metrics, stopping rules, and go/no-go decision criteria. Triggers on \"/digital-marketing-pro:ab-test-plan\", \"set up an A/B test\", \"how long should my test run\", \"calculate sample size for an experiment\", \"is this test result significant\". Reads the brand profile and past campaign-tracker results to avoid re-testing validated hypotheses; finished tests are evaluated with significance-tester.py by the cro-specialist agent.
Generate 3-5 ad copy variations per platform — headlines, descriptions, and CTAs formatted to Google, Meta, LinkedIn, TikTok, X, and Pinterest specs — each scored 1-10 with policy-compliance flags, A/B testing groupings, and a message-match check against the landing page. Triggers on \"/digital-marketing-pro:ad-creative\", \"write ad copy for Meta\", \"give me RSA headline variations\", \"we need LinkedIn ad copy\", \"draft TikTok ad creative\". Reads the brand profile, guidelines, and compliance rules; routes video ad scripts to /digital-marketing-pro:video-script and gates AI-generated visuals for EU campaigns through /digital-marketing-pro:c2pa-metadata and /digital-marketing-pro:check.
Walk through adding a custom MCP server integration to the plugin — searches npm for an existing MCP package (or scaffolds a custom server from the plugin's guide), generates the exact .mcp.json entry, sets up environment-variable credentials, tests connectivity, and documents the tools the new server exposes. Triggers on \"/digital-marketing-pro:add-integration\", \"connect Ahrefs to the plugin\", \"add a new MCP server\", \"integrate our internal API\", \"hook up Stripe data\". Reads the brand profile and agency credential profiles at ~/.claude-marketing/credentials/ to map client-specific keys; custom builds follow skills/context-engine/custom-mcp-guide.md.
Audit how a brand appears across the 6 canonical AI answer surfaces — ChatGPT, Perplexity, Google AI Mode, AI Overviews, Gemini, Copilot — probing 10-25 queries into a numbered output bundle with per-platform visibility scorecards, citation-accuracy checks, a competitor matrix, content gaps, and an optimization playbook behind a four-gate quality scorecard. Triggers on \"/digital-marketing-pro:aeo-audit\", \"does ChatGPT know about our brand\", \"check our AI search visibility\", \"how does Perplexity describe us\", \"are we showing up in AI Overviews\". Reads the brand profile; reconciles probes against GSC actuals via /digital-marketing-pro:gsc-ai-performance and defines the AI-visibility scoring standard reused by geo-monitor and share-of-voice.
Strategy module for Answer Engine / Generative Engine Optimization — audits AI visibility, restructures content for citation, runs entity-consistency checks across Knowledge Graph, Wikidata, Wikipedia, Crunchbase, and LinkedIn, and produces JSON-LD schema specs, monitoring frameworks, and a 90-day LLM content strategy. Triggers on \"/digital-marketing-pro:aeo-geo\", \"how do we get cited by AI\", \"optimize for AI Overviews\", \"fix our entity consistency\", \"do we need llms.txt\". Reads the brand profile, compliance rules, and industry benchmarks; its measurement counterpart is /digital-marketing-pro:aeo-audit, with GSC actuals via /digital-marketing-pro:gsc-ai-performance.
Generate a portfolio-level dashboard across ALL client brands — per-client RAG health scores, campaign activity, budget pacing, aggregate KPIs, team utilization, pending approvals, upcoming deadlines, and an alerts panel — built for agency standups and weekly reviews. Triggers on \"/digital-marketing-pro:agency-dashboard\", \"how are all our clients doing\", \"portfolio health check\", \"budget pacing across accounts\", \"which accounts are at risk\". Enumerates every brand under ~/.claude-marketing/brands/ and pulls data via campaign-tracker.py, execution-tracker.py, and team-manager.py; drill into a single client with /digital-marketing-pro:performance-report or /digital-marketing-pro:client-report.
Invoke when the user needs to manage multiple client brands, view portfolio-level dashboards, generate client reports, manage SOPs, switch credential profiles, assign team tasks, configure regions, or generate executive summaries. Triggers on requests involving multi-client management, agency workflows, client onboarding, or portfolio oversight.
Invoke when the user needs help with marketing measurement, KPI definition, dashboard design, attribution reporting, performance analysis, competitive benchmarking, or translating data into marketing decisions. Triggers on requests involving metrics, reporting, analytics setup, or data interpretation.