Board meeting in 2 hours. Your CMO asks: "What's our competitive advantage? Why are we losing to Competitor X?"
You panic-Google. Read 10 articles. Still confused. Clock ticking.
Enter ChatGPT: your instant business analyst — but only if you know how to extract strategic insights, not generic business babble.
This module shows you how Fortune 500 consultants, VCs, and executives use ChatGPT for $500/hour-quality analysis in minutes.
💡 In this module, you'll master:
- Market research & competitive analysis
- Strategic frameworks (SWOT, Porter's 5 Forces, BCG Matrix)
- Data interpretation & insight generation
- Business model analysis & validation
- Executive reporting & presentations
- Decision-making frameworks
📊 Use Case 1: Market Research
Comprehensive Market Analysis Prompt
Act as a market research analyst with 10 years of experience.
Analyze the market for [YOUR PRODUCT/SERVICE]:
Product: AI-powered meal planning app for busy professionals
Target market: US, 25-45 years old, $75K+ household income
Provide:
1. Market size & growth
- TAM (Total Addressable Market)
- Current market size + 5-year growth projections
- Key growth drivers
2. Customer segments
- 3-4 distinct customer personas
- Pain points for each
- Willingness to pay
3. Competitive landscape
- Top 5 competitors
- Their strengths/weaknesses
- Market share estimates
- Pricing strategies
4. Market trends
- 3-5 major trends shaping this space
- Opportunities these create
5. Barriers to entry
- What makes this market hard/easy to enter?
6. Recommendations
- Market positioning strategy
- Which segment to target first
- Key differentiators needed
Format: Executive summary + detailed sections
Use data/statistics where available (with caveats if estimated)
⚠️ Critical reminder: ChatGPT's market data (sizes, growth rates, statistics) may be outdated or estimated. Always verify key numbers with:
- Industry reports (Gartner, Forrester, Statista)
- Government data (census, trade associations)
- Company financials (public companies, 10-Ks)
- Recent news articles (last 6-12 months)
Use ChatGPT for: Structure, framework, analysis approach. Fill with real data yourself.
⚔️ Use Case 2: Competitive Analysis
Deep Competitor Intelligence
Act as a competitive intelligence analyst.
My company: [YOUR COMPANY - brief description]
Competitor: [COMPETITOR NAME]
Analyze:
1. Business model
- How do they make money?
- Revenue streams breakdown
- Unit economics (if public)
2. Product/Service offering
- Core features
- What do they do better than us?
- What do we do better?
3. Go-to-market strategy
- Customer acquisition channels
- Marketing approach
- Sales process
- Pricing strategy
4. Strengths (what makes them formidable)
5. Weaknesses (vulnerabilities we can exploit)
6. Recent moves
- Product launches
- Funding rounds
- Key hires
- Partnerships
7. Predicted next moves (based on patterns)
8. Counter-strategies
- How we should respond
- Opportunities to differentiate
Format as briefing doc for executive team
🎯 Pro Tip: Competitive Feature Matrix
Create a feature comparison table:
Companies: Us, [Competitor 1], [Competitor 2], [Competitor 3]
Features to compare:
- [Feature 1]
- [Feature 2]
- [Feature 3]
- [etc.]
For each:
- ✅ Full support
- ⚠️ Partial support
- ❌ Not available
- 🔜 Coming soon
Add row for pricing
Add row for target customer
Add "Winner" column highlighting best-in-class for each feature
🎯 Use Case 3: Strategic Frameworks
Framework 1: SWOT Analysis
Conduct a SWOT analysis for [YOUR COMPANY/PRODUCT]:
Context:
- Company: [Description]
- Industry: [Sector]
- Stage: [Startup/Growth/Mature]
- Recent developments: [Key changes]
Analyze:
STRENGTHS (Internal, Positive)
- What do we do exceptionally well?
- What unique resources/capabilities?
- What advantages vs competitors?
WEAKNESSES (Internal, Negative)
- What needs improvement?
- Where do competitors beat us?
- What resources are we lacking?
OPPORTUNITIES (External, Positive)
- What market trends favor us?
- What gaps can we fill?
- What partnerships/alliances possible?
THREATS (External, Negative)
- What could harm our business?
- What are competitors doing?
- What market shifts worry us?
Then:
- Identify 3 strategic priorities based on this analysis
- Suggest strategies that leverage strengths to capitalize on opportunities
- Recommend how to address critical weaknesses and threats
Framework 2: Porter's Five Forces
Use this to analyze industry attractiveness and competitive intensity
Apply Porter's Five Forces to [YOUR INDUSTRY]:
1. Threat of New Entrants (High/Medium/Low)
- Barriers to entry?
- Capital requirements?
- Brand loyalty?
2. Bargaining Power of Suppliers (High/Medium/Low)
- How many suppliers?
- Can we switch easily?
- Do they have leverage?
3. Bargaining Power of Buyers (High/Medium/Low)
- How price-sensitive are customers?
- Can they easily switch?
- How much do they buy?
4. Threat of Substitutes (High/Medium/Low)
- What alternative solutions exist?
- How close are they to our offering?
5. Industry Rivalry (High/Medium/Low)
- How many competitors?
- Market growth rate?
- Differentiation level?
Conclusion: Is this an attractive industry? Why/why not?
Strategy: How should we position ourselves given these forces?
Framework 3: BCG Growth-Share Matrix
Analyze our product portfolio using BCG Matrix:
Products/Business Units:
1. [Product A] - Revenue: $X, Market growth: Y%, Market share: Z%
2. [Product B] - Revenue: $X, Market growth: Y%, Market share: Z%
3. [Product C] - Revenue: $X, Market growth: Y%, Market share: Z%
Categorize each as:
- ⭐ Stars (High growth, high share) → Invest heavily
- 💰 Cash Cows (Low growth, high share) → Harvest profits
- ❓ Question Marks (High growth, low share) → Invest or divest
- 🐕 Dogs (Low growth, low share) → Consider exit
For each product:
- Classification + reasoning
- Strategic recommendation
- Resource allocation suggestion
Portfolio-level strategy: How should we rebalance?
📈 Use Case 4: Data Interpretation & Insights
Turn Raw Data Into Actionable Insights
Act as a data analyst with business strategy expertise.
Here's our data: [PASTE DATA - can be formatted as table, CSV, or bullet points]
Example:
- Q1 Revenue: $500K (up 15% vs Q4)
- Customer acquisition cost: $120 (up from $95)
- Churn rate: 8% (up from 5%)
- Average deal size: $2,400 (flat)
- Marketing spend: $80K (up 40%)
Analyze:
1. What's the story? (What's actually happening in plain English)
2. Key trends (What's changing and why it matters)
3. Red flags (Concerning patterns requiring immediate attention)
4. Opportunities (Positive signals to double down on)
5. Root cause analysis (Why are we seeing these results?)
6. Recommendations (3-5 specific actions with expected impact)
Format: Executive summary (3 bullets) + detailed analysis + action items
Audience: C-suite executives, non-technical
💡 Specific Data Analysis Prompts
Customer Cohort Analysis
Analyze customer cohort retention:
Cohort data (% retained after N months):
- Jan 2024: M1=90%, M2=75%, M3=65%, M6=50%
- Feb 2024: M1=88%, M2=72%, M3=60%
- Mar 2024: M1=85%, M2=68%
What's the retention pattern?
Is it improving/declining?
At what month do we lose most customers?
What should our retention strategy focus on?
A/B Test Analysis
Analyze A/B test results:
Variant A (Control):
- 10,000 visitors
- 250 conversions (2.5%)
Variant B (New design):
- 10,000 visitors
- 280 conversions (2.8%)
Is this difference statistically significant?
Should we roll out Variant B?
What factors might explain the difference?
What should we test next?
💼 Use Case 5: Business Model Validation
Act as a venture capital analyst evaluating business models.
Business idea: [YOUR IDEA - describe in 2-3 sentences]
Analyze:
1. Revenue model
- How exactly does money flow in?
- Is it scalable?
- Multiple revenue streams possible?
2. Unit economics
- CAC (Customer Acquisition Cost) estimate
- LTV (Lifetime Value) estimate
- LTV:CAC ratio (should be >3:1)
- Payback period
3. Market validation
- Who are the customers? (be specific)
- What pain does this solve? (rate pain level 1-10)
- Why will they pay?
- Market size (TAM/SAM/SOM)
4. Competitive moat
- What prevents competitors from copying?
- Network effects?
- Switching costs?
- Proprietary tech/data?
5. Risk assessment
- Top 3 risks that could kill this
- Mitigation strategies
6. Verdict
- Fundable? (VC perspective)
- Bootstrap-able? (Self-funded perspective)
- Biggest assumptions to validate first
Be brutally honest — I want to know what won't work, not just validation.
📊 Use Case 6: Executive Reporting
Board-Ready Presentations
Transform this information into an executive presentation outline:
Situation: [Describe current state]
Data: [Key metrics/findings]
Goal: [What decision are we driving toward?]
Audience: [Board/C-suite/Investors]
Create:
1. Slide structure (10-15 slides max)
- Each slide: Title + Key points + Visual suggestion
2. Executive summary (first slide)
- 3 bullets that tell the whole story
3. Key message per slide
- One insight per slide
- Data to support it
- "So what?" (why it matters)
4. Recommended flow
- Problem → Analysis → Recommendation → Action plan
5. Appendix slides
- Detailed data for Q&A
Tone: Direct, data-driven, action-oriented
Length: Each slide should be explainable in 60 seconds
📧 Executive Summary Email Template
Write an executive summary email for [TOPIC]:
Format:
Subject: [Decision needed: X] or [FYI: Key insight from Y]
TL;DR (3 bullets max)
- Main finding/recommendation
- Why it matters
- What action is needed
Context (2-3 sentences)
- Why we're looking at this now
Analysis (3-5 key points)
- Each point: Finding + So what?
Recommendation
- Clear course of action
- Expected outcome
- Resources needed
Next steps
- Who does what by when
Length: Under 300 words total
Tone: Confident, concise, assume busy reader
🤔 Use Case 7: Decision-Making Frameworks
Help me make a strategic decision using structured analysis:
Decision: [What you're deciding - e.g., "Should we expand to Europe?"]
Context:
- Current situation: [Brief description]
- Constraints: [Budget, time, resources]
- Stakeholders: [Who cares about this decision?]
Apply these frameworks:
1. Pros & Cons (weighted)
- List all pros (weight each 1-10)
- List all cons (weight each 1-10)
- Calculate weighted score
2. ICE Score (Impact, Confidence, Ease)
- Impact: How big is potential upside? (1-10)
- Confidence: How sure are we? (1-10)
- Ease: How easy to execute? (1-10)
- ICE Score = (Impact × Confidence) / Ease
3. Decision Matrix
- Criteria: [List 4-6 decision criteria]
- Weight each criterion (importance 1-10)
- Score each option against criteria
- Calculate weighted total
4. Regret Minimization
- What will I regret more: doing this and failing, or not doing it at all?
5. Reversibility Test
- Is this decision reversible? (If yes, bias toward action)
6. Pre-Mortem
- Assume we do this and it fails. What went wrong?
Final recommendation: Based on all frameworks, what should we do?
🎯 Hands-On Exercise: Strategic Analysis Project
📝 Complete Business Analysis Challenge
Scenario: You're consulting for a company (real or hypothetical).
Deliverable: Strategic analysis report + presentation
Steps:
- Choose a company/product (your own startup idea, your employer, or public company)
- Market research: Use ChatGPT to outline market size, trends, segments
- Competitive analysis: Analyze top 3 competitors
- SWOT analysis: Internal strengths/weaknesses, external opportunities/threats
- Porter's Five Forces: Industry attractiveness analysis
- Strategic recommendation: Based on above, what should they do?
- Executive presentation: 10-slide deck outline
Reflection:
- How long did this take vs doing manually? (Hint: 80% faster)
🚀 Accelerate Your Strategic Analysis
You've learned the analysis frameworks. Now supercharge them with AI tools built for research, documentation, and presentation:
🧠
Claude Pro - Deep Analysis Assistant
Anthropic | $20/month
Perfect for analysts who need: Analyze entire market research reports, earnings transcripts, and strategy documents. 200K token context = upload full reports and ask complex questions.
💡 Use Case: "Upload competitor's annual report (50 pages) + industry analysis (30 pages). Compare their strategy to ours. What are we missing?" Claude analyzes both documents simultaneously, spots patterns across 80 pages.
- 200K context window: Analyze book-length documents (vs. ChatGPT's 8K-32K)
- Nuanced reasoning: Better at complex strategic questions, trade-off analysis
- Document upload: PDFs, Word docs, spreadsheets—analyze actual business files
- Why analysts love it: Handles multi-source analysis that ChatGPT truncates
📋
Notion AI - Research Hub
Notion Labs | $10/month
Perfect for analysts who need: Organize your strategic analysis project—market research notes, competitor profiles, SWOT matrices, and action items—all in one AI-powered workspace.
💡 Use Case: Create "Market Analysis 2025" workspace with databases for competitors, trends, customer segments. Ask Notion AI to "Summarize top 3 competitive threats" or "Generate executive summary from all research notes." One-click insights.
- AI auto-summaries: Condense pages of research into key points
- Connected workspace: Link market data → SWOT → recommendations (AI sees connections)
- Team collaboration: Share analysis workspace with stakeholders, track feedback
- Why analysts love it: Single source of truth for complex projects
📊
Beautiful.ai - AI Presentation Designer
Beautiful.ai | $12/month
Perfect for analysts who need: Turn your strategic analysis into executive presentations in minutes. AI auto-formats slides, suggests layouts, and maintains brand consistency.
💡 Use Case: "Create 10-slide board presentation: market opportunity, competitive landscape, SWOT, strategic recommendation." AI generates designer-quality slides with smart layouts. No PowerPoint wrestling required.
- Smart templates: SWOT, competitive matrix, market sizing—pre-built for business analysis
- Auto-design: Add data, AI picks best chart type and layout (no design skills needed)
- Team libraries: Brand colors, fonts, slide templates shared across team
- Why analysts love it: Presentations in 20 minutes vs. 4 hours in PowerPoint
💰 Business Analyst ROI
Analysis speed: 3-5x faster (competitive analysis: 2 days → 6 hours)
Tool investment: $42/month (Claude + Notion + Beautiful.ai)
Time saved: 10-15 hours/month on research, documentation, presentations
Quality improvement: Deeper insights (analyze more sources), pro-quality deliverables
ROI: If your hourly rate is $75+, tools pay for themselves in 30 minutes saved
📚 Summary: Your Business Analysis Toolkit
- ✅ Market research: Structure, segments, trends — verify data externally
- ✅ Competitive intelligence: Deep dives on rivals, feature matrices
- ✅ Strategic frameworks: SWOT, Porter's 5 Forces, BCG Matrix
- ✅ Data interpretation: Turn metrics into insights and recommendations
- ✅ Business model analysis: Revenue models, unit economics, validation
- ✅ Executive reporting: Board presentations, summary emails, slide decks
- ✅ Decision frameworks: ICE scoring, decision matrices, pre-mortems
🎯 Key Takeaway: ChatGPT gives you consultant-level frameworks in minutes. But remember: it provides structure, you provide domain expertise and data verification. Together, you create analysis that drives real business decisions. Final module: build complete AI workflows.
🚀 Final Module: Building AI Workflows
You've mastered individual use cases. Now let's connect them into complete workflows — multi-step processes that automate entire jobs, not just tasks.
Coming up in Module 8: Building AI Workflows — chain prompts together, create custom GPTs, integrate with APIs, build automation systems that run while you sleep.