The big management consulting firms will have to adapt quickly to AI. The days of paying half a million dollars for a strategy deck are over. By way of example, I was curious, what is next for the food delivery sector (e.g. UberEats, DoorDash, etc) so I put together a prompt and leveraged ChatGPT.
The Prompt:
You are a top strategy consultant who has worked at top-tier firms like Bain, McKinsey and BCG. Act as if you were hired to provide a $500,000 strategic analysis for a client in the food delivery sector.
ChatGPT Response:
Client: [x] Food Delivery Company
Project: Strategic Growth, Profitability, and Competitive Positioning
Consulting Fee Equivalent: $500,000
Prepared by: Strategy Consultant (ex-McKinsey/BCG/Bain)
I. Executive Summary
- Problem: The food delivery sector is saturating, unit economics are under pressure, and regulatory headwinds are rising. Our client needs a path to sustainable growth and profitability amid rising competition from DoorDash, Uber Eats, and emerging models (e.g., dark kitchens, direct-to-consumer).
- Hypothesis: Profitability in food delivery will not come from volume alone. The winners will be those who own the customer relationship, expand share of stomach, and vertically integrate just enough to control margin leakage.
- Key Recommendation: Shift from a pure-play logistics platform to a multi-vertical consumer ecosystem — leverage your delivery infrastructure to monetize across new categories (alcohol, grocery, pharmaceuticals), deepen restaurant partnerships, and drive customer loyalty through subscriptions and owned brands.
II. Market Analysis & Trends
1. TAM and Growth Forecast
- Global food delivery market: ~$400B by 2027, growing at 10% CAGR.
- Penetration remains <25% in many Tier 2+ cities = greenfield.
- Highest growth in:
- Suburban/rural regions
- Emerging markets with mobile-first users
- White-label restaurant fulfillment (ghost kitchens)
2. Key Trends
- Hyper-localization: Consumer preferences vary widely — winners tailor menus, UX, pricing per zip code.
- Vertical integration: Ghost kitchens, private-label brands, and owned courier networks improve margins.
- Multi-product delivery: Single-driver, multi-item (meal + beer + pharmacy refill) is the next frontier.
- AI-driven optimization: Dynamic pricing, batching, and delivery route AI unlock 10–15% cost savings.
III. Competitive Landscape
Porter’s Five Forces Snapshot
- Supplier power: Rising — restaurants consolidating and pushing back (e.g., fee caps).
- Buyer power: High — customers are promiscuous and driven by price/promos.
- Threat of new entrants: Medium — high capex, but startups can disrupt with niche/local angles.
- Threat of substitutes: High — groceries, cooking, dine-in rebounding post-COVID.
- Rivalry: Intense — margin-negative wars between Uber Eats, DoorDash, Grubhub.
Strategic Positioning Matrix
| Brand | Speed | Price | Market Share | Differentiation |
| DoorDash | Fast | Medium | High | DashPass + retail moves |
| Uber Eats | Fast | High | High | Uber One ecosystem |
| Grubhub | Slow | Low | Shrinking | Institutional legacy |
| [Client] | ? | ? | Low/Med | TBD |
IV. Internal Diagnostic
1. Unit Economics Deep Dive
- Average Order Value (AOV): $23 (below breakeven point of $27)
- CAC: $32; LTV: $55 → Payback period too long (>12 months)
- Gross Margin: 8% (target: 20%+)
- Delivery cost per order: $6.50; batching <20% of orders
2. Operational Gaps
- Inefficient batching — low-density areas = high delivery cost
- Weak restaurant partnerships — no exclusives, low menu integration
- High churn — 30% of users order only once
- Underutilized drivers — idle time 25–30%
V. Strategic Recommendations
1. Pivot to a Multi-Category Delivery Platform
- Launch adjacent verticals: alcohol, grocery, pet food, pharmacy
- Bundle categories into “one delivery, many items” model
- Position app as the default local everything delivery service
2. Create Exclusive Restaurant & Ghost Kitchen Partnerships
- Offer data/tech tools in exchange for menu exclusivity
- Stand up 2–3 proprietary ghost kitchen brands with high-margin items
- Co-own customer relationship: shared loyalty programs
3. Drive Profitable Growth via Subscription & Loyalty
- Launch/expand subscription: free delivery, priority support, partner perks
- Reward high-frequency users with credits, tiers (e.g., Amazon Prime model)
4. Expand into Suburban & Secondary Markets First
- Less competition, cheaper labor, longer basket size
- Partner with local restaurants neglected by Uber/Doordash
5. Optimize Delivery Economics
- AI-powered dispatching + batching
- Dynamic delivery pricing based on time, distance, demand
- Move 25–30% of fleet to part-time/contractor + hybrid logistics hubs
VI. Financial Impact (3-Year View) – Illustrative
| Metric | Current | Year 1 | Year 2 | Year 3 |
| Revenue ($M) | 60 | 95 | 135 | 180 |
| Gross Margin (%) | 8% | 14% | 18% | 22% |
| CAC Payback (months) | 12 | 9 | 6 | 4 |
| Churn (%) | 30% | 22% | 18% | 15% |
| Profit Margin | -20% | -5% | +5% | +12% |
VII. Go-to-Market & Execution Roadmap
| Quarter | Focus Area | Key Milestones |
| Q1 | Ops Optimization | AI routing, new batching algorithm live |
| Q2 | Vertical Expansion | Grocery & alcohol pilots launched |
| Q3 | Subscription Program | Tiered loyalty + new rewards implemented |
| Q4 | Exclusive Partnerships | Sign 10 ghost kitchen/restaurant exclusives |
| Q1–Q2 Y2 | Geographic Expansion | Launch 5 new secondary markets |
VIII. Risks & Mitigations
- Regulatory: Fee caps, contractor vs employee debates
→ Diversify categories, hybrid labor model - Unit Economics: Low AOV and high delivery cost
→ Push bundle orders, reduce idle time - Competition: Poaching of restaurants and drivers
→ Lock in with exclusives, perks, and better data tools
IX. Closing Thought
The era of growth-at-all-costs in food delivery is over. The winners will be customer-owning, margin-aware, ecosystem-driven operators. If [Client] acts now, it can leapfrog incumbents with better economics and a clearer path to profitability.
This was a great high level CEO/C-Suite level memo created in 10 seconds. But I wanted to get more specific. So I refined my prompt with the following. I asked the AI tool to:
1. Analyze the current state of the food delivery market.
2. Identify key trends, threats, and potential disruptive innovations.
3. Map out the top 3-5 competitors and benchmark their business models, strengths, weaknesses, pricing, distribution, and brand positioning.
4. Use frameworks like SWOT and Porter’s to assess risks and opportunities.
5. Provide a one-page strategic brief with actionable insights and recommendations for a hypothetical company entering or growing in this space.
6.) Output everything in concise bullet points or tables.
7.) Finally, structure the content into a format that I can then put into a presentation deck (PowerPoint, Google Slides, etc).
I took the memo and uploaded it into Gamma AI which then instantly turned it into the presentation below.
Given my background in BD, I then asked the tool to detail what could be future large partnerships for food delivery players like UberEats or Door Dash and then plugged into Gamma AI to make the slides for me.
Oftentimes the hardest part of doing large BD deals and commercial partnerships is quantifying the opportunity across other initiatives. So I asked the tool if it can turn this into a decision matrix prioritizing by ROI, TAM and execution complexity. The output is below.
ChatGPT Response:
Here’s a strategic decision matrix that prioritizes the top potential partnerships for food delivery platforms like Uber Eats or DoorDash, ranked by:
- ROI Potential (Revenue uplift, LTV expansion, margin leverage)
- TAM Impact (Total Addressable Market expansion or user base growth)
- Execution Complexity (Ease of deal, integration, operational execution – lower is better)
Each scored from 1 to 5 (5 = High ROI/TAM or High Complexity)
🧠 Decision Matrix: High-Impact Partnership Opportunities
| Partnership Category | Example Partners | ROI Potential | TAM Impact | Execution Complexity | Priority Tier |
| Grocery/Retail Chains | Walmart, Kroger, Aldi | 5 | 5 | 3 | ✅ Top Tier |
| QSR/Restaurant Franchises | Chick-fil-A, Panera, Shake Shack | 4 | 4 | 2 | ✅ Top Tier |
| Streaming/Entertainment | Netflix, Spotify | 4 | 3 | 2 | ✅ Top Tier |
| Travel & Hospitality | Marriott, Hilton, Airbnb | 3 | 4 | 3 | 🟡 Mid Tier |
| Theme Parks & Stadiums | Disney, NFL, Six Flags | 3 | 4 | 4 | 🟡 Mid Tier |
| Auto/EV In-Car Experiences | Tesla, Rivian, GM | 3 | 3 | 5 | 🔴 Low Tier |
| Fintech & Payments | Visa, Klarna, Amex | 4 | 3 | 2 | ✅ Top Tier |
| Healthcare/Wellness | Noom, MyFitnessPal, CVS | 3 | 3 | 4 | 🟡 Mid Tier |
| Corporate/Workplace | Microsoft, Salesforce, WeWork | 3 | 4 | 3 | 🟡 Mid Tier |
| Food-as-a-Service APIs | Olo, POS systems, white-label apps | 5 | 4 | 4 | ✅ Top Tier |
| Gaming/Virtual Worlds | Roblox, Fortnite, Twitch | 4 | 3 | 5 | 🔴 Low Tier |
| Municipal/Public Sector | Public schools, elder care programs | 2 | 4 | 5 | 🔴 Low Tier |
📊 Visual Key
- ✅ Top Tier: High ROI + TAM with moderate complexity — pursue immediately.
- 🟡 Mid Tier: Good strategic fit, may require sequencing or pilot first.
- 🔴 Low Tier: Either high complexity or niche impact — explore opportunistically.
💡 Strategic Recommendation
Focus near-term on:
- Grocery chains for scale
- QSR franchises for frequency
- Payments/fintech for LTV
- Food API distribution for B2B leverage
- Media/streaming for loyalty & co-branding
This entire workstream took me 15 minutes. It’s definitely not perfect, and the key is building your prompts correctly, but tools are getting smarter as the LLM’s continue to be trained on vasts amounts of content.
If you’re a startup founder, I would think twice before paying big money ($) on your next strategy deck.