Recommendation Canvas

1---2name: recommendation-canvas3description: Evaluate an AI product idea across outcomes, hypotheses, risks, and positioning. Use when deciding whether an AI solution deserves investment or recommendation.4intent: >-5  Evaluate and propose AI product solutions using a structured canvas that assesses business outcomes, customer outcomes, problem framing, solution hypotheses, positioning, risks, and value justification. Use this to build a comprehensive, defensible recommendation for stakeholders and decision-makers—especially when proposing AI-powered features or products that carry higher uncertainty and risk.6type: component7---8 9 10## Purpose11Evaluate and propose AI product solutions using a structured canvas that assesses business outcomes, customer outcomes, problem framing, solution hypotheses, positioning, risks, and value justification. Use this to build a comprehensive, defensible recommendation for stakeholders and decision-makers—especially when proposing AI-powered features or products that carry higher uncertainty and risk.12 13This is not a feature spec—it's a strategic proposal that articulates *why* this AI solution is worth building, *what* assumptions need validating, and *how* you'll measure success.14 15## Key Concepts16 17### The Recommendation Canvas Framework18Created for Dean Peters' Productside "AI Innovation for Product Managers" class, the canvas synthesizes multiple PM frameworks into one strategic view:19 20**Core Components:**211. **Business Outcome:** What's in it for the business?222. **Product Outcome:** What's in it for the customer?233. **Problem Statement:** Persona-centric problem framing244. **Solution Hypothesis:** If/then hypothesis with experiments255. **Positioning Statement:** Value prop and differentiation266. **Assumptions & Unknowns:** What could invalidate this?277. **PESTEL Risks:** Political, Economic, Social, Technological, Environmental, Legal288. **Value Justification:** Why this is worth doing299. **Success Metrics:** SMART metrics to measure impact3010. **What's Next:** Strategic next steps31 32### Why This Works33- **Outcome-driven:** Forces clarity on business AND customer value34- **Hypothesis-centric:** Treats solution as a bet to validate, not a commitment35- **Risk-explicit:** Makes assumptions and risks visible upfront36- **Executive-friendly:** Comprehensive but structured for C-level review37- **AI-appropriate:** Especially useful for AI features with high uncertainty38 39### Anti-Patterns (What This Is NOT)40- **Not a PRD:** This is strategic framing, not detailed requirements41- **Not a business case (yet):** It informs the business case but needs validation first42- **Not a feature list:** Focus on outcomes, not capabilities43 44### When to Use This45- Proposing a new AI-powered product or feature46- Pitching to execs or securing budget/sponsorship47- Evaluating whether an AI solution is worth pursuing48- Aligning cross-functional stakeholders (product, engineering, data science, business)49- After completing initial discovery (you need context to fill this out)50 51### When NOT to Use This52- For trivial features (don't over-engineer small tweaks)53- Before any discovery work (you need user research and problem validation first)54- As a replacement for experimentation (canvas informs experiments, not vice versa)55 56---57 58## Application59 60Use `template.md` for the full fill-in structure.61 62### Step 1: Gather Context63Before filling out the canvas, ensure you have:64- **Problem understanding:** User research, pain points (reference `skills/problem-statement/SKILL.md`)65- **Persona clarity:** Who experiences the problem? (reference `skills/proto-persona/SKILL.md`)66- **Market context:** Competitive landscape, category positioning67- **Business constraints:** Budget, timelines, strategic priorities68 69**If missing context:** Run discovery work first. This canvas synthesizes insights—it doesn't create them.70 71---72 73### Step 2: Define Outcomes74 75#### Business Outcome76What's in it for the business? Use this format:77- [Direction] [Metric] [Outcome] [Context] [Acceptance Criteria]78 79```markdown80## Business Outcome81- [e.g., "Reduce by 25% the churn of existing customers using our existing product"]82```83 84**Example:**85- "Increase by 15% the monthly recurring revenue from enterprise customers within 12 months"86 87**Quality checks:**88- **Measurable:** Can you track this metric?89- **Time-bound:** Within what timeframe?90- **Ambitious but realistic:** Not "10x revenue in 1 month"91 92---93 94#### Product Outcome95What's in it for the customer? Use this format:96- [Direction] [Metric] [Outcome] [Context from persona's POV] [Acceptance Criteria]97 98```markdown99## Product Outcome100- [e.g., "Increase the speed of finding patients when I know the inclusion and exclusion criteria"]101```102 103**Example:**104- "Reduce by 60% the time spent manually processing invoices for small business owners"105 106**Quality checks:**107- **Customer-centric:** Written from user perspective ("I," not "we")108- **Outcome, not feature:** "Reduce time spent" not "Use AI automation"109 110---111 112### Step 3: Frame the Problem113Use the problem framing narrative from `skills/problem-statement/SKILL.md`:114 115```markdown116## The Problem Statement117 118### Problem Statement Narrative119- [Persona description: 2-3 sentences telling the persona's story from their POV]120- [Example: "Sarah is a freelance designer managing 10 clients. She spends 8 hours/month manually tracking invoices and chasing late payments. By the time she follows up, some clients have already moved to other designers, costing her revenue and damaging relationships."]121```122 123**Quality checks:**124- **Empathetic:** Does this sound like the user's voice?125- **Specific:** Not "users want better tools" but "Sarah spends 8 hours/month..."126- **Validated:** Based on real user research, not assumptions127 128---129 130### Step 4: Define the Solution Hypothesis131 132#### Hypothesis Statement133Use the epic hypothesis format from `skills/epic-hypothesis/SKILL.md`:134 135```markdown136## Solution Hypothesis137 138### Hypothesis Statement139**If we** [action or solution on behalf of target persona]140**for** [target persona]141**Then we will** [attain or achieve desirable outcome]142```143 144**Example:**145- "If we provide AI-powered invoice reminders that auto-send at optimal times for freelance designers, then we will reduce time spent on payment follow-ups by 70%"146 147---148 149#### Tiny Acts of Discovery150Define lightweight experiments to validate the hypothesis:151 152```markdown153### Tiny Acts of Discovery154**We will test our assumption by:**155- [Experiment 1: Prototype AI reminder system and test with 5 freelancers]156- [Experiment 2: A/B test manual vs. AI-timed reminders for 20 users]157- [Experiment 3: Survey users on perceived value after 2 weeks]158```159 160**Quality checks:**161- **Fast:** Days/weeks, not months162- **Cheap:** Prototypes, concierge tests, not full builds163- **Falsifiable:** Could prove you wrong164 165---166 167#### Proof-of-Life168Define validation measures:169 170```markdown171### Proof-of-Life172**We know our hypothesis is valid if within** [timeframe]173**we observe:**174- [Quantitative outcome: e.g., "80% of users send reminders via the AI system"]175- [Qualitative outcome: e.g., "8 out of 10 users report saving 5+ hours/month"]176```177 178---179 180### Step 5: Define Positioning181Use the positioning statement format from `skills/positioning-statement/SKILL.md`:182 183```markdown184## Positioning Statement185 186### Value Proposition187**For** [target customer/user persona]188**that need** [statement of underserved need]189[product name]190**is a** [product category]191**that** [statement of benefit, focusing on outcomes]192 193### Differentiation Statement194**Unlike** [primary competitor or competitive arena]195[product name]196**provides** [unique differentiation, focusing on outcomes]197```198 199---200 201### Step 6: Document Assumptions & Unknowns202 203```markdown204## Assumptions & Unknowns205- **[Assumption 1]** - [Description, e.g., "We assume users will trust AI-generated reminders"]206- **[Assumption 2]** - [Description, e.g., "We assume payment timing optimization increases response rates"]207- **[Unknown 1]** - [Description, e.g., "We don't know if users prefer email or SMS reminders"]208```209 210**Quality checks:**211- **Explicit:** Make hidden assumptions visible212- **Testable:** Each assumption can be validated via experiments213 214---215 216### Step 7: Identify PESTEL Risks217 218#### Risks to Investigate (High Priority)219```markdown220## Issues/Risks to Investigate221- **Political:** [e.g., "Regulatory changes to AI-generated communications"]222- **Economic:** [e.g., "Economic downturn reduces willingness to pay for premium features"]223- **Social:** [e.g., "Users may perceive AI reminders as impersonal or pushy"]224- **Technological:** [e.g., "AI model accuracy may degrade over time without retraining"]225- **Environmental:** [e.g., "Energy costs of AI processing"]226- **Legal:** [e.g., "GDPR compliance for storing customer email patterns"]227```228 229---230 231#### Risks to Monitor (Lower Priority)232```markdown233## Issues/Risks to Monitor234- **Political:** [e.g., "Potential AI regulation in EU markets"]235- **Economic:** [e.g., "Exchange rate fluctuations affecting international customers"]236- **Social:** [e.g., "Changing norms around automated communication"]237- **Technological:** [e.g., "Emerging AI competitors with better models"]238- **Environmental:** [e.g., "Carbon footprint concerns from stakeholders"]239- **Legal:** [e.g., "Future data privacy laws"]240```241 242---243 244### Step 8: Justify the Value245 246```markdown247## Value Justification248 249### Is this Valuable?250- [Absolutely yes / Yes with caveats / No with suggested alternatives / Absolutely NO!]251 252### Solution Justification253<!-- Write these to convince C-level executives -->254We think this is a valuable idea. Here's why:2551. **[Justification 1]** - [Description, e.g., "Addresses the #1 pain point for our target segment"]2562. **[Justification 2]** - [Description, e.g., "Differentiates us from competitors who only offer manual reminders"]2573. **[Justification 3]** - [Description, e.g., "Low technical risk—leverages existing AI infrastructure"]258```259 260---261 262### Step 9: Define Success Metrics263Use SMART metrics (Specific, Measurable, Attainable, Relevant, Time-Bound):264 265```markdown266## Success Metrics2671. **[Metric 1]** - [e.g., "80% of active users adopt AI reminders within 3 months"]2682. **[Metric 2]** - [e.g., "Average time spent on payment follow-ups decreases by 50% within 6 months"]2693. **[Metric 3]** - [e.g., "Net Promoter Score for invoicing feature increases from 6 to 8 within 6 months"]270```271 272---273 274### Step 10: Define Next Steps275 276```markdown277## What's Next2781. **[Next step 1]** - [e.g., "Run 2-week prototype test with 10 beta users"]2792. **[Next step 2]** - [e.g., "Build lightweight AI model for reminder timing optimization"]2803. **[Next step 3]** - [e.g., "Conduct legal review of GDPR implications"]2814. **[Next step 4]** - [e.g., "Present findings to exec team for go/no-go decision"]2825. **[Next step 5]** - [e.g., "If validated, add to Q2 roadmap"]283```284 285---286 287## Examples288 289See `examples/sample.md` for a full recommendation canvas example.290 291Mini example excerpt:292 293```markdown294### Business Outcome295- Increase by 20% MRR from freelance users within 12 months296 297### Solution Hypothesis298**If we** provide AI-powered invoice reminders299**for** freelance designers300**Then we will** reduce time spent on follow-ups by 70%301```302 303## Common Pitfalls304 305### Pitfall 1: Vague Outcomes306**Symptom:** "Business outcome: increase revenue. Product outcome: improve UX."307 308**Consequence:** No measurability or accountability.309 310**Fix:** Use the outcome formula: [Direction] [Metric] [Outcome] [Context] [Acceptance Criteria]. Be specific.311 312---313 314### Pitfall 2: Solution-First Thinking315**Symptom:** Problem statement is "We need AI-powered X"316 317**Consequence:** You've jumped to solution without validating the problem.318 319**Fix:** Frame problem from user perspective. Let the solution hypothesis emerge from validated pain points.320 321---322 323### Pitfall 3: Skipping Tiny Acts of Discovery324**Symptom:** Hypothesis → straight to roadmap, no experiments325 326**Consequence:** High risk of building the wrong thing.327 328**Fix:** Define 2-3 lightweight experiments. Test before committing engineering resources.329 330---331 332### Pitfall 4: Generic PESTEL Risks333**Symptom:** "Political: regulations might change"334 335**Consequence:** Risk analysis is theater, not actionable.336 337**Fix:** Be specific: "GDPR compliance for storing client email timing data requires legal review."338 339---340 341### Pitfall 5: Weak Value Justification342**Symptom:** "This is valuable because customers will like it"343 344**Consequence:** Not convincing to execs.345 346**Fix:** Use data: "Addresses #1 pain point per user research. 20% churn reduction = $500k ARR. Low tech risk."347 348---349 350## References351 352### Related Skills353- `skills/problem-statement/SKILL.md` — Informs the problem narrative354- `skills/epic-hypothesis/SKILL.md` — Informs the solution hypothesis structure355- `skills/positioning-statement/SKILL.md` — Informs positioning section356- `skills/proto-persona/SKILL.md` — Defines target persona357- `skills/jobs-to-be-done/SKILL.md` — Informs customer outcomes358 359### External Frameworks360- Osterwalder's Value Proposition Canvas — Influences problem/solution framing361- PESTEL Analysis — Risk assessment framework362- SMART Goals — Success metrics structure363 364### Dean's Work365- AI Recommendation Canvas Template (created for Productside "AI Innovation for Product Managers" class)366 367### Provenance368- Adapted from `prompts/recommendation-canvas-template.md` in the `https://github.com/deanpeters/product-manager-prompts` repo.369 370---371 372**Skill type:** Component373**Suggested filename:** `recommendation-canvas.md`374**Suggested placement:** `/skills/components/`375**Dependencies:** References `skills/problem-statement/SKILL.md`, `skills/epic-hypothesis/SKILL.md`, `skills/positioning-statement/SKILL.md`, `skills/proto-persona/SKILL.md`, `skills/jobs-to-be-done/SKILL.md`