.claude/skills/market-analyst/SKILL.md
Synthesize multiple sentiment analyses to identify market trends, gaps, opportunities, and predict likely hits. Cross-analyzes patterns to find underserved markets and highlight unique innovations.
npx skillsauth add natea/fitfinder market-analystInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill consumes outputs from the reddit-sentiment-analysis skill to perform meta-analysis across multiple products/games. It identifies:
Use this skill when you have:
Input Data: 2+ Reddit sentiment analysis reports in /docs/
reddit-sentiment-analysis skillAnalysis Scope: Clear product category (e.g., FPS games, productivity apps, streaming services)
1. Identify Available Sentiment Reports
/docs/ for reddit-sentiment-*.md files2. Extract Key Data Points
For each product/game analyzed, extract:
{
product_name: string,
overall_sentiment: {positive: %, negative: %, neutral: %},
likes: [
{aspect: string, mentions: number, sentiment: %, quotes: []}
],
dislikes: [
{aspect: string, mentions: number, severity: string, quotes: []}
],
wishes: [
{feature: string, mentions: number, urgency: string, quotes: []}
],
key_insights: [],
competitor_mentions: {}
}
3. Identify Universal Success Factors
Analyze LIKES across all products to find patterns:
Pattern Detection Algorithm:
// Group similar aspects across products
const commonLikes = groupSimilarAspects(allProducts.likes);
// Calculate frequency and consistency
for (aspect in commonLikes) {
const frequency = countProducts(aspect);
const avgSentiment = calculateAverage(aspect.sentiment);
const consistency = calculateVariance(aspect.sentiment);
if (frequency >= 50% && avgSentiment >= 85% && consistency < 15%) {
markAs("Universal Success Factor");
}
}
Success Factor Categories:
4. Identify Universal Pain Points
Analyze DISLIKES across all products:
// Find recurring complaints
const commonDislikes = groupSimilarIssues(allProducts.dislikes);
// Classify by universality
for (issue in commonDislikes) {
const frequency = countProducts(issue);
const avgSeverity = calculateSeverity(issue);
if (frequency >= 60% && avgSeverity === "HIGH") {
markAs("Industry-Wide Problem");
}
}
Pain Point Categories:
5. Analyze Wish Patterns
Examine WISHES to identify unmet demand:
// Find common wishes across products
const universalWishes = groupSimilarWishes(allProducts.wishes);
// Calculate demand intensity
for (wish in universalWishes) {
const demandScore = wish.frequency * wish.avgUrgency * wish.mentions;
if (demandScore > THRESHOLD) {
markAs("High-Demand Unmet Need");
}
}
6. Identify Market Gaps
Gap Detection Framework:
Type 1: Feature Gaps (Widely wished for, nobody delivers)
IF: Wish appears in 3+ products
AND: Urgency >= MEDIUM across all
AND: No product currently delivers it
THEN: Feature Gap Opportunity
Type 2: Segment Gaps (Underserved audience)
IF: Common complaint about product not serving a specific need
AND: No product specifically targets that need
THEN: Segment Gap Opportunity
Type 3: Price/Value Gaps (Wrong pricing tier)
IF: Multiple products criticized for pricing
AND: Wishes mention "more affordable option" or "premium option"
AND: No product fills that price point
THEN: Price Gap Opportunity
Type 4: Business Model Gaps (Better service model needed)
IF: Common complaints about monetization/lifecycle
AND: Alternative model wished for across products
THEN: Business Model Gap Opportunity
7. Calculate Gap Priority Score
gapPriorityScore = (
demandIntensity * 0.35 + // How many people want it
competitiveGap * 0.25 + // How few products offer it
urgencyLevel * 0.20 + // How badly it's needed
marketSize * 0.15 + // Addressable market size
feasibility * 0.05 // Technical/business feasibility
) * 100
Priority Tiers:
8. Identify Outlier Successes
Find products/features praised uniquely:
// Detect novelty
for (product in allProducts) {
for (like in product.likes) {
const uniqueness = calculateUniqueness(like, otherProducts);
const sentiment = like.sentiment;
if (uniqueness > 80% && sentiment > 85%) {
markAs("Novelty Success", {
feature: like.aspect,
product: product.name,
why_unique: analyzeWhy(like),
replicability: assessReplicability(like)
});
}
}
}
Novelty Categories:
9. Assess Novelty Replicability
For each novelty success:
10. Predict Likely Hits
Hit Prediction Algorithm:
function predictHitPotential(productConcept) {
const score = {
alignsWithSuccessFactors: 0, // Does it have universal likes?
avoidsCommonPitfalls: 0, // Does it avoid universal dislikes?
addressesUnmetNeeds: 0, // Does it fill market gaps?
hasNoveltyFactor: 0, // Does it innovate?
priceValueProposition: 0 // Is pricing right?
};
// Score each dimension (0-100)
score.alignsWithSuccessFactors = checkAlignment(productConcept, universalSuccessFactors);
score.avoidsCommonPitfalls = checkAvoidance(productConcept, universalPainPoints);
score.addressesUnmetNeeds = checkGapFilling(productConcept, marketGaps);
score.hasNoveltyFactor = checkNovelty(productConcept, noveltySuccesses);
score.priceValueProposition = checkPricing(productConcept, pricingAnalysis);
const hitProbability = (
score.alignsWithSuccessFactors * 0.30 +
score.avoidsCommonPitfalls * 0.25 +
score.addressesUnmetNeeds * 0.25 +
score.hasNoveltyFactor * 0.15 +
score.priceValueProposition * 0.05
);
return {
probability: hitProbability,
confidence: calculateConfidence(dataQuality, sampleSize),
breakdown: score,
recommendations: generateRecommendations(score)
};
}
11. Generate Strategic Recommendations
Product Development Recommendations:
### Must-Have Features (Universal Success Factors)
1. [Feature] - Present in X/Y products with Z% positive sentiment
- Why it matters: [explanation]
- How to implement: [guidance]
### Critical Pitfalls to Avoid (Universal Pain Points)
1. [Issue] - Complained about in X/Y products with Z severity
- Why it fails: [explanation]
- How to avoid: [guidance]
### Market Gap Opportunities (High Priority)
1. [Gap] - Priority Score: XX/100
- Demand evidence: [data]
- Competition: [current state]
- Recommended approach: [strategy]
12. Create Market Opportunity Matrix
HIGH NOVELTY
|
LOW DEMAND Q2: Risky Innovation Q1: Blue Ocean HIGH DEMAND
| |
Q3: Avoid/Niche Q4: Proven Demand
|
LOW NOVELTY
Q1 (High Demand + High Novelty): PRIORITY - Innovate in underserved areas
Q2 (Low Demand + High Novelty): RISKY - Innovation without market validation
Q3 (Low Demand + Low Novelty): AVOID - Crowded, low-interest space
Q4 (High Demand + Low Novelty): SAFE - Proven market, execution differentiator
# Market Analysis Report: [Product Category]
**Analysis Date**: [Date]
**Products Analyzed**: [List]
**Sentiment Reports Used**: [Number]
**Total Data Points**: [Posts + Comments analyzed]
---
## Executive Summary
[2-3 paragraph overview of key findings, top opportunities, major risks]
---
## Section 1: Universal Success Factors
### What Drives Success Across All Products
1. **[Success Factor Name]** (appears in X/Y products, Z% avg positive sentiment)
- **Evidence**: [Quotes from multiple products]
- **Why it works**: [Psychological/practical explanation]
- **Implementation guidance**: [How to deliver this]
- **Products excelling**: [Examples]
[Repeat for 5-7 success factors]
### Success Factor Summary Table
| Factor | Frequency | Avg Sentiment | Consistency | Priority |
|--------|-----------|---------------|-------------|----------|
| [Factor 1] | 5/5 products | 92% | High | CRITICAL |
| [Factor 2] | 4/5 products | 87% | Medium | HIGH |
...
---
## Section 2: Universal Pain Points
### What Consistently Fails Across Products
1. **[Pain Point Name]** (appears in X/Y products, Z severity)
- **Evidence**: [Quotes showing frustration]
- **Why it fails**: [Root cause analysis]
- **How to avoid**: [Prevention strategy]
- **Products struggling**: [Examples]
[Repeat for 5-7 pain points]
### Pain Point Summary Table
| Issue | Frequency | Avg Severity | Impact | Avoidability |
|-------|-----------|--------------|--------|--------------|
| [Issue 1] | 5/5 products | CRITICAL | High | Easy |
| [Issue 2] | 4/5 products | HIGH | Medium | Hard |
...
---
## Section 3: Market Gaps & Opportunities
### High-Priority Gaps (Score 75-100)
1. **[Gap Name]** - Priority Score: XX/100
- **Type**: [Feature/Segment/Price/Business Model]
- **Demand Evidence**:
- Mentioned in X/Y products
- Y total mentions, Z% urgency HIGH
- Representative quotes: "[quote 1]", "[quote 2]"
- **Current Competition**: [Who's attempting this, if anyone]
- **Market Size Estimate**: [TAM/SAM if calculable]
- **Recommended Approach**: [Strategy to fill gap]
- **Risks**: [Challenges to address]
- **Timeline to Market**: [Estimate]
[Repeat for all high-priority gaps]
### Medium-Priority Gaps (Score 60-74)
[Similar structure, condensed]
### Gap Opportunity Matrix
Demand Intensity vs. Competitive Gap [Visual representation of opportunities]
---
## Section 4: Novelty & Innovation Analysis
### Successful Innovations (Outlier Wins)
1. **[Innovation Name]** from [Product]
- **What makes it unique**: [Description]
- **Sentiment**: [% positive, mentions]
- **Evidence**: [Quotes praising novelty]
- **Replicability**: [EASY/MEDIUM/HARD]
- **Transferability**: [Which categories could use this]
- **Competitive moat**: [WEAK/MEDIUM/STRONG]
- **Recommendation**: [Should others copy? How?]
[Repeat for 3-5 novelty successes]
### Innovation Categories
- **Mechanic Innovations**: [List]
- **Design Innovations**: [List]
- **Business Model Innovations**: [List]
- **Community Innovations**: [List]
---
## Section 5: Predicted Hits & Strategic Recommendations
### Upcoming Products/Concepts Likely to Succeed
1. **[Product/Concept]** - Hit Probability: XX%
- **Why it will succeed**:
- ✅ Aligns with success factors: [Score/100]
- ✅ Avoids common pitfalls: [Score/100]
- ✅ Addresses unmet needs: [Score/100]
- ✅ Has novelty factor: [Score/100]
- ✅ Price/value proposition: [Score/100]
- **Key strengths**: [List]
- **Potential risks**: [List]
- **Confidence level**: [HIGH/MEDIUM/LOW based on data]
[Repeat for 3-5 predicted hits]
### Product Development Blueprint
**If creating a new product in this category, it MUST:**
✅ **Include These (Universal Success Factors)**
1. [Factor 1] - Critical
2. [Factor 2] - High priority
3. [Factor 3] - Medium priority
...
❌ **Avoid These (Universal Pain Points)**
1. [Pitfall 1] - Critical to avoid
2. [Pitfall 2] - High priority to avoid
...
🎯 **Target These Gaps (Market Opportunities)**
1. [Gap 1] - Priority Score: XX
2. [Gap 2] - Priority Score: XX
...
💡 **Consider These Innovations (Novelty Opportunities)**
1. [Innovation 1] - Transferable from [Product]
2. [Innovation 2] - Novel approach to [Problem]
...
### Strategic Positioning Recommendations
**Blue Ocean Opportunities** (High demand + High novelty):
- [Opportunity 1]: [Description and strategy]
- [Opportunity 2]: [Description and strategy]
**Safe Bets** (High demand + Proven approach):
- [Opportunity 1]: [Description and execution focus]
**Risky Innovations** (Low current demand + High novelty):
- [Opportunity 1]: [Why risky, when it might pay off]
**Avoid Zones** (Low demand + Low novelty):
- [Space 1]: [Why to avoid]
---
## Section 6: Trend Analysis
### Emerging Trends
1. **[Trend Name]**
- **Evidence**: [Sentiment shifts, wish patterns]
- **Trajectory**: [Growing/Stable/Declining]
- **Opportunity window**: [Timeframe]
- **First-mover advantage**: [Strength]
### Dying Trends
1. **[Trend Name]**
- **Evidence**: [Negative sentiment increase]
- **Why it's failing**: [Analysis]
- **Avoid investing in**: [Specific approaches]
---
## Section 7: Competitive Intelligence
### Competitor Positioning
| Product | Strength | Weakness | Sentiment | Market Position |
|---------|----------|----------|-----------|-----------------|
| [Product 1] | [Core strength] | [Main weakness] | XX% positive | Leader/Challenger |
...
### Competitive Gaps
Products are NOT competing on:
- [Dimension 1]: Opportunity for differentiation
- [Dimension 2]: Blue ocean potential
---
## Appendices
### A. Data Quality & Methodology
- **Products analyzed**: [List with report dates]
- **Total posts/comments**: [Numbers]
- **Confidence scores**: [How calculated]
- **Limitations**: [Data gaps, biases, timeframe]
### B. Detailed Calculations
[Show priority score calculations, hit prediction formulas]
### C. Raw Data Summary
[Tables of all extracted data points]
---
## Actionable Next Steps
1. **Immediate (This week)**:
- [Action based on critical findings]
2. **Short-term (This month)**:
- [Actions based on high-priority gaps]
3. **Long-term (This quarter)**:
- [Strategic positioning moves]
---
**Report Generated By**: Market Analyst Skill v1.0
**Based On**: [X] Reddit Sentiment Analysis Reports
**Data Sources**: Reddit (r/[subreddits])
**Analysis Date**: [Date]
TodoWrite([
"Identify and load all sentiment analysis reports",
"Extract structured data from each report",
"Identify universal success factors across products",
"Identify universal pain points across products",
"Analyze wish patterns for unmet demand",
"Calculate market gap priority scores",
"Detect novelty successes and assess replicability",
"Predict likely hits and generate recommendations",
"Create market opportunity matrix",
"Generate comprehensive market analysis report"
])
CRITICAL: Batch all file reads in parallel:
[Single Message - Parallel Report Loading]:
Read("/docs/reddit-sentiment-analysis-game1.md")
Read("/docs/reddit-sentiment-analysis-game2.md")
Read("/docs/reddit-sentiment-analysis-game3.md")
Read("/docs/reddit-sentiment-analysis-game4.md")
Read("/docs/reddit-sentiment-analysis-game5.md")
Process all reports simultaneously to identify:
For each identified wish pattern:
Save comprehensive report to:
/docs/market-analysis-[category]-[date].md
✅ Analyze minimum 3 products for meaningful patterns ✅ Use recent sentiment data (within 3 months) ✅ Consider product category context (FPS games ≠ puzzle games) ✅ Weight by sample size (1000 comments > 50 comments) ✅ Look for sentiment intensity, not just direction ✅ Consider temporal trends (sentiment changing over time) ✅ Cross-reference competitor mentions ✅ Validate gaps with market research
❌ Mix incompatible product categories (games + productivity apps) ❌ Over-generalize from small sample sizes ❌ Ignore context (niche vs. mainstream products) ❌ Assume correlation = causation ❌ Miss seasonal/event-driven sentiment spikes ❌ Ignore demographic differences in sentiment ❌ Recommend unfeasible solutions
This skill works perfectly with:
Input: 5 FPS game sentiment reports
Output:
- Success factors: Gunplay feel, map variety, progression
- Pain points: Aggressive monetization, yearly release cycles
- Gaps: Affordable tactical shooter, 2-3 year lifecycles
- Predicted hit: Tactical shooter at $20-30 with 3-year support
Input: 4 productivity tool sentiment reports
Output:
- Success factors: Clean UX, integration ecosystem, offline mode
- Pain points: Confusing pricing, feature bloat, poor onboarding
- Gaps: Simple, focused tool for [specific use case]
- Predicted hit: Specialized tool doing one thing excellently
Input: 3 streaming platform sentiment reports
Output:
- Success factors: Content library, UI/UX, affordable pricing
- Pain points: Content removal, ads in paid tiers, app crashes
- Gaps: Ad-free budget tier, permanent content library
- Predicted hit: Niche streaming service with ownership model
The Market Analyst Skill transforms individual sentiment analyses into strategic market intelligence by:
This enables data-driven decision-making for:
The output is a comprehensive, evidence-based market analysis report ready for strategic planning and product development decisions.
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