Market Analyst Skill

Purpose

This skill consumes outputs from the

reddit-sentiment-analysis

skill to perform meta-analysis across multiple products/games. It identifies:

Common patterns

across successful products (what universally drives satisfaction)

Market gaps

where demand exists but supply is lacking

Underserved segments

with unmet needs

Novelty opportunities

where unique approaches could succeed

Predicted hits

based on cross-product sentiment intelligence

Strategic recommendations

for product development and positioning

When to Use This Skill

Use this skill when you have:

✅ Multiple sentiment analysis reports (2+ products/games analyzed)

✅ Need to identify market opportunities across a product category

✅ Want to predict which upcoming products will succeed

✅ Looking for gaps in the market based on user sentiment

✅ Need strategic recommendations for product development

✅ Want to understand what makes products succeed or fail

Prerequisites

Input Data

2+ Reddit sentiment analysis reports in

/docs/

Generated by

reddit-sentiment-analysis

skill

Must follow standard format with LIKES/DISLIKES/WISHES sections

Recent data (ideally within same time period)

Analysis Scope

Clear product category (e.g., FPS games, productivity apps, streaming services)

Core Workflow

Phase 1: Data Ingestion and Normalization

1. Identify Available Sentiment Reports

Scan

/docs/

for

reddit-sentiment-*.md

files

Parse each report to extract structured data

Validate format and completeness

2. 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

:

{

}

}

Phase 2: Cross-Product Pattern Analysis

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:

Gameplay/Functionality

Core mechanics, features, usability

Value Proposition

Pricing, content volume, value-for-money

Polish/Quality

Performance, visuals, stability, UX

Community/Social

Multiplayer, social features, community engagement

Innovation

Novel mechanics, creative approaches, unique features

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:

Monetization Issues

Aggressive MTX, pay-to-win, expensive pricing

Technical Problems

Performance, bugs, server issues

Design Flaws

Poor UX, frustrating mechanics, balance issues

Content/Feature Gaps

Missing features, lack of variety

Business Model Issues

Live service problems, abandonment fears

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"

)

;

}

}

Phase 3: Gap Identification and Market Opportunity Analysis

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:

CRITICAL (90-100)

Massive demand, no competition, urgent need

HIGH (75-89)

Strong demand, minimal competition, clear need

MEDIUM (60-74)

Moderate demand, some competition, growing need

LOW (40-59)

Niche demand, crowded market, optional feature

Phase 4: Novelty Detection and Innovation Analysis

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:

Mechanic Innovation

Unique gameplay/feature never seen before

Design Innovation

Novel UX/UI approach or artistic direction

Business Model Innovation

New monetization or service model

Community Innovation

Unique social/multiplayer approach

Accessibility Innovation

Solving problems in new ways 9. Assess Novelty Replicability For each novelty success: Transferable to other products? (YES/NO/PARTIAL) Category-specific or universal? (UNIVERSAL/CATEGORY/PRODUCT) Competitive moat strength? (WEAK/MEDIUM/STRONG) First-mover advantage duration? (MONTHS/YEARS/PERMANENT) Phase 5: Predictive Analysis and Recommendations 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 Output Format Market Analysis Report Structure

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]
2. What makes it unique: [Description]
3. Sentiment: [% positive, mentions]
4. Evidence: [Quotes praising novelty]
5. Replicability: [EASY/MEDIUM/HARD]
6. Transferability: [Which categories could use this]
7. Competitive moat: [WEAK/MEDIUM/STRONG]
8. 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%
2. Why it will succeed:
3. ✅ Aligns with success factors: [Score/100]
4. ✅ Avoids common pitfalls: [Score/100]
5. ✅ Addresses unmet needs: [Score/100]
6. ✅ Has novelty factor: [Score/100]
7. ✅ Price/value proposition: [Score/100]
8. Key strengths: [List]
9. Potential risks: [List]
10. 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]
2. Evidence: [Sentiment shifts, wish patterns]
3. Trajectory: [Growing/Stable/Declining]
4. Opportunity window: [Timeframe]
5. First-mover advantage: [Strength]

Dying Trends

1. [Trend Name]
2. Evidence: [Negative sentiment increase]
3. Why it's failing: [Analysis]
4. Avoid investing in: [Specific approaches]

Section 7: Competitive Intelligence

Competitor Positioning