QuadrantX Market Intelligence

Marathon Running Shoes
Report Q4 2025

How Leading LLMs Currently Interpret the Marathon Running Shoes Market

View Rankings
20
Vendors Analyzed
5
LLM Models
5
Analysis Runs
5
Leaders Identified

QuadrantX Positioning

Vendor placement based on Narrative Dominance and Sentiment scores across LLM analyses

Leaders
Challengers
Niche Players
Laggards

Complete Vendor Rankings

All 20 vendors ranked by combined Narrative Dominance and Sentiment scores

#1

Nike

Leader
ND 100
Sentiment 95
#2

Adidas

Leader
ND 95
Sentiment 84
#3

ASICS

Leader
ND 86
Sentiment 78
#4

Brooks

Leader
ND 62
Sentiment 64
#5
ND 61
Sentiment 61
#6

Brooks Running

Challenger
ND 62
Sentiment 58
#7

Saucony

Niche Player
ND 60
Sentiment 65
#8

On

Niche Player
ND 60
Sentiment 64
#9

Hoka

Niche Player
ND 52
Sentiment 60
#10

Puma

Niche Player
ND 24
Sentiment 63
#11
ND 52
Sentiment 60
#12

On Running

Laggard
ND 28
Sentiment 46
#13
ND 19
Sentiment 39
#14

Mizuno

Laggard
ND 25
Sentiment 32
#15
ND 31
Sentiment 25
#16

Salomon

Laggard
ND 20
Sentiment 35
#17

Altra

Laggard
ND 17
Sentiment 36
#18
ND 17
Sentiment 32
#19

Skechers

Laggard
ND 15
Sentiment 34
#20
ND 15
Sentiment 30

Key Findings

Critical insights extracted from cross-model analysis

Innovation Concentration

Modern, cloud-native platforms show concentrated sentiment advantages at multiple touchpoints.

Narrative Visibility Gaps

A narrow top-funnel ND range indicates crowded awareness conditions. 10 vendors show limited visibility despite market presence.

Sentiment Cliffs

Certain platforms exhibit notable drops between mid- and bottom-funnel stages, reflecting evaluation-stage friction.

Feature-Set Separators

ERP-integrated suites gain advantage through ecosystem lock-in, while modern competitors differentiate through UX and automation.

๐Ÿ† Category Awards

Recognizing standout vendors based on AI-consensus analysis

๐Ÿ†
Most Valuable
Nike
Score: 195

Achieved the highest combined performance with ND 100 and Sentiment 95, establishing clear market leadership.

๐Ÿš€
Most Potential
Hoka
Sentiment: 60

Identified by our AI analyst as showing strong growth momentum. Watch for Hoka's ability to scale marketing investment and clarify brand positioning to match its product innovation strength.

โšก
Most Controversial
Brooks
Variance: 64

Generated the most debate across AI models with a variance score of 64. Models showed significant disagreement on this vendor's positioning.

๐Ÿ’Ž
Hidden Gem
Saucony
Sentiment: 65

Strong sentiment score of 65 despite lower market visibility (ND: 60). Well-regarded by those who know them, representing an underappreciated option.

QuadrantX Methodology

QuadrantX applies a structured, multi-model approach using 5 independent runs across 5 LLMs (claude, openai, gemini, perplexity, deepseek). Each model is queried with deterministic temperature settings (0.1) to ensure reproducibility. Narrative Dominance (ND) measures how prominently vendors appear in AI-generated market discussions, while Sentiment captures overall perception quality. Scores are normalized through consensus scoring with variance tracking and outlier suppression. This snapshot enables objective, repeatable comparison across editions.

Transparency & Reproducibility

Complete audit trail: report identifiers, LLM configurations, and exact prompts used

๐Ÿ” Report Metadata & Archive References

Click to expand
Report ID:
06fdbdfb-f8c0-460b-99c7-4a822edabd5e
Archive File Pattern:
06fdbdfb-f8c0-460b-99c7-4a822edabd5e_[model]_[run].json
Generated: December 06, 2025 (UTC)
Total LLM Runs: 5

๐Ÿค– LLM Model Configurations โ€” 5 models used

Click to expand
CLAUDE
Provider: anthropic
Model: claude-sonnet-4-20250514
Temperature: 0.1
Max Tokens: 8192
Runs: 3
Archive: 06fdbdfb-f8c0-460b-99c7-4a822edabd5e_claude_*.json
OPENAI
Provider: openai
Model: gpt-4o
Temperature: 0.1
Max Tokens: 8192
Runs: 3
Archive: 06fdbdfb-f8c0-460b-99c7-4a822edabd5e_openai_*.json
GEMINI
Provider: google
Model: gemini-2.0-flash
Temperature: 0.1
Max Tokens: 8192
Runs: 3
Archive: 06fdbdfb-f8c0-460b-99c7-4a822edabd5e_gemini_*.json
PERPLEXITY
Provider: perplexity
Model: sonar-pro
Temperature: 0.1
Max Tokens: 8192
Runs: 3
Archive: 06fdbdfb-f8c0-460b-99c7-4a822edabd5e_perplexity_*.json
DEEPSEEK
Provider: deepseek
Model: deepseek-chat
Temperature: 0.1
Max Tokens: 8192
Runs: 3
Archive: 06fdbdfb-f8c0-460b-99c7-4a822edabd5e_deepseek_*.json

๐Ÿง  AI Analyst Enhancement โ€” Professional content synthesis

Click to expand
โœจ Analyst Model: CLAUDE

This report includes AI-enhanced analyst content. After gathering raw data from all LLM models, an additional AI call synthesizes the findings into professional narratives, vendor spotlights, strategic insights, and market predictions.

Vendor Spotlights: 3
Strategic Insights: 4
Market Predictions: 3
Archive: 06fdbdfb-f8c0-460b-99c7-4a822edabd5e_claude_0.json
Prompt Template: report_analyst.yaml
The analyst prompt ingests all vendor positions, scores, and initial findings to generate comprehensive professional content for the full PDF report.

๐Ÿ“ Category Analysis Prompt Template

Click to expand
# Market Category Analysis Request

## Category: Marathon Running Shoes

The marathon running shoe market exhibits characteristics of a mature category with established hierarchies and high barriers to entry. The top three vendors (Nike, Adidas, ASICS) control the narrative visibility landscape with scores above 86, while the remaining 17 vendors struggle below 62, indicating significant market concentration. This concentration reflects the importance of brand recognition, distribution scale, and marketing investment in driving consumer awareness and consideration.

Consumer sentiment patterns reveal interesting dynamics, with premium positioning generally correlating with higher sentiment scores. Nike's exceptional 95.0 sentiment score demonstrates successful premium positioning, while mid-tier brands like Puma (62.9 sentiment, 24.4 ND) show that positive consumer perception doesn't automatically translate to market visibility. The market also shows evidence of specialization premiums, with running-focused brands like Brooks achieving leadership positions despite smaller overall scale compared to diversified athletic companies.

Please provide a comprehensive analysis of the **Marathon Running Shoes** market. 

**Important**: Analyze this category based on what it actually represents. This could be:
- A software/technology market (if the category name suggests software, platforms, or technology)
- A services market (consulting, banking, healthcare, etc.)
- A product market (consumer goods, industrial products, etc.)
- An institutional market (banks, universities, hospitals, etc.)
- Any other market type that the category name implies

Let the category name and description guide your interpretation. Do NOT assume this is a software market unless the category explicitly indicates software or technology.

Structure your response as JSON with the following sections:

### Required JSON Structure:

```json
{{{{
  "market_overview": {{{{
    "market_type": "Software|Services|Products|Institutions|Hybrid|Other",
    "summary": "2-3 paragraph overview of the current market state",
    "market_size_estimate": "Estimated market size if known",
    "growth_trajectory": "Growth trends and projections",
    "key_drivers": ["List of key market drivers"],
    "key_challenges": ["List of key challenges"],
    "geographic_context": "Geographic focus if applicable (e.g., Canada, Global, US)"
  }}}},
  "vendors": [
    {{{{
      "name": "Vendor/Company/Institution Name",
      "position": "Leader|Challenger|Niche Player|Emerging",
      "recommendation_score": 8.5,
      "strengths": ["Strength 1", "Strength 2"],
      "weaknesses": ["Weakness 1", "Weakness 2"],
      "best_for": ["Use case 1", "Customer segment 1"],
      "notable_attributes": ["Key differentiator 1", "Key differentiator 2"],
      "market_segment": "Enterprise|Consumer|SMB|Premium|Mass Market|All",
      "summary": "Brief 1-2 sentence description"
    }}}}
  ],
  "competitive_analysis": {{{{
    "must_have_attributes": ["Essential attributes all players should have"],
    "differentiators": ["What separates leaders from others"],
    "emerging_trends": ["New capabilities or offerings gaining traction"],
    "baseline_expectations": ["Basic offerings expected by all customers"]
  }}}},
  "customer_guidance": {{{{
    "evaluation_criteria": ["Key factors to consider when choosing"],
    "common_pitfalls": ["Mistakes to avoid"],
    "by_segment": {{{{
      "enterprise_institutional": "Guidance for large organizations",
      "mid_market": "Guidance for mid-sized organizations or customers",
      "consumer_smb": "Guidance for consumers or small businesses"
    }}}}
  }}}},
  "trends": {{{{
    "rising": ["Trends gaining momentum"],
    "declining": ["Trends losing relevance"],
    "emerging": ["New trends to watch"]
  }}}}
}}}}
```

### Analysis Guidelines:

1. **Market Interpretation**: First determine what type of market this is based on the category name. For example:
   - "Retail Banking in Canada" = Financial services/institutions market
   - "Customer Data Platforms" = Software/technology market
   - "Corporate Gifting" = Products/services market
   - "Expense Management Software" = Software market
   - "Luxury Hotels in Europe" = Services/hospitality market

2. **Player Coverage**: Include at least 10-15 relevant players (vendors, companies, institutions, brands) if the category has that many significant participants. Prioritize by market presence and relevance.

3. **Objectivity**: Provide balanced assessments. Every player has strengths AND weaknesses - include both.

4. **Specificity**: Be specific about offerings, use cases, and recommendations. Avoid generic statements.

5. **Recommendation Scores**: Use a 1-10 scale where:
   - 9-10: Clear leader, recommended for most use cases
   - 7-8: Strong option for specific use cases
   - 5-6: Viable but with notable limitations
   - 3-4: Limited applicability
   - 1-2: Not recommended for most customers

6. **Position Definitions**:
   - **Leader**: High market presence + broadly recommended + strong reputation
   - **Challenger**: High visibility but specific concerns, limitations, or emerging status
   - **Niche Player**: Strong in specific segments but limited broader appeal
   - **Emerging**: Newer entrants or players showing growth potential

7. **Context Sensitivity**: If the category has a geographic focus (e.g., "in Canada", "in Europe"), ensure your analysis reflects that specific market context.

8. **No fabrication / domains**: Do NOT invent vendors or website domains. If a website/domain is unknown, omit it or set it to null/""; prefer well-known, real vendors only.



Please provide your analysis in valid JSON format only, without any markdown code fences or additional text.