diagnosis-competition

name

diagnosis-competition

description

Use when you need to track competitor dynamics and develop response strategies. Competitor Dynamic Tracking & Response, monitors competitor feature changes, evaluates dynamic changes in own advantages, generates response strategies, and tracks effectiveness. Keywords: competitor tracking, competitor analysis, competitor monitoring, feature changes, competitive analysis, competitor changes, competitor dynamics, competitor changed, competitor made a move.

Competitor Dynamic Tracking & Response 🤖

Core Principles

1. Feature changes are signals, not noise: Every competitor feature change reflects their strategic intent; the key is identifying intent, not listing changes
2. Advantages are dynamic, not static: Competitive advantages are constantly changing; yesterday's lead doesn't guarantee tomorrow's lead
3. Response strategies must be trackable: The value of a strategy lies in execution and effectiveness verification, not停留在 the recommendation level

Interaction Mode

🤖→👤 AI suggests, human approves

Input

Input Item	Type	Required	Source	Description
Competitor data	JSON	Yes	Competitor monitoring system → Competitor data	Feature list, version updates, user reviews
Own data	JSON	Yes	Product data platform → Own data	Feature list, user reviews, satisfaction
Market data	JSON	○	Industry reports → Market data	Industry trends, user demand changes
Historical tracking	JSON	○	output/pm-monitoring/diagnosis-competition/Historical reports	Historical competitor analysis reports

Execution Steps

Step 1: Feature Change Monitoring [Conditional]

Goal: Identify recent competitor feature changes

Monitoring Channels:

• Competitor websites / changelogs
• App store update records
• User review aggregation
• Social media discussions
• Industry media coverage

Change Type Classification:

Type	Definition	Attention Level
New feature	New capability unique to competitor	P0
Feature optimization	Experience/performance improvement of existing feature	P1
Feature retirement	Feature no longer supported	P2
Pricing adjustment	Pricing strategy change	P1
Ecosystem expansion	Partner/integration changes	P2

Output Format:

feature_changes:
  - competitor: {name}
    change_type: new_feature | enhancement | deprecation | pricing | ecosystem
    feature_name: {name}
    change_date: {date}
    description: {description}
    user_reaction:
      sentiment: positive | negative | neutral
      volume: {count}
      key_themes: [themes]
    source: {source_url}
    priority: P0 | P1 | P2

Step 2: Advantage Dynamic Assessment [Core]

Goal: Evaluate changes in own strengths and weaknesses relative to competitors

Assessment Dimensions:

Dimension	Metric	Data Source
Feature leadership	Unique feature count vs competitor	Feature comparison matrix
User experience	Rating comparison, feature usability	App Store/Google Play
Performance metrics	Response time, stability comparison	Third-party reviews
Value perception	Price-performance ratio, brand awareness	User research
Ecosystem richness	Integration count, API openness	Technical documentation

Assessment Methods:

• Radar chart multi-dimensional comparison
• Trend line change analysis
• User review semantic analysis

Output Format:

advantage_changes:
  period: {start} to {end}
  dimensions:
    - dimension: feature_leadership
      previous_status: leading | parity | lagging
      current_status: leading | parity | lagging
      change: improved | unchanged | declined
      delta: {description}
    - dimension: user_experience
      previous_status: leading | parity | lagging
      current_status: leading | parity | lagging
      change: improved | unchanged | declined
      delta: {description}
  overall_trend:
    direction: gaining | holding | losing
    confidence: {percentage}
  critical_changes:
    - description: "Competitor X launched feature Y, narrowing the feature gap"
      impact_level: high | medium | low

Step 3: Response Strategy Generation [Core]

Goal: Generate response strategies based on competitor dynamics

Strategy Types:

Strategy Type	Applicable Scenario	Execution Requirements
Accelerate	Competitor capturing market share	Rapid iteration, high priority
Differentiate	Competitor feature homogenization	Find unique value points
Defend	Competitor threatening core features	Strengthen moat
Monitor	Impact uncertain	Continuous monitoring, reserve plans

Strategy Generation Rules:

response_strategy:
  - competitor_change:
      feature: {feature_name}
      change_type: new_feature
    recommended_approach: accelerate | differentiate | defend | monitor
    action:
      title: {action_title}
      description: {description}
      options:
        - option: aggressive
          description: "Fast follow, feature priority"
          timeline: 2-4 weeks
          priority: P0
          resource_needed: {story_points}
        - option: balanced
          description: "Differentiated implementation"
          timeline: 4-8 weeks
          priority: P1
          resource_needed: {story_points}
        - option: conservative
          description: "Continue observing, wait for more information"
          timeline: tbd
          priority: P2
    selected_option: {option}
    tracking:
      status: planned | in_progress | completed | dismissed
      milestones: [...]

Step 4: Effectiveness Tracking [Conditional]

Goal: Track the execution effectiveness of response strategies

Tracking Metrics:

• Strategy execution completion rate
• User feedback after feature launch
• Market share changes
• User rating changes

Tracking Report:

effect_tracking:
  strategy_id: {id}
  execution:
    planned_date: {date}
    actual_date: {date}
    completed: true | false
  outcome:
    user_feedback:
      sentiment_change: {delta}
      volume: {count}
    market_impact:
      share_change: {delta}
      new_users: {count}
    competitive_position:
      status_change: improved | unchanged | declined

Output Depth Classification

Depth Level	Output Scope	Description
quick	Competitor diagnosis and feature comparison	Core conclusions + minimum viable output
standard	Complete output (current default)	Complete output, including all Step outputs
deep	Complete diagnosis + competitor strategic inference + differentiation opportunity identification + competitive response roadmap	Complete output + extended analysis + deep inference

Output

Output File Path: output/pm-monitoring/diagnosis-competition/ Output Schema:

{
  "type": "object",
  "required": ["report_id", "feature_changes", "advantage_changes", "response_strategy"],
  "properties": {
    "report_id": {"type": "string", "description": "Unique report identifier"},
    "generated_at": {"type": "string", "description": "Generation time"},
    "period": {"type": "object", "description": "Analysis period, including start and end time"},
    "feature_changes": {"type": "object", "description": "Feature change summary, including total count and P0/P1 counts"},
    "advantage_changes": {"type": "object", "description": "Advantage changes, including gaining/holding/losing dimensions"},
    "response_strategy": {"type": "array", "description": "Response strategy list, including competitor, feature, and priority"}
  }
}

├── {date}/
│   ├── feature_changes.yaml
│   ├── advantage_changes.yaml
│   ├── response_strategy.yaml
│   └── effect_tracking.yaml
└── latest/
    └── competition_report.md

Competitor Response Output Format

competition_response:
  report_id: {uuid}
  generated_at: {ISO8601}
  period: {start} to {end}
  feature_changes:
    total: {count}
    p0_count: {count}
    p1_count: {count}
  advantage_changes:
    gaining: [{dimensions}]
    holding: [{dimensions}]
    losing: [{dimensions}]
  response_strategy:
    - id: STR-001
      competitor: {name}
      feature: {feature}
      approach: accelerate
      action: {description}
      timeline: {weeks}
      priority: P0
      tracking:
        status: planned

Decision Rules

Scenario	Decision Rule
Competitor launches disruptive feature	Immediately generate response strategy, mark P0
Advantage gap narrows < 10%	Generate defense strategy
Multiple competitors homogenizing	Trigger differentiation strategy generation
Strategy execution delayed	Re-evaluate priority
Major market environment change	Re-evaluate overall strategy

Quality Checks

P0 Checks (must pass for quick/standard/deep)

• Competitor coverage completeness ≥ 90%
• Feature change identification timeliness ≤ 7 days

P1 Checks (must pass for standard/deep)

• Advantage assessment consistent with actual market feedback
• Strategy executability ≥ 80%
• Effectiveness tracking coverage 100%
• Report completeness (all dimensions)

P2 Checks (must pass for deep only)

• Extended analysis complete (deep inference and roadmap generated)
• Decision records complete (key decisions have rationale and alternatives)

Degradation Strategy

Upstream File Missing Degradation Plan

Missing Upstream Input	Degradation Plan	Output Impact
Competitor data	User provides competitor name list, AI tracks competitor dynamics based on public information and industry knowledge	AI knowledge-based competitor tracking report, data sources and confidence levels need to be annotated
Own data	User provides own product feature list and user reviews, AI performs manual comparison	User input-based strength/weakness analysis, lacking data validation
Market data	Skip industry trend analysis, strategy recommendations based on feature comparison only	Strategy recommendations without industry trends
Historical tracking	Skip historical trend analysis, output current snapshot only	Competitor status snapshot report, no trend comparison

Data Acquisition Notes

When upstream files are missing, obtain necessary data through the following methods:

1. Competitor data missing: Request user to provide competitor name list, AI will track competitor feature dynamics based on public information (websites, app stores, industry reports, etc.) and AI knowledge base, annotating data sources and confidence levels in the output
2. Own data missing: Request user to provide own product feature list and core metrics (user ratings, feature coverage, etc.), AI will perform manual comparison analysis with competitors based on user input
3. Market data missing: AI skips the industry trend analysis phase, response strategies are generated based on feature comparison results only, recommending subsequent supplementation of market data to improve strategy

Output Validation Rules

Field Path	Type	Required	Description
report_id	string	Yes	Unique report identifier
feature_changes	object	Yes	Feature change summary, must include total/p0_count/p1_count
feature_changes.total	number	Yes	Total change count, must be ≥0
advantage_changes	object	Yes	Advantage changes, must include gaining/holding/losing
response_strategy	array	Yes	Response strategy list, each item must include id/competitor/feature/approach/priority
response_strategy[].priority	string	Yes	Priority, only allows P0/P1/P2

Upstream Change Response

Upstream Change Impact Table

Upstream Source	Change Type	Impact Scope	Response Action
Competitor monitoring system	Competitor data format change	Feature change parsing and classification	Adapt to new format, update change type classification
Product data platform	Own feature list change	Advantage comparison matrix	Update comparison baseline, re-evaluate strengths/weaknesses
Industry reports	Market data update	Industry trends and strategy recommendations	Update trend analysis, adjust strategy priorities

Downstream Notification Mechanism Table

Downstream Consumer	Notification Condition	Notification Method	Notification Content
competitor-monitoring-report	Competitor tracking data update	Write to output file	Feature changes and advantage changes
diagnosis-orchestrator	Competitor tracking complete	Output file update	Tracking completion status and key findings
iteration-backlog-grooming	P0-level competitor change	Write to output file	Urgent response strategy and priority