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Competitive Intelligence & Analysis

Capability Slug: competitor_analysis Plan Tier: Command Credit Cost: 10 / 12 / 15 credits per run (varies by analysis type) Category: Intelligence & Attribution Default mode: listing_comparison

Overview

Competitive Intelligence & Analysis is the AI synthesis layer for competitor data you've already gathered. Pass in an AWS Marketplace listing dump, scraped content, a pricing page, or a structured competitor profile, and the capability returns one of five structured outputs depending on which mode you run.

The capability is deliberately data-agnostic. It does not scrape, does not call a marketplace data feed, and does not have a built-in competitor database. You bring the data; Claude finds the patterns, gaps, and recommended responses.

How this differs from LinkedIn Ad Intelligence

LinkedIn Ad Intelligence (linkedin_ad_intelligence) pulls live competitor ads from the LinkedIn Ad Library API and runs a Claude-powered teardown — real data, narrow scope (ads only). Competitor Analysis is broader (listings, content, positioning, pricing, GTM) but runs on whatever data you bring. Use both: LinkedIn Ad Intelligence for the LinkedIn ad slice, Competitor Analysis for everything else.

The five analysis modes

Mode Credits What it answers
listing_comparison (default) 12 "How does our AWS Marketplace listing stack up against this competitor's?"
content_monitoring 10 "What has this competitor been publishing across channels, and what does it mean for us?"
positioning_analysis 15 "Where can we differentiate? Where are they vulnerable? Where's the white space?"
gtm_response 15 "Competitor just did X. What's the response playbook?"
pricing_intelligence 10 "How does our pricing compare on model, tiers, and feature gating?"

All modes run on Claude 3 Sonnet. Token caps and temperatures vary: analytical modes use 0.3 temperature; positioning and gtm_response use 0.4-0.5 for more strategic creativity.

What listing_comparison returns

A side-by-side AWS Marketplace listing comparison across 10 components: title, short description, long description, highlights, images/videos, pricing, categories, customer reviews, support options, free trial/POC offer.

{
  "comparison": [
    {
      "component": "Product Title",
      "your_listing": "...",
      "their_listing": "...",
      "winner": "you|them|tie",
      "notes": "..."
    }
  ],
  "your_advantages": ["...", "..."],
  "their_advantages": ["...", "..."],
  "recommendations": ["...", "..."]
}

AWS Marketplace-specific axes are scored too: ISV Accelerate eligibility positioning, Private Offer messaging, integration partnerships highlighted, AWS service integrations, co-sell alignment messaging.

What content_monitoring returns

Multi-channel content fingerprinting across the channels you provide data for: AWS Marketplace listing, company blog, LinkedIn, Twitter/X, YouTube, case studies, press releases, webinars/events.

{
  "activity_summary": "...",
  "recent_changes": [
    {
      "channel": "blog|linkedin|...",
      "what_changed": "...",
      "date": "..."
    }
  ],
  "alerts": [
    {
      "trigger": "major_product_update|pricing_change|partnership|...",
      "what_changed": "...",
      "strategic_implication": "...",
      "recommended_response": "...",
      "urgency": "high|medium|low"
    }
  ],
  "strategic_implications": ["...", "..."]
}

The alert structure is the most actionable output — each alert has an explicit trigger type, an urgency level, and a recommended response, so it can flow directly into a competitive intelligence dashboard or alert pipeline.

What positioning_analysis returns

Positioning analysis across seven dimensions (target market, value proposition, product category, pricing strategy, AWS integration, GTM, brand personality), plus AWS-Marketplace-specific positioning (channel preference, Private Offer positioning, co-sell messaging, AWS partnership level).

{
  "positioning_analysis": [
    {
      "dimension": "Target Market",
      "their_positioning": "...",
      "evidence": ["..."]
    }
  ],
  "differentiation_opportunities": [
    {
      "opportunity": "...",
      "rationale": "...",
      "execution_hint": "..."
    }
  ],
  "positioning_recommendations": ["...", "..."]
}

Useful as input to a brand-voice refresh, a marketplace listing rewrite, or a category-creation play.

What gtm_response returns

Pass a competitor_action parameter (e.g., "Datadog launched a new observability product targeting our segment") and get back a ready-to-hand-off response playbook:

{
  "threat_assessment": {
    "severity": "high|medium|low",
    "time_sensitivity": "...",
    "customer_impact": "...",
    "market_perception_impact": "..."
  },
  "response_strategy": "Direct counter|Differentiate|Ignore + rationale",
  "execution_plan": {
    "sales_enablement": ["talk tracks", "battlecards"],
    "marketing_response": ["content", "campaigns"],
    "product_roadmap_implications": ["..."],
    "partner_aws_coordination": ["..."],
    "marketplace_actions": {
      "listing_updates": ["..."],
      "pricing_adjustments": ["..."],
      "private_offer_strategy": "...",
      "co_sell_positioning_changes": ["..."]
    },
    "content_messaging": {
      "competitive_positioning_statements": ["..."],
      "feature_comparison_updates": ["..."],
      "customer_communication_templates": ["..."],
      "sales_objection_handling": ["..."]
    }
  },
  "timeline": [
    { "milestone": "...", "owner": "...", "deadline": "..." }
  ]
}

This is the most opinionated mode — it presents three response options (direct counter / differentiate / ignore) with rationale, picks one as the recommended approach, then breaks the recommendation down to executable steps.

What pricing_intelligence returns

Pricing model, tier structure, feature gating, price points at key usage levels, discounting practices, and AWS Marketplace-specific pricing context (AWS credits, committed spend, Private Offer flexibility).

{
  "pricing_comparison": [
    {
      "tier": "...",
      "your_price": "...",
      "their_price": "...",
      "feature_delta": ["..."]
    }
  ],
  "value_for_money_assessment": "...",
  "anchoring_observations": ["..."],
  "marketplace_specific": {
    "private_offer_flexibility": "...",
    "aws_credits_messaging": "...",
    "committed_spend_strategy": "..."
  },
  "recommendations": ["..."]
}

Useful as input to a pricing review or as a deal-desk reference for negotiating against a known competitor.

Required and optional parameters

Parameter Required Description
analysis_type Yes One of listing_comparison, content_monitoring, positioning_analysis, gtm_response, pricing_intelligence
competitor_data Recommended Free-form or structured competitor data (listing dump, scraped content, pricing page, etc.). String or JSON-serializable array both work.
your_data Recommended for listing_comparison and pricing_intelligence Your own corresponding data for the side-by-side comparison
competitor_action Required for gtm_response One-line description of what the competitor did (e.g. "Launched new tier at $99/month")
channels Optional for content_monitoring Array of channels you have data for (defaults to all from the prompt)

Brand-voice context (company.name, company.industry, target_audience) is pulled from your company profile via BrandContextBuilder.

Composing with upstream capabilities

The capability is deliberately data-agnostic so it composes with other capabilities that produce competitor data:

Upstream capability Output you can feed in Recommended mode
LinkedIn Ad Intelligence (linkedin_ad_intelligence) Live competitor ad teardown positioning_analysis or content_monitoring
AWS Innovation Monitor (aws_innovation_monitor) Surfaced competitor announcements gtm_response
Marketplace Awareness (marketplace_awareness) Article-level GTM analysis gtm_response
SEO Intelligence (seo_intelligence) Competitor traffic, keywords, tech stack positioning_analysis

Run the upstream capability, take the structured output, pass it as competitor_data to this capability for the next layer of analysis.

When to use it

Scenario Recommended mode
Quarterly listing tune-up — how do we stack up? listing_comparison
Competitive intelligence brief for sales / executive readout content_monitoring
Positioning workshop prep positioning_analysis
Reactive GTM after a competitor announcement gtm_response
Pricing review or deal-desk reference pricing_intelligence
LinkedIn ad teardown specifically LinkedIn Ad Intelligence — different capability, real-time API

It is not:

  • A scraper. The capability does not fetch competitor websites, AWS Marketplace listings, or social channels. Bring your own data.
  • A persistent competitive intelligence database. Each run is a discrete analysis; outputs are not stored as a comparable historical series.
  • A replacement for human strategy. The gtm_response mode produces a playbook starting point — review and adapt before executing.

API access

Exposed through the agent runtime as competitor_analysis. Partner API keys scoped with view_marketing_analytics and manage_listings plus the agent capability slug can run all five analysis modes. See Partner API Capabilities.

See also

Capability slug: competitor_analysis · Handler: CompetitorAnalysisCapability · Model: Claude 3 Sonnet · Schema: CompetitorAnalysisSchema · Input: user-provided competitor data + brand-voice context