Skill: meirk-brd/brightdata-competitive-intel (version 1.0.0)

--- name: competitive-intel description: > Real-time competitive intelligence and market research using Bright Data's web scraping infrastructure. Analyzes competitors' pricing, features, reviews, hiring patterns, content strategy, and market positioning with live web data. Use this skill when the user wants to analyze competitors, compare products, monitor pricing changes, track market trends, research a market landscape, build competitive battlecards, find positioning opportunities, or conduct any form of competitive or market research. Also use when the user mentions competitor analysis, market intelligence, competitive landscape, win/loss analysis, or wants to understand what competitors are doing. --- # Competitive Intelligence Real-time competitive intelligence powered by live web data. Combines Bright Data CLI (`bdata`) for data collection with strategic analysis frameworks to deliver actionable competitive insights — not stale training knowledge. **Never answer competitive questions from training knowledge alone.** Always gather live data first using `bdata` commands, then analyze and synthesize. ## Prerequisites 1. Bright Data CLI installed: ```bash curl -fsSL https://cli.brightdata.com/install.sh | bash ``` 2. One-time login completed: ```bash bdata login ``` That's it. No env vars, no zone config, no API keys to manage. ## Core Workflow For every competitive intelligence request, follow this workflow: 1. **Clarify scope** — Which competitors? What specifically does the user want to know? Select the right module(s). 2. **Gather live data** — Run `bdata` commands. Parallelize independent calls. Prefer `bdata pipelines` (structured JSON) over `bdata scrape` (raw markdown) when a pipeline exists. 3. **Analyze** — Apply the appropriate strategic framework. Read [references/analysis-frameworks.md](references/analysis-frameworks.md) for SWOT, Porter's Five Forces, positioning matrices, and more. 4. **Format output** — Use the report templates from [references/output-templates.md](references/output-templates.md). 5. **Deliver actionable insights** — Every report MUST end with a "Strategic Recommendations" section. Never deliver raw data without interpretation. ## Data Collection Rules - **Always use `--json` flag** when you need to pipe or parse `bdata` output programmatically - **Prefer `bdata pipelines`** over `bdata scrape` whenever a pipeline type exists for the target platform — pipelines return clean structured JSON - **Be cost-efficient** — A snapshot should use 3-8 `bdata` calls, not 50. Scrape what you need. - **Parallelize** — Run independent `bdata` calls in parallel using multiple Bash tool calls in a single response - **Handle failures gracefully** — If a page is gated or returns empty, say so and try the fallback. Never hallucinate data to fill gaps. - **Cite every data point** — Include source URLs for everything. Users must be able to verify. For the full mapping of intelligence needs to `bdata` commands, read [references/data-source-guide.md](references/data-source-guide.md). For interpreting raw data as strategic signals, read [references/industry-signals.md](references/industry-signals.md). --- ## Analysis Modules ### 1. Competitor Snapshot **When to use**: User asks to analyze, profile, or understand a specific competitor. **Data gathering**: ```bash # Step 1: Discover competitor's website and recent news bdata search "[competitor name]" --json # Step 2: Scrape key pages (run in parallel) bdata scrape [competitor-url] # Homepage — positioning, messaging bdata scrape [competitor-url]/pricing # Pricing tiers and model bdata scrape [competitor-url]/about # Team, mission, history (try /about, /about-us, /company) # Step 3: Structured data enrichment (if URLs available) bdata pipelines crunchbase_company "[crunchbase-url]" # Funding, investors, employee count bdata pipelines linkedin_company_profile "[linkedin-url]" # Employee count, growth, locations ``` **Analysis**: Synthesize into a structured profile. Identify positioning, target audience, key claims, strengths, and vulnerabilities. Compare to user's product if context is available. **Output**: Use the Competitor Snapshot template from [references/output-templates.md](references/output-templates.md). --- ### 2. Pricing Intelligence **When to use**: User wants to compare pricing, understand pricing models, or find pricing positioning opportunities. **Data gathering**: ```bash # Scrape pricing pages for each competitor (run in parallel) bdata scrape [competitor-a-url]/pricing bdata scrape [competitor-b-url]/pricing bdata scrape [competitor-c-url]/pricing # For e-commerce products bdata pipelines amazon_product "[amazon-url]" bdata pipelines walmart_product "[walmart-url]" # Supplementary: third-party pricing breakdowns bdata search "[competitor] pricing review" --json ``` **Analysis**: Extract plan names, prices, feature lists, and limits from each page. Normalize into a comparison matrix. Identify pricing model types (per-seat, usage-based, freemium, enterprise-only). Flag positioning signals and recommend opportunities. **Output**: Use the Pricing Intelligence template from [references/output-templates.md](references/output-templates.md). --- ### 3. Review Intelligence **When to use**: User wants to understand customer sentiment, find competitor pain points, or identify exploitable gaps. **Data gathering**: ```bash # Find review pages via search bdata search "[competitor] site:g2.com" --json bdata search "[competitor] site:capterra.com" --json # Scrape review pages bdata scrape [g2-url] bdata scrape [capterra-url] # Structured review data (use when direct URLs are available) bdata pipelines google_maps_reviews "[google-maps-url]" 30 bdata pipelines amazon_product_reviews "[amazon-url]" bdata pipelines google_play_store "[play-store-url]" bdata pipelines apple_app_store "[app-store-url]" ``` **Analysis**: Categorize sentiment (positive/neutral/negative). Extract top praised features, top complaints, and feature requests. Identify comparison mentions ("switched from X", "better than Y"). Complaints are the user's positioning opportunity. **Output**: Use the Review Intelligence template from [references/output-templates.md](references/output-templates.md). --- ### 4. Hiring Signal Analysis **When to use**: User wants to infer a competitor's strategic direction from their hiring patterns. **Data gathering**: ```bash # Find LinkedIn company page bdata search "[competitor] linkedin company" --json # Get structured job listings bdata pipelines linkedin_job_listings "[linkedin-company-url]" # Fallback: scrape careers page directly bdata search "[competitor] careers" --json bdata scrape [careers-url] ``` **Analysis**: Categorize roles by department. Analyze hiring velocity (scaling vs. stable vs. contracting). Identify technology signals from job descriptions. Look for geographic expansion signals. Interpret seniority mix (hiring leaders = new initiative; hiring ICs = scaling existing). **Output**: Use the Hiring Signal Analysis template from [references/output-templates.md](references/output-templates.md). --- ### 5. Content & SEO Battle **When to use**: User wants to understand competitors' content strategy or search positioning for specific keywords. **Data gathering**: ```bash # Check SERP rankings for target keywords (run in parallel) bdata search "[keyword 1]" --json bdata search "[keyword 2]" --json bdata search "[keyword 3]" --json # Estimate competitor's indexed content bdata search "site:[competitor.com]" --json # Scrape blog/content pages bdata scrape [competitor-url]/blog bdata scrape [top-ranking-article-url] ``` **Analysis**: Map which competitors rank for which keywords. Estimate content volume and publishing frequency. Identify topic clusters each competitor invests in. Find content gaps — topics nobody covers well that the user could own. **Output**: Use the Content & SEO Battle template from [references/output-templates.md](references/output-templates.md). --- ### 6. Market Landscape Map **When to use**: User wants to understand all players in a market, find white space, or map the competitive landscape. **Data gathering**: ```bash # Discover players via multiple search queries (run in parallel) bdata search "[industry] companies" --json bdata search "best [product category] tools" --json bdata search "[product category] alternatives" --json # Scrape category/comparison pages bdata scrape [g2-category-url] # Quick snapshot of each discovered competitor bdata scrape [competitor-1-url] bdata scrape [competitor-2-url] # ... for each key player (limit to top 8-10) # Enrich key players with funding/size data bdata pipelines crunchbase_company "[crunchbase-url]" ``` **Analysis**: Categorize players by tier (enterprise, mid-market, SMB, open-source). Build a positioning map (e.g., price vs. feature breadth). Identify white space — underserved segments or positioning no one owns. Note market trends, recent entrants, and consolidation signals. **Output**: Use the Market Landscape Map template from [references/output-templates.md](references/output-templates.md). --- ## Multi-Module Analysis When the user asks for a comprehensive competitive analysis (e.g., "full battlecard", "deep dive", "board meeting prep"), combine multiple modules: 1. Start with **Competitor Snapshot** for each competitor 2. Add **Pricing Intelligence** for comparison 3. Add **Review Intelligence** for customer sentiment 4. Optionally add **Hiring Signals** and **Content & SEO** for strategic depth 5. Wrap everything in the **Executive Summary** template from [references/output-templates.md](references/output-templates.md) For full battlecards, use the **Competitive Battlecard** template. ## Choosing the Right Module | User says... | Module to use | |-------------|--------------| | "Analyze [competitor]", "Tell me about [company]" | Competitor Snapshot | | "Compare pricing", "How much does [X] cost" | Pricing Intelligence | | "What do customers think", "Reviews of [X]", "Pain points" | Review Intelligence | | "What are they hiring for", "Job postings", "Where are they expanding" | Hiring Signal Analysis | | "How do they rank", "Their content strategy", "SEO" | Content & SEO Battle | | "Who are the players", "Market landscape", "Competitive landscape" | Market Landscape Map | | "Full battlecard", "Deep competitive analysis", "Board prep" | Multi-Module (combine all) | ## Output Quality Standards 1. **Every data point must have a source URL** — no unattributed claims 2. **Separate facts from analysis** — clearly distinguish scraped data from Claude's interpretation 3. **End with "So What?"** — every report must have actionable strategic recommendations 4. **Be honest about gaps** — if data is unavailable, say so. Never fill gaps with training knowledge presented as live data. 5. **Date-stamp the analysis** — include "Data collected on [date]" so users know freshness

path: evals/evals.json
content: {
  "skill_name": "competitive-intel",
  "evals": [
    {
      "id": 1,
      "prompt": "Analyze Notion as a competitor. I'm building a project management tool for small teams.",
      "expected_output": "Comprehensive competitor snapshot including Notion's pricing, positioning, team size, and strategic recommendations",
      "expectations": [
        "Claude uses bdata CLI commands (bdata scrape, bdata search, or bdata pipelines) to gather data — not training knowledge alone",
        "The output includes Notion's current pricing tiers with actual dollar amounts scraped from their pricing page",
        "The output identifies Notion's target audience and positioning based on scraped homepage content",
        "The output includes data from at least 2 different sources (e.g., website + Crunchbase or LinkedIn)",
        "The output provides actionable positioning recommendations specific to small team project management",
        "The output includes a Sources section with URLs of pages that were scraped",
        "The output follows the Competitor Snapshot template structure"
      ]
    },
    {
      "id": 2,
      "prompt": "Compare pricing between Slack, Microsoft Teams, and Discord for business communication.",
      "expected_output": "Pricing comparison table with plan tiers, features, and strategic analysis",
      "expectations": [
        "Claude scrapes the pricing pages of all three competitors using bdata scrape commands",
        "The output includes a comparison matrix/table with all three competitors side by side",
        "Pricing data includes specific dollar amounts per plan tier sourced from live scraping",
        "The output identifies each competitor's pricing model (per-seat, freemium, etc.)",
        "The output includes a Positioning Opportunities section with actionable recommendations",
        "The output follows the Pricing Intelligence Report template structure"
      ]
    },
    {
      "id": 3,
      "prompt": "What are people saying about Figma vs Canva? I want to understand which pain points I could exploit.",
      "expected_output": "Review intelligence report with sentiment analysis and pain point extraction for both products",
      "expectations": [
        "Claude uses bdata to find and scrape review pages (G2, Capterra, app stores, or similar)",
        "Pain points are identified and categorized for both Figma and Canva",
        "The output includes actual user quotes as evidence for claims",
        "The output identifies exploitable gaps — specific weaknesses the user could target",
        "The output follows the Review Intelligence Report template structure",
        "The output includes a Strategic Recommendations section"
      ]
    },
    {
      "id": 4,
      "prompt": "What can we learn from Stripe's hiring patterns? Are they expanding into new areas?",
      "expected_output": "Hiring signal analysis with strategic interpretation of Stripe's job postings",
      "expectations": [
        "Claude uses bdata pipelines or bdata scrape to gather job posting data from LinkedIn or Stripe's careers page",
        "Roles are categorized by department (engineering, sales, marketing, etc.)",
        "The output interprets hiring patterns as strategic signals (tech bets, geographic expansion, product direction)",
        "The output follows the Hiring Signal Analysis template structure",
        "The output includes a Strategic Recommendations section"
      ]
    },
    {
      "id": 5,
      "prompt": "Map out the competitive landscape for API documentation tools.",
      "expected_output": "Market landscape map with categorized players, positioning analysis, and white space identification",
      "expectations": [
        "Claude uses bdata search to discover competitors in the API documentation space",
        "At least 5 competitors are identified and categorized",
        "Players are organized by tier (enterprise, mid-market, SMB, open-source)",
        "The output identifies white space or underserved segments in the market",
        "Each competitor has a one-line positioning summary based on scraped website content",
        "The output follows the Market Landscape Map template structure"
      ]
    }
  ]
}


path: references/analysis-frameworks.md
content: # Analysis Frameworks

Apply these strategic frameworks to transform raw competitive data into actionable intelligence. Choose the framework that best fits the user's question and the data available.

## When to Use Each Framework

| Framework | Best For | Triggered By |
|-----------|----------|-------------|
| SWOT Analysis | Single competitor deep dive | Competitor Snapshot, Battlecard |
| Porter's Five Forces | Market-level competitive dynamics | Market Landscape Map |
| Positioning Matrix | Comparing multiple competitors visually | Market Landscape, Pricing Intelligence |
| Jobs-to-be-Done | Understanding why customers choose competitors | Review Intelligence |
| Blue Ocean Strategy | Finding uncontested market space | Market Landscape Map |
| Win/Loss Framework | Understanding competitive wins and losses | Review Intelligence, Battlecard |

---

## 1. SWOT Analysis

**Use when**: Profiling a single competitor in depth, or comparing your position against a competitor.

### How to Apply

From the scraped data, categorize findings into:

1. **Strengths** — What the competitor does well (sourced from: homepage messaging, positive reviews, high rankings, strong funding, fast hiring)
2. **Weaknesses** — Where they fall short (sourced from: negative reviews, missing features, pricing complaints, slow hiring, tech debt signals)
3. **Opportunities** — External factors they could exploit (sourced from: market trends, adjacent markets, new technologies, regulatory changes)
4. **Threats** — External risks they face (sourced from: new entrants, open-source alternatives, market commoditization, regulatory pressure)

### Output Format

```markdown
## SWOT Analysis: [Competitor]

| | Helpful | Harmful |
|--|---------|---------|
| **Internal** | **Strengths**: [list] | **Weaknesses**: [list] |
| **External** | **Opportunities**: [list] | **Threats**: [list] |

### Implications for Your Strategy
- Their strength in [X] means you should [differentiate on Y / match X as table stakes]
- Their weakness in [X] is your opportunity to [specific action]
- The market opportunity in [X] means [specific recommendation]
```

### Data Sources to Evidence
- Strengths: Homepage claims, funding data, positive reviews, SERP rankings
- Weaknesses: Negative reviews, feature gaps visible on pricing page, complaints on G2/Capterra
- Opportunities: Industry news, hiring patterns showing new directions
- Threats: Competitor discovery results showing new entrants, pricing pressure from alternatives

---

## 2. Porter's Five Forces

**Use when**: Analyzing overall market attractiveness and competitive dynamics, especially for Market Landscape analysis.

### How to Apply

Assess each force based on scraped evidence:

1. **Competitive Rivalry** (existing competitors)
   - How many players exist? (from market landscape search)
   - Are they well-funded? (from Crunchbase data)
   - Is there pricing pressure? (from pricing page comparisons)
   - Is growth slowing? (from hiring velocity analysis)

2. **Threat of New Entrants**
   - Are barriers to entry high or low? (technical complexity, capital requirements)
   - Are new players appearing? (from recent search results, recent Crunchbase entries)
   - Is open-source disrupting? (from GitHub presence)

3. **Threat of Substitutes**
   - What alternatives exist outside the direct category?
   - Are customers using manual processes or different tools?
   - Evidence from review mentions of alternatives

4. **Bargaining Power of Buyers**
   - Can customers easily switch? (from pricing models, data portability signals)
   - Are customers price-sensitive? (from review pricing complaints)
   - Is the market B2B or B2C?

5. **Bargaining Power of Suppliers**
   - Dependency on specific platforms, APIs, or infrastructure
   - Evidence from job postings (specific technology dependencies)

### Output Format

```markdown
## Porter's Five Forces: [Market/Industry]

| Force | Intensity | Evidence |
|-------|----------|---------|
| Competitive Rivalry | [High/Medium/Low] | [N] players identified, [funding levels], [pricing trends] |
| Threat of New Entrants | [High/Medium/Low] | [barriers], [recent entrants] |
| Threat of Substitutes | [High/Medium/Low] | [alternatives], [switching evidence] |
| Buyer Power | [High/Medium/Low] | [switching costs], [price sensitivity] |
| Supplier Power | [High/Medium/Low] | [dependencies], [platform risks] |

### Market Attractiveness: [High / Medium / Low]
[Summary interpretation and strategic implications]
```

---

## 3. Positioning Matrix (2x2)

**Use when**: Visually mapping competitors along two strategic dimensions, especially during Pricing Intelligence or Market Landscape analysis.

### How to Apply

1. Choose two axes that matter most to the user's market:
   - **Price** (low → high)
   - **Feature breadth** (narrow/focused → broad/all-in-one)
   - **Target segment** (SMB → Enterprise)
   - **Ease of use** (simple → complex/powerful)
   - **Customizability** (opinionated → flexible)

2. Place each competitor based on scraped evidence:
   - Price axis: from pricing page data
   - Feature axis: from product page / feature list scraping
   - Segment axis: from messaging and pricing model analysis

3. Identify the empty quadrant — that's potential white space.

### Output Format

```markdown
## Positioning Matrix: [Category]

**Axes**: [X-axis: e.g., Price (Low → High)] vs. [Y-axis: e.g., Feature Breadth (Focused → Comprehensive)]

```
              Comprehensive
                   │
  [Budget          │       [Enterprise
   All-in-one]     │        Suite]
   Company C       │       Company A
                   │
Low Price ─────────┼───────── High Price
                   │
  [Simple &        │       [Premium
   Affordable]     │        Specialist]
   Company D       │       Company B
                   │
               Focused
```

### White Space: [Quadrant description] — [Why it's an opportunity]
### Recommendation: [Where the user should position and why]
```

### Common Axis Pairs
- **SaaS products**: Price vs. Feature breadth
- **Developer tools**: Ease of use vs. Power/flexibility
- **E-commerce**: Price vs. Quality/brand
- **B2B services**: Self-serve vs. White-glove AND SMB vs. Enterprise

---

## 4. Jobs-to-be-Done (JTBD)

**Use when**: Analyzing reviews to understand why customers hire/fire competitors, especially during Review Intelligence analysis.

### How to Apply

From review data, identify:

1. **Functional jobs** — What task is the customer trying to accomplish?
   - Look for phrases: "I use [product] to...", "We needed...", "The main reason we..."

2. **Emotional jobs** — How does the customer want to feel?
   - Look for: "gives me confidence", "less stressful", "makes me look good"

3. **Social jobs** — How does the customer want to be perceived?
   - Look for: "my team loves", "impressed the board", "our clients notice"

4. **Hiring criteria** — What made them choose this product?
   - Look for: "we chose because", "what sold us", "the reason we switched"

5. **Firing criteria** — What would make them leave?
   - Look for: "considering switching", "frustrating because", "if they don't fix"

### Output Format

```markdown
## Jobs-to-be-Done Analysis: [Product/Category]

### Primary Jobs Customers Hire [Product] For
1. **[Job]** — Evidence: "[quote]" *(Source)*
2. **[Job]** — Evidence: "[quote]" *(Source)*

### Why Customers Hire (Switching Triggers)
- [Trigger 1]: "[quote about what pushed them to switch]"
- [Trigger 2]: "[quote]"

### Why Customers Fire (Churn Triggers)
- [Trigger 1]: "[quote about what's making them consider leaving]"
- [Trigger 2]: "[quote]"

### Underserved Jobs
Jobs customers mention but no competitor fully addresses:
1. **[Unmet job]** — Evidence: "[quote]"

### Implications
- [How to position your product to address these jobs]
- [Which underserved jobs represent the biggest opportunity]
```

---

## 5. Blue Ocean Strategy

**Use when**: Looking for uncontested market space during Market Landscape analysis, or when the user wants to find a unique position.

### How to Apply

Build an Eliminate-Reduce-Raise-Create (ERRC) grid based on competitor analysis:

1. **Eliminate** — Which factors the industry competes on should be eliminated?
   - Look for: features no one uses (from review data), legacy capabilities

2. **Reduce** — Which factors should be reduced below the industry standard?
   - Look for: over-engineered features, complexity that frustrates users (from reviews)

3. **Raise** — Which factors should be raised above the industry standard?
   - Look for: features customers love but want more of (from reviews)

4. **Create** — Which factors should the industry create that it's never offered?
   - Look for: unmet needs in reviews, feature requests, adjacent market innovations

### Output Format

```markdown
## Blue Ocean Analysis: [Category]

### ERRC Grid

| Eliminate | Reduce |
|-----------|--------|
| [Factor competitors invest in that customers don't value] | [Factor that's over-served relative to customer needs] |

| Raise | Create |
|-------|--------|
| [Factor customers want more of] | [Factor nobody offers yet] |

### Value Curve Comparison
| Factor | Industry Avg | Your Proposed Position | Rationale |
|--------|-------------|----------------------|-----------|
| [Factor 1] | [High/Med/Low] | [Your level] | [Why] |
| [Factor 2] | [High/Med/Low] | [Your level] | [Why] |

### Blue Ocean Opportunity
[Description of the uncontested market space and how to reach it]
```

---

## 6. Win/Loss Framework

**Use when**: Building competitive battlecards, or when the user wants to understand why customers choose one competitor over another. Most useful with Review Intelligence data.

### How to Apply

From reviews and competitive mentions, categorize:

1. **Win themes** — Why customers choose this competitor
   - Look for: "chose because", "best at", "switched to"

2. **Loss themes** — Why customers leave or don't choose
   - Look for: "switched from", "left because", "chose [other] instead"

3. **Trap questions** — Questions that expose competitor weaknesses
   - Derived from top pain points in negative reviews

4. **Objection handlers** — How to respond when prospect favors competitor
   - Derived from competitor's top strengths

### Output Format

```markdown
## Win/Loss Analysis: [Your Product] vs. [Competitor]

### Why We Win Against [Competitor]
| Win Theme | Evidence | Sales Talking Point |
|-----------|---------|-------------------|
| [Theme] | "[Customer quote]" | "[How to leverage in conversation]" |

### Why We Lose to [Competitor]
| Loss Theme | Evidence | Counter-Strategy |
|------------|---------|-----------------|
| [Theme] | "[Customer quote]" | "[How to mitigate]" |

### Landmine Questions
Questions to ask prospects that highlight competitor weaknesses:
1. "[Question]" — Exposes: [weakness]
2. "[Question]" — Exposes: [weakness]

### Objection Handling
| When Prospect Says... | Respond With... |
|----------------------|----------------|
| "[Objection favoring competitor]" | "[Your response]" |
```

---

## Combining Frameworks

For comprehensive analyses, combine frameworks naturally:

- **Competitor Snapshot** → SWOT
- **Market Landscape** → Porter's Five Forces + Positioning Matrix
- **Review Intelligence** → JTBD + Win/Loss
- **Full Battlecard** → SWOT + Win/Loss + Positioning Matrix
- **Market Entry Strategy** → Porter's Five Forces + Blue Ocean + Positioning Matrix

Only apply frameworks when they add genuine insight. A simple pricing comparison doesn't need Porter's Five Forces. Match the depth of analysis to the complexity of the question.


path: references/data-source-guide.md
content: # Data Source Selection Guide

This reference maps every competitive intelligence need to the specific `bdata` CLI command. Use this to decide which command to run for each piece of intelligence.

## Command Selection Rule

**Always prefer `bdata pipelines`** (structured JSON) **over `bdata scrape`** (raw markdown) when a pipeline type exists for the target platform. Pipelines return clean, structured data that's easier to analyze. Fall back to `bdata scrape` only when no pipeline exists.

## Intelligence Need → Command Mapping

### Company & Business Intelligence

| Need | Primary Command | Fallback |
|------|----------------|----------|
| Company overview (funding, size, investors) | `bdata pipelines crunchbase_company "[crunchbase-url]"` | `bdata scrape [url]/about` |
| Employee count & company details | `bdata pipelines linkedin_company_profile "[linkedin-url]"` | `bdata pipelines crunchbase_company "[url]"` |
| Financial data (public companies) | `bdata pipelines yahoo_finance_business "[yahoo-finance-url]"` | `bdata pipelines crunchbase_company "[url]"` |
| Company news & PR | `bdata search "[company] news" --json` | `bdata pipelines reuter_news "[reuters-url]"` |
| Company website / homepage | `bdata scrape [url]` | — |

### Pricing & Products

| Need | Primary Command | Fallback |
|------|----------------|----------|
| SaaS pricing pages | `bdata scrape [url]/pricing` | `bdata search "[company] pricing" --json` |
| Amazon product details | `bdata pipelines amazon_product "[amazon-url]"` | `bdata scrape [url]` |
| Amazon product reviews | `bdata pipelines amazon_product_reviews "[amazon-url]"` | — |
| Amazon search results | `bdata pipelines amazon_product_search "[keyword]" "[amazon-domain]"` | `bdata search "[keyword] site:amazon.com" --json` |
| Walmart products | `bdata pipelines walmart_product "[walmart-url]"` | `bdata scrape [url]` |
| eBay listings | `bdata pipelines ebay_product "[ebay-url]"` | `bdata scrape [url]` |
| Etsy products | `bdata pipelines etsy_products "[etsy-url]"` | `bdata scrape [url]` |
| Best Buy products | `bdata pipelines bestbuy_products "[bestbuy-url]"` | `bdata scrape [url]` |
| Third-party pricing reviews | `bdata search "[company] pricing review" --json` | — |

### Reviews & Customer Sentiment

| Need | Primary Command | Fallback |
|------|----------------|----------|
| G2 reviews (SaaS) | `bdata scrape [g2-product-url]` | `bdata search "[product] site:g2.com" --json` → scrape result |
| Capterra reviews (SaaS) | `bdata scrape [capterra-product-url]` | `bdata search "[product] site:capterra.com" --json` → scrape result |
| Google Maps reviews (local) | `bdata pipelines google_maps_reviews "[maps-url]" [days]` | — |
| Google Play Store (apps) | `bdata pipelines google_play_store "[play-url]"` | — |
| Apple App Store (apps) | `bdata pipelines apple_app_store "[appstore-url]"` | — |
| Trustpilot reviews | `bdata scrape [trustpilot-url]` | `bdata search "[company] site:trustpilot.com" --json` → scrape result |

### Hiring & Talent

| Need | Primary Command | Fallback |
|------|----------------|----------|
| Job listings | `bdata pipelines linkedin_job_listings "[linkedin-url]"` | `bdata scrape [careers-url]` |
| Company LinkedIn page | `bdata pipelines linkedin_company_profile "[linkedin-url]"` | `bdata search "[company] linkedin" --json` |
| Key people / leadership | `bdata pipelines linkedin_person_profile "[linkedin-url]"` | `bdata scrape [url]/team` |
| Careers page | `bdata scrape [url]/careers` | `bdata search "[company] careers" --json` → scrape result |

### Content & SEO

| Need | Primary Command | Fallback |
|------|----------------|----------|
| SERP rankings for keyword | `bdata search "[keyword]" --json` | — |
| Indexed page count | `bdata search "site:[domain]" --json` | — |
| Blog / content pages | `bdata scrape [url]/blog` | `bdata search "site:[domain] blog" --json` |
| Individual articles | `bdata scrape [article-url]` | — |
| News search | `bdata search "[topic]" --json --type news` | `bdata search "[topic] news" --json` |

### Social Media

| Need | Primary Command | Fallback |
|------|----------------|----------|
| Instagram profile | `bdata pipelines instagram_profiles "[instagram-url]"` | — |
| Instagram posts | `bdata pipelines instagram_posts "[instagram-url]"` | — |
| TikTok profile | `bdata pipelines tiktok_profiles "[tiktok-url]"` | — |
| TikTok posts | `bdata pipelines tiktok_posts "[tiktok-url]"` | — |
| YouTube channel | `bdata pipelines youtube_profiles "[youtube-url]"` | — |
| YouTube video details | `bdata pipelines youtube_videos "[youtube-url]"` | — |
| YouTube comments | `bdata pipelines youtube_comments "[youtube-url]" [count]` | — |
| X (Twitter) posts | `bdata pipelines x_posts "[x-url]"` | — |
| Reddit posts | `bdata pipelines reddit_posts "[reddit-url]"` | — |
| Facebook posts | `bdata pipelines facebook_posts "[facebook-url]"` | — |
| Facebook reviews | `bdata pipelines facebook_company_reviews "[facebook-url]"` | — |
| LinkedIn posts | `bdata pipelines linkedin_posts "[linkedin-url]"` | — |

### Competitor Discovery

| Need | Primary Command | Fallback |
|------|----------------|----------|
| Find competitors by category | `bdata search "[category] companies" --json` | `bdata search "best [category] tools" --json` |
| Find alternatives | `bdata search "[product] alternatives" --json` | `bdata scrape [g2-category-url]` |
| G2 category page | `bdata scrape [g2-category-url]` | `bdata search "[category] site:g2.com" --json` → scrape result |
| Market overview | `bdata search "[industry] market landscape" --json` | — |

## Finding URLs When You Don't Have Them

Often you'll know a competitor's name but not their specific URLs on platforms. Use this pattern:

```bash
# Find a company's Crunchbase page
bdata search "[company name] crunchbase" --json | jq -r '.organic[0].link'

# Find a company's LinkedIn page
bdata search "[company name] linkedin company" --json | jq -r '.organic[0].link'

# Find a company's G2 page
bdata search "[company name] site:g2.com" --json | jq -r '.organic[0].link'

# Find a company's careers page
bdata search "[company name] careers" --json | jq -r '.organic[0].link'
```

## Cost Efficiency Guidelines

| Analysis Type | Recommended `bdata` Calls | Estimated Cost |
|--------------|--------------------------|----------------|
| Quick Snapshot (1 competitor) | 3-5 calls | ~$0.01-$0.05 |
| Pricing Comparison (3 competitors) | 3-6 calls | ~$0.01-$0.05 |
| Review Intelligence (1 competitor) | 2-4 calls | ~$0.01-$0.05 |
| Hiring Signal Analysis | 2-3 calls | ~$0.01-$0.03 |
| Content & SEO Battle | 4-8 calls | ~$0.02-$0.08 |
| Market Landscape Map | 6-15 calls | ~$0.05-$0.15 |
| Full Battlecard (1 competitor) | 8-15 calls | ~$0.05-$0.15 |
| Multi-competitor deep dive (3+) | 15-30 calls | ~$0.10-$0.50 |

## Error Handling

| Error / Situation | What to Do |
|------------------|------------|
| Page returns empty or minimal content | Try the fallback command. If that fails too, note "Data unavailable — page may be gated or require authentication." |
| 403 / Access Denied | The page likely requires login. Note this and try alternative sources (e.g., search for third-party coverage). |
| Pipeline timeout | Use `--async` flag, then `bdata status <job-id> --wait --timeout 300`. |
| Pipeline type doesn't exist | Fall back to `bdata scrape [url]` for raw content. |
| No results from search | Broaden the search query. Try different query variations. |
| Rate limit exceeded | Wait briefly and retry, or use `--async` mode. |

## Chaining Commands

The CLI is pipe-friendly. Useful patterns:

```bash
# Search → extract first URL → scrape it
bdata search "[company] pricing" --json | jq -r '.organic[0].link' | xargs bdata scrape

# Get all organic result URLs from a search
bdata search "[query]" --json | jq -r '.organic[].link'

# Pipeline output to file for later analysis
bdata pipelines crunchbase_company "[url]" -o competitor_data.json
```


path: references/industry-signals.md
content: # Industry Signal Interpretation Guide

This reference helps you interpret raw data collected via `bdata` as strategic intelligence signals. Raw data is just numbers and text — the value is in what it *means*.

## Pricing Signals

### What Pricing Changes Reveal

| Signal | What You Observe | What It Likely Means |
|--------|-----------------|---------------------|
| Price increase | Higher prices than last known / industry average | Confidence in product value, moving upmarket, or cost pressure |
| Price decrease | Lower prices, new budget tiers | Competitive pressure, pivot to volume/SMB, struggling with enterprise sales |
| New free tier | Introduced a free plan | Land-and-expand strategy, competing with open-source, or new market entry |
| Removed free tier | Free plan eliminated | Monetization pressure, focusing on qualified leads, or mature product stage |
| Usage-based pricing | Per-API-call, per-seat, per-GB model | Targeting scalability-conscious buyers, aligning revenue with value delivery |
| Enterprise "Contact Us" | No public pricing for top tier | Targeting large deals, high ACV strategy, or hiding pricing from competitors |
| Annual discount > 30% | Big gap between monthly and annual | Cash flow priority, high churn rate they're trying to mitigate |
| Feature unbundling | Features previously included now sold as add-ons | Monetization pressure, or creating entry-level price point |

### Pricing Model Implications

| Model | Favors | Challenges | Strategic Signal |
|-------|--------|-----------|-----------------|
| Per-seat | Predictable revenue, easy to understand | Penalizes collaboration, invites seat-sharing hacks | B2B focus, enterprise-friendly |
| Usage-based | Scales with customer value, low entry barrier | Unpredictable bills, hard to forecast | Developer/API-first, PLG strategy |
| Flat-rate | Simple, no surprise bills | Doesn't scale with value, hard to monetize power users | SMB-focused, simplicity positioning |
| Freemium | Massive top-of-funnel, viral potential | Conversion challenges, support costs | Growth-stage, PLG, market share grab |
| Enterprise-only | High ACV, dedicated support | Long sales cycles, small customer base | Mature, niche, or complex product |

---

## Hiring Signals

### Role Distribution Analysis

| Department Emphasis | What It Signals | Confidence Level |
|--------------------|----------------|-----------------|
| **Engineering-heavy** (>50% of roles) | Product investment phase, building new features or rebuilding platform | High |
| **Sales-heavy** (>40% of roles) | Revenue scaling phase, product is mature enough to sell aggressively | High |
| **Marketing-heavy** (>30% of roles) | Brand awareness push, entering new markets, or pre-IPO visibility | Medium |
| **Customer Success heavy** | Churn problem, or moving upmarket where CS is expected | Medium |
| **Data/ML roles emerging** | AI/ML product features coming, or building data moats | High |
| **Security/Compliance roles** | Enterprise push, regulated industry entry, or post-incident response | High |
| **DevRel/Developer Advocate** | Developer ecosystem play, API/platform strategy | High |
| **Balanced across all** | Mature company in steady growth | Medium |

### Technology Signals from Job Descriptions

| Tech Mentioned | Strategic Signal |
|---------------|-----------------|
| Kubernetes, Terraform, cloud-native | Scaling infrastructure, multi-cloud strategy |
| React/Next.js, design systems | Frontend modernization, UX investment |
| Rust, Go (replacing Python/Node) | Performance-critical features, infrastructure rewrite |
| LLM, RAG, vector databases | AI features coming, likely within 3-6 months |
| Kafka, Flink, streaming | Real-time data processing, event-driven architecture |
| SOC2, HIPAA, FedRAMP | Enterprise compliance push, government/healthcare market entry |
| GraphQL, API gateway | Platform/ecosystem strategy, third-party integrations |
| Mobile (iOS/Android native) | Mobile-first or mobile expansion play |

### Geographic Signals

| Hiring Location | Strategic Signal |
|----------------|-----------------|
| New office in EU | GDPR compliance push, European market expansion |
| Remote roles in APAC | Asia-Pacific market entry |
| Engineering hub in lower-cost market | Cost optimization, scaling engineering capacity |
| Sales team in new city/country | Direct market entry into that geography |
| No remote roles (return to office) | Culture choice, or need for high-collaboration work (security, hardware) |

### Seniority Signals

| Pattern | Interpretation |
|---------|---------------|
| Many VP/Director hires | New teams being formed, new business units, strategic pivots |
| Mostly Senior/Staff engineers | Deep technical work, complex problems, platform rebuilds |
| Many junior/entry-level | Scaling existing teams, well-defined processes, growth mode |
| CTO/CPO/CMO hire | Leadership change, strategic pivot, pre-IPO or post-funding professionalization |
| "Founding" roles (Founding Engineer, etc.) | New initiative, internal startup, or early-stage expansion area |

---

## Content & SEO Signals

### Publishing Frequency Signals

| Pattern | What It Means |
|---------|-------------|
| Daily publishing | Aggressive SEO play, content-led growth, likely has dedicated content team |
| Weekly publishing | Healthy content strategy, sustainable investment |
| Monthly or less | Content is not a growth lever, or team is resource-constrained |
| Burst then silence | Had a content push but didn't sustain it (budget cut? team change?) |
| Increasing frequency | New investment in content marketing |
| Decreasing frequency | Cutting content budget, pivoting to other channels |

### Topic Shift Signals

| What Changes | What It Means |
|-------------|-------------|
| New topic cluster appears | Product expanding into that area, or targeting new buyer persona |
| Technical → business content | Moving upmarket, targeting decision-makers instead of practitioners |
| Product → thought leadership | Brand building, pre-IPO positioning, or competing for mindshare |
| How-to → comparison content | Getting more competitive, actively fighting for buyer attention |
| Competitor mention articles | Direct competitive play, feeling market pressure |

### SERP Signals

| What You See | What It Means |
|-------------|-------------|
| Competitor ranks #1 for your target keywords | They've invested heavily in this topic; you need differentiated content to compete |
| No one ranks well for a keyword | Content gap opportunity — first mover advantage available |
| Competitor dominates 5+ keywords in a cluster | They own this topic area; consider adjacencies instead |
| Competitor's rankings are declining | Their content is aging, opportunity to overtake |
| New domain appearing in top 3 | New entrant or pivot by existing player — investigate |

---

## Review Signals

### Sentiment Patterns

| Pattern | Interpretation | Action |
|---------|---------------|--------|
| High rating (4.5+) but many detailed negative reviews | Product is good overall but has specific painful gaps | Target those specific gaps in your positioning |
| Low rating (<3.5) with passionate positive outliers | Product serves a niche very well but frustrates everyone else | Don't compete head-on; serve the broader market better |
| Declining ratings over time | Product debt accumulating, or team/quality changes | Opportunity to win their churning customers |
| Improving ratings over time | Competitor is investing and executing; they're getting better | Don't wait — differentiate now before the gap closes |
| Many reviews mentioning price | Product seen as too expensive relative to value | Price positioning opportunity |
| "Support" mentioned frequently in negatives | Customer success issues; relationship opportunity for you | Emphasize your support quality |

### Review Content Analysis

| What Reviewers Say | Strategic Signal |
|-------------------|-----------------|
| "We switched from [X] because..." | Direct churn triggers — validate these are real and target them |
| "I wish it could..." | Feature requests = roadmap leak. If many ask for the same thing, it's a real gap |
| "Compared to [Y], it's better at..." | Head-to-head positioning from actual users — more reliable than marketing claims |
| "The onboarding was..." | UX maturity signal. Bad onboarding = opportunity for PLG competitor |
| "Our team of [N] uses..." | Company size signal. Tells you their actual customer profile |
| "We've been using it for [N] years" | Switching cost / lock-in signal. Long-tenured users are harder to convert |

---

## Funding Signals

### Round Type Implications

| Round | What It Means | Competitive Implication |
|-------|-------------|----------------------|
| Seed / Pre-seed | Very early, product may not exist yet | Not a threat today but could be in 12-18 months |
| Series A | Product-market fit validated, scaling started | Starting to compete seriously, watch their next moves |
| Series B-C | Growth stage, scaling sales and marketing | Active competitor, likely aggressive on pricing and hiring |
| Series D+ | Late stage, pre-IPO or sustained growth | Established player, large resources, may be slowing on innovation |
| Down round | Valuation decreased, likely struggling | Vulnerable competitor — their best talent may be leaving |
| Acquisition | Being bought by larger company | Strategic pivot likely, integration period = vulnerability window |
| IPO | Going public | Focused on metrics/profitability, may cut risky initiatives |

### Investor Type Signals

| Investor Type | What It Signals |
|--------------|----------------|
| Top-tier VC (a16z, Sequoia, etc.) | Credibility, large network, aggressive growth expectations |
| Strategic investor (Google, Microsoft, etc.) | Likely integration/partnership coming, ecosystem play |
| PE firm | Profitability focus, possible cost-cutting, may reduce R&D |
| Government/defense VC (In-Q-Tel, etc.) | Government/security market entry |
| Healthcare-focused VC | Healthcare/biotech market expansion |
| International VC | Geographic expansion aligned with investor's region |

---

## Social Media Signals

### Engagement Patterns

| Signal | Interpretation |
|--------|---------------|
| Follower growth accelerating | Marketing investment paying off, or viral moment |
| Follower growth flat/declining | Brand fatigue, or investment shifted elsewhere |
| High engagement, low followers | Niche but passionate community — quality over quantity |
| Low engagement, high followers | Vanity metrics, possibly bought followers, or audience mismatch |
| Executive active on LinkedIn | Thought leadership strategy, personal brand building |
| Company posting job openings on social | Urgent hiring, possibly high attrition |
| Suddenly active after dormancy | New marketing hire, new strategy, or upcoming launch |

### Content Strategy Signals

| What They Post | What It Means |
|---------------|-------------|
| Product updates/releases | Active development, shipping regularly |
| Customer case studies | Sales-driven content, building social proof |
| Industry thought leadership | Positioning as category leader, mindshare play |
| Employee spotlights | Employer branding, likely facing hiring challenges |
| Memes / casual content | B2C or developer audience, community-building strategy |
| Competitive comparisons | Feeling market pressure, actively fighting for positioning |

---

## Combining Signals for Confidence

Individual signals can be misleading. Combine multiple signals for higher confidence:

| Hypothesis | Supporting Signals (need 2+) |
|-----------|----------------------------|
| "Competitor is pivoting to enterprise" | Enterprise pricing tier added + security/compliance hires + SOC2 mentioned in jobs + content shifting to business topics |
| "Competitor is struggling" | Down round + hiring freeze + declining reviews + reduced content output |
| "Competitor entering our market" | New product page + hires in our domain + content on our topics + search ads on our keywords |
| "Competitor about to launch AI features" | ML/AI job postings + "AI" in recent blog posts + AI-related investor + executive AI conference appearances |
| "Competitor moving downmarket" | New free tier + lower pricing + self-serve onboarding + PLG-focused hires (growth engineers, product-led) |

When signals conflict (e.g., aggressive hiring but declining reviews), note the tension and flag it — it may indicate a transition period.


path: references/output-templates.md
content: # Output Templates

Use these templates as the base structure for each report type. Customize sections as needed based on available data, but maintain the overall structure and always include the Sources and Strategic Recommendations sections.

**Every report must include**:
- A date stamp: "Data collected on [YYYY-MM-DD]"
- Source URLs for every factual claim
- A Strategic Recommendations section at the end

---

## Competitor Snapshot

```markdown
# Competitor Snapshot: [Company Name]

*Data collected on [YYYY-MM-DD]*

## Overview
- **Website**: [url]
- **Founded**: [year] | **HQ**: [city, country] | **Employees**: [count or range]
- **Funding**: [total raised] ([last round type] — [date]) | **Investors**: [key investors]
- **Positioning**: [one-line summary of how they position themselves]

## Product & Pricing
| Plan | Price | Key Features | Limits |
|------|-------|-------------|--------|
| [Free/Starter] | [price] | [features] | [limits] |
| [Pro/Growth] | [price] | [features] | [limits] |
| [Enterprise] | [price] | [features] | [limits] |

**Pricing model**: [per-seat / usage-based / flat-rate / freemium / enterprise-only]

## Messaging Analysis
- **Tagline**: "[their tagline]"
- **Key claims**: [what they emphasize on their homepage]
- **Target audience**: [who they're speaking to — personas, company size, industry]
- **Differentiation**: [how they position against alternatives]

## Strengths
1. [Strength with evidence]
2. [Strength with evidence]

## Vulnerabilities
1. [Weakness or gap with evidence]
2. [Weakness or gap with evidence]

## Strategic Recommendations
- [Actionable recommendation based on findings]
- [How to position against this competitor]

## Sources
- [URL] — [what was gathered from this source]
- [URL] — [what was gathered from this source]
```

---

## Pricing Intelligence Report

```markdown
# Pricing Intelligence Report: [Category/Market]

*Data collected on [YYYY-MM-DD]*

## Comparison Matrix

| | [Competitor A] | [Competitor B] | [Competitor C] | Your Product |
|--|---------------|---------------|---------------|-------------|
| **Free tier** | [Yes/No — details] | [Yes/No — details] | [Yes/No — details] | [?] |
| **Starter** | [$X/mo — features] | [$Y/mo — features] | [$Z/mo — features] | [?] |
| **Pro/Growth** | [$X/mo — features] | [$Y/mo — features] | [$Z/mo — features] | [?] |
| **Enterprise** | [Custom/price] | [Custom/price] | [Custom/price] | [?] |
| **Pricing model** | [per-seat/usage/flat] | [per-seat/usage/flat] | [per-seat/usage/flat] | [?] |

## Pricing Model Analysis

### [Competitor A]
- **Model**: [per-seat / usage-based / flat-rate / freemium]
- **Strategy**: [Land-and-expand / Premium positioning / Volume play]
- **Notable**: [Discounts, annual billing incentives, hidden costs]

### [Competitor B]
- ...

### [Competitor C]
- ...

## Key Insights
1. **Price leader**: [Who is cheapest at each tier and why]
2. **Premium play**: [Who charges the most and what justifies it]
3. **Free tier strategy**: [Who offers what for free and why]
4. **Feature gates**: [Which features are locked behind higher tiers]
5. **Hidden costs**: [Any usage-based charges, overage fees, or add-on costs]

## Positioning Opportunities
- [Where is there room to undercut on price?]
- [Where is there room to charge more by offering more?]
- [What pricing model would differentiate?]

## Sources
- [URL] — [Competitor A pricing page]
- [URL] — [Competitor B pricing page]
- [URL] — [Competitor C pricing page]
```

---

## Review Intelligence Report

```markdown
# Review Intelligence: [Company/Product Name]

*Data collected on [YYYY-MM-DD]*

## Sentiment Overview
- **Overall rating**: [X.X/5 stars] across [N] reviews analyzed
- **Positive**: [X]% | **Neutral**: [X]% | **Negative**: [X]%
- **Sources**: [G2 (N reviews), Capterra (N reviews), App Store (N reviews), ...]

## What Customers Love
1. **[Feature/Aspect]** — "[Direct quote from review]" *(Source: [platform])*
2. **[Feature/Aspect]** — "[Direct quote from review]" *(Source: [platform])*
3. **[Feature/Aspect]** — "[Direct quote from review]" *(Source: [platform])*

## What Customers Hate (Your Opportunity)
1. **[Pain point]** — "[Direct quote from review]" *(Source: [platform])*
   - *Frequency*: Mentioned in ~[N]% of negative reviews
   - *Severity*: [High/Medium/Low impact on user workflow]
2. **[Pain point]** — "[Direct quote from review]" *(Source: [platform])*
   - *Frequency*: ...
   - *Severity*: ...

## Feature Requests
1. **[Requested feature]** — mentioned [N] times across reviews
2. **[Requested feature]** — mentioned [N] times across reviews

## Competitive Mentions
- "[Product] vs [Other]": "[Quote about comparison]" *(Source: [platform])*
- Switching signals: "[Quote about switching from/to competitor]" *(Source: [platform])*

## Strategic Recommendations
- [Which pain points to exploit in your positioning]
- [Which loved features are table stakes you must match]
- [Which feature requests represent unmet demand]

## Sources
- [URL] — [N] reviews analyzed from [platform]
- [URL] — [N] reviews analyzed from [platform]
```

---

## Hiring Signal Analysis Report

```markdown
# Hiring Signal Analysis: [Company Name]

*Data collected on [YYYY-MM-DD]*

## Hiring Velocity
- **Total open roles**: [N]
- **Signal**: [Aggressive growth / Steady scaling / Selective hiring / Contracting]

## Department Breakdown

| Department | Open Roles | % of Total | Signal |
|-----------|-----------|-----------|--------|
| Engineering | [N] | [X]% | [Investing heavily in product] |
| Sales | [N] | [X]% | [Scaling revenue org] |
| Marketing | [N] | [X]% | [Brand awareness push] |
| Customer Success | [N] | [X]% | [Retention focus] |
| Product | [N] | [X]% | [Expanding product scope] |
| Operations | [N] | [X]% | [Scaling infrastructure] |
| Other | [N] | [X]% | — |

## Strategic Signals

### Technology Bets
- [Technologies mentioned in job descriptions and what they suggest about product direction]

### Geographic Expansion
- [New office locations or remote hiring in new regions — what markets they're entering]

### Product Direction
- [What new roles suggest about upcoming features or product pivots]

### Seniority Mix
- **Leadership hires**: [N] — [signals: new initiatives, new teams]
- **IC hires**: [N] — [signals: scaling existing teams]
- **Interpretation**: [What the mix tells us about their stage]

## Strategic Recommendations
- [What their hiring tells you about where they're headed]
- [How to position against their likely next moves]

## Sources
- [URL] — LinkedIn job listings
- [URL] — Careers page
```

---

## Content & SEO Battle Report

```markdown
# Content & SEO Battle Report: [Category/Keywords]

*Data collected on [YYYY-MM-DD]*

## SERP Dominance

| Keyword | #1 | #2 | #3 | Your Ranking |
|---------|----|----|-----|-------------|
| [keyword 1] | [domain] | [domain] | [domain] | [?] |
| [keyword 2] | [domain] | [domain] | [domain] | [?] |
| [keyword 3] | [domain] | [domain] | [domain] | [?] |

## Content Volume

| Competitor | Indexed Pages (est.) | Blog Activity | Publishing Frequency |
|-----------|---------------------|--------------|---------------------|
| [A] | ~[N] pages | [Active/Dormant] | [Daily/Weekly/Monthly] |
| [B] | ~[N] pages | [Active/Dormant] | [Daily/Weekly/Monthly] |
| [C] | ~[N] pages | [Active/Dormant] | [Daily/Weekly/Monthly] |

## Topic Analysis

| Topic Cluster | [Competitor A] | [Competitor B] | [Competitor C] | Gap? |
|-------------|---------------|---------------|---------------|------|
| [Topic 1] | [N] articles | [N] articles | [N] articles | [Yes/No] |
| [Topic 2] | [N] articles | [N] articles | [N] articles | [Yes/No] |

## Top-Performing Content
1. **[Competitor A]**: "[Article title]" — [URL] — ranks #[N] for "[keyword]"
2. **[Competitor B]**: "[Article title]" — [URL] — ranks #[N] for "[keyword]"

## Content Gaps (Your Opportunities)
1. **[Topic]** — [Why it's an opportunity: no competitor covers it well, high search volume, etc.]
2. **[Topic]** — ...

## Strategic Recommendations
- [Which keywords to target first]
- [Content format recommendations]
- [How to differentiate your content]

## Sources
- SERP data from Google via `bdata search`
- [URLs of scraped blog/content pages]
```

---

## Market Landscape Map

```markdown
# Market Landscape: [Category/Industry]

*Data collected on [YYYY-MM-DD]*

## Market Overview
[2-3 sentence summary of the market: size, growth, key trends]

## Market Map

### Enterprise Tier
| Company | Positioning | Employees | Funding | Key Differentiator |
|---------|------------|-----------|---------|-------------------|
| [Name] | [one-line] | [count] | [total] | [what sets them apart] |

### Mid-Market
| Company | Positioning | Employees | Funding | Key Differentiator |
|---------|------------|-----------|---------|-------------------|
| [Name] | [one-line] | [count] | [total] | [what sets them apart] |

### SMB / Startups
| Company | Positioning | Employees | Funding | Key Differentiator |
|---------|------------|-----------|---------|-------------------|
| [Name] | [one-line] | [count] | [total] | [what sets them apart] |

### Open Source / Free
| Project | Positioning | Stars/Users | Key Differentiator |
|---------|------------|------------|-------------------|
| [Name] | [one-line] | [count] | [what sets them apart] |

## Positioning Map

**Axes**: [X-axis label] vs. [Y-axis label]

```
                    [High Y-axis label]
                         │
    [Company D]          │         [Company A]
                         │
    [Company E]          │         [Company B]
                         │
[Low X-axis] ────────────┼──────────── [High X-axis]
                         │
    [Company F]          │         [Company C]
                         │
                    [Low Y-axis label]
```

## White Space Opportunities
1. **[Underserved segment]** — [Why: no player focuses here, growing demand, etc.]
2. **[Unoccupied position]** — [Why: gap in the positioning map]

## Market Trends
- [Trend 1: e.g., consolidation, AI adoption, pricing pressure]
- [Trend 2: e.g., new entrants from adjacent markets]
- [Trend 3: e.g., open-source alternatives gaining traction]

## Strategic Recommendations
- [Where to position given the landscape]
- [Which segment to target]
- [Which competitors to watch closely]

## Sources
- [URL] — [source description]
- [URL] — [source description]
```

---

## Competitive Battlecard

Use this template for comprehensive, sales-ready battlecards:

```markdown
# Competitive Battlecard: [Your Product] vs. [Competitor]

*Data collected on [YYYY-MM-DD] — refresh recommended every [30/60/90] days*

## Quick Reference
- **Their pitch**: "[Their tagline/positioning]"
- **Our pitch against them**: "[How to position against this competitor]"
- **When we win**: [Scenarios where you have an advantage]
- **When we lose**: [Scenarios where they have an advantage]

## Head-to-Head Comparison

| Capability | [Your Product] | [Competitor] | Advantage |
|-----------|---------------|-------------|-----------|
| [Feature 1] | [Your offering] | [Their offering] | [Ours/Theirs/Tie] |
| [Feature 2] | [Your offering] | [Their offering] | [Ours/Theirs/Tie] |
| **Pricing** | [Your pricing] | [Their pricing] | [Ours/Theirs/Tie] |

## Their Strengths (Acknowledge)
1. [Strength] — [How to handle when prospect brings this up]
2. [Strength] — [How to handle when prospect brings this up]

## Their Weaknesses (Exploit)
1. [Weakness] — [Talking point for sales conversations]
2. [Weakness] — [Talking point for sales conversations]

## Landmines to Set
Questions to ask prospects that highlight your advantages:
1. "[Question that exposes competitor weakness]"
2. "[Question that exposes competitor weakness]"

## Customer Evidence
- [Quote from customer who switched from competitor]
- [Quote from customer who evaluated both and chose you]

## Objection Handling
| Objection | Response |
|----------|---------|
| "[Common objection about your product vs competitor]" | "[How to respond]" |

## Sources
- [URL] — [source description]
```

---

## Executive Summary (Multi-Module)

Use this when combining multiple modules into one comprehensive report:

```markdown
# Competitive Intelligence Report: [Topic/Market]

*Data collected on [YYYY-MM-DD]*

## Executive Summary
[3-5 bullet points capturing the most important findings across all analyses]

## Key Findings
1. **[Finding]** — [One-sentence evidence]
2. **[Finding]** — [One-sentence evidence]
3. **[Finding]** — [One-sentence evidence]

## Detailed Analysis
[Include full reports from each module used, as separate sections]

## Strategic Recommendations
1. **Immediate** (this week): [Quick wins based on findings]
2. **Short-term** (this quarter): [Positioning and product decisions]
3. **Long-term** (this year): [Strategic direction based on market trends]

## Sources
[Consolidated list of all sources across modules]
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