competitive-intel

What this skill does

# 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)