Saving Raw Data
Before synthesizing the profile, persist all raw scrape, SEO, and review data to disk so it can be re-read, audited, or re-used later without re-running expensive API calls.
Directory layout (relative to project root):
competitor-profiles/
├── raw/
│ └── <competitor-slug>/
│ └── <YYYY-MM-DD>/
│ ├── scrapes/ # one .md file per scraped page (homepage.md, pricing.md, ...)
│ ├── seo/ # one .json file per DataForSEO call (backlinks-summary.json, ranked-keywords.json, ...)
│ └── reviews/ # one .md or .json file per review source (g2.md, capterra.md, ...)
├── <competitor-slug>.md # final synthesized profile
└── _summary.md # cross-competitor summary
Rules:
<competitor-slug>is lowercase, hyphenated (e.g.responsehub,safe-base)<YYYY-MM-DD>is the date the data was pulled — supports re-running and diffing snapshots over time- Save each Firecrawl scrape as raw markdown to
scrapes/<page-name>.md - Save each DataForSEO response as raw JSON to
seo/<endpoint-name>.json - Save each review source to
reviews/<source>.md(cleaned text) or.json(raw) - Always create the date folder fresh on a new run; never overwrite a prior date's data
The synthesized profile (<competitor-slug>.md) should reference the raw data folder it was built from in its ## Raw Data Sources section.
Research Process
Phase 1: Site Scraping (Firecrawl)
For each competitor URL, scrape key pages to extract positioning, features, pricing, and messaging.
Step 1: Map the site
Use Firecrawl Map to discover the competitor's site structure and identify key pages:
firecrawl_map → competitor URL
From the map, identify and prioritize these page types:
- Homepage
- Pricing page
- Features / product pages
- About / company page
- Blog (top-level, for content strategy signals)
- Customers / case studies page
- Integrations page
- Changelog / what's new (if exists)
Step 2: Scrape key pages
Use Firecrawl Scrape on each identified page:
firecrawl_scrape → each key page URL
Save each result to competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/scrapes/<page-name>.md before extracting fields.
Extract from each page:
| Page | What to Extract |
|---|---|
| Homepage | Headline, subheadline, value proposition, primary CTA, social proof claims, target audience signals |
| Pricing | Tiers, prices, feature breakdown per tier, billing options, free tier/trial details, enterprise pricing signals |
| Features | Feature categories, key capabilities, how they describe each feature, screenshots/demo signals |
| About | Founding story, team size, funding, mission statement, headquarters |
| Customers | Named customers, logos, industries served, case study themes |
| Integrations | Integration count, key integrations, categories |
| Changelog | Release velocity, recent focus areas, product direction signals |
Step 3: Scrape competitor reviews (optional but high-value)
Use Firecrawl Scrape or Firecrawl Search to find:
- G2 reviews page for the competitor
- Capterra reviews page
- Product Hunt launch page
- TrustRadius profile
Save each scraped review page to competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/reviews/<source>.md. Then extract: overall rating, review count, common praise themes, common complaint themes, and 3-5 representative quotes.
Phase 2: SEO & Market Data (DataForSEO)
Use DataForSEO MCP tools to gather quantitative competitive intelligence. Save each raw response as JSON to competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/seo/<endpoint-name>.json before parsing it into the profile. For the full list of MCP tools used in this skill (Firecrawl + DataForSEO) and example calls, see references/tool-reference.md.
Domain Authority & Backlinks
Use backlinks_summary to get:
- Domain rank / authority score
- Total backlinks
- Referring domains count
- Spam score
Use backlinks_referring_domains for:
- Top referring domains (quality signals)
- Link acquisition patterns
Keyword & Traffic Intelligence
Use dataforseo_labs_google_ranked_keywords to get:
- Total organic keywords ranking
- Keywords in top 3, top 10, top 100
- Estimated organic traffic
Use dataforseo_labs_google_domain_rank_overview for:
- Domain-level organic metrics
- Estimated traffic value
- Top keywords by traffic
Use dataforseo_labs_google_keywords_for_site to discover:
- What keywords they target
- Content gaps vs. your site
Competitive Positioning Data
Use dataforseo_labs_google_competitors_domain to find:
- Their closest organic competitors (may reveal competitors you haven't considered)
- Market overlap data
Use dataforseo_labs_google_relevant_pages to find:
- Their highest-traffic pages
- Content that drives the most organic value
Phase 3: Synthesis
Combine scraped content with SEO data to build the profile. Cross-reference claims (e.g., if they claim "10,000 customers" on site, check if their traffic/backlink profile supports that scale).
Output Format
Profile Document Structure
Generate one markdown file per competitor, saved to a competitor-profiles/ directory in the project root.
Filename: competitor-profiles/[competitor-name].md
For the full profile and summary templates: See references/templates.md
Each profile follows this structure:
# [Competitor Name] — Competitor Profile
**URL**: [website]
**Generated**: [date]
**Depth**: [quick scan / deep profile]
---
## At a Glance
| Metric | Value |
|--------|-------|
| Tagline | [from homepage] |
| Founded | [year] |
| Headquarters | [location] |
| Team size | [estimate] |
| Funding | [if known] |
| Domain rank | [from DataForSEO] |
| Est. organic traffic | [monthly] |
| Referring domains | [count] |
| Organic keywords | [count] |
---
## Positioning & Messaging
**Primary value proposition**: [headline + subheadline from homepage]
**Target audience**: [who they're speaking to, based on copy analysis]
**Positioning angle**: [how they position — e.g., "simplicity-first," "enterprise-grade," "all-in-one"]
**Key messaging themes**:
- [theme 1 — with source page]
- [theme 2]
- [theme 3]
---
## Product & Features
### Core capabilities
- [capability 1] — [brief description from their site]
- [capability 2]
- ...
### Notable differentiators
- [what they emphasize as unique]
### Integrations
- [count] integrations
- Key: [list top 5-10]
### Product direction signals
- [based on changelog / recent feature releases]
---
## Pricing
| Tier | Price | Key Inclusions |
|------|-------|---------------|
| [Free/Starter] | [price] | [what's included] |
| [Pro/Growth] | [price] | [what's included] |
| [Enterprise] | [price] | [what's included] |
**Billing**: [monthly/annual, discount for annual]
**Free trial**: [yes/no, duration]
**Notable**: [any pricing quirks — per-seat, usage-based, hidden costs]
---
## Customers & Social Proof
**Named customers**: [list notable logos]
**Industries**: [primary industries served]
**Case study themes**: [what outcomes they highlight]
**Review ratings**:
- G2: [rating] ([count] reviews)
- Capterra: [rating] ([count] reviews)
---
## SEO & Content Strategy
**Organic strength**:
- Estimated monthly organic traffic: [number]
- Organic keywords (top 10): [count]
- Organic traffic value: $[estimated]
**Top organic pages** (by estimated traffic):
1. [page URL] — [keyword] — [est. traffic]
2. [page URL] — [keyword] — [est. traffic]
3. [page URL] — [keyword] — [est. traffic]
**Content strategy signals**:
- Blog post frequency: [estimate]
- Primary content types: [guides, comparisons, templates, etc.]
- Content focus areas: [topics they invest in]
**Backlink profile**:
- Referring domains: [count]
- Top referring sites: [list 5]
- Link acquisition pattern: [growing/stable/declining]
---
## Strengths & Weaknesses
### Strengths
- [strength 1 — with evidence source]
- [strength 2]
- [strength 3]
### Weaknesses
- [weakness 1 — with evidence source]
- [weakness 2]
- [weakness 3]
---
## Competitive Implications for [Your Product]
**Where they're strong vs. us**: [areas where this competitor has an advantage]
**Where we're strong vs. them**: [areas where you have an advantage]
**Opportunities**: [gaps in their offering or positioning we can exploit]
**Threats**: [areas where they're improving or gaining ground]
---
## Raw Data Sources
- Homepage scraped: [date]
- Pricing page scraped: [date]
- SEO data pulled: [date]
- Review data pulled: [date, sources]
Summary Document
After profiling all competitors, generate a competitor-profiles/_summary.md that includes:
- Competitor landscape overview — one paragraph summarizing the competitive field
- Comparison table — key metrics side by side for all profiled competitors
- Positioning map — where each competitor sits (e.g., simple↔complex, cheap↔premium)
- Key takeaways — 3-5 strategic observations from the research
- Gaps and opportunities — where the market is underserved
Quick Scan vs. Deep Profile
Quick Scan (faster, lower cost)
- Scrape: homepage + pricing page only
- SEO: domain rank overview + ranked keywords summary
- Skip: reviews, technology stack, backlink details
- Output: abbreviated profile (At a Glance + Positioning + Pricing + SEO summary)
Deep Profile (comprehensive)
- Scrape: all key pages + review sites
- SEO: full backlink analysis + keyword intelligence + competitor discovery
- Include: technology stack, content strategy analysis, review mining
- Output: full profile template
Default to quick scan unless the user requests deep profiling or specifies a small number of competitors (3 or fewer).
Handling Multiple Competitors
When profiling more than one competitor:
- Parallelize scraping — scrape all competitors' homepages simultaneously, then pricing pages, etc.
- Use consistent metrics — pull the same DataForSEO metrics for every competitor so profiles are comparable
- Build the summary last — after all individual profiles are complete
- Prioritize by relevance — if the user has 10+ competitors, suggest profiling the top 5 first based on domain overlap or market similarity
Updating Profiles
Profiles are snapshots. When updating:
- Check pricing pages first (most volatile)
- Re-pull SEO metrics (traffic and rankings shift monthly)
- Scan changelog for product changes
- Update the "Generated" date
- Note what changed since last profile in a
## Change Logsection at the bottom
Task-Specific Questions
Only ask if not answered by context or input:
- What competitor URLs should I profile?
- Quick scan or deep profile?
- Any specific dimensions to focus on (pricing, SEO, positioning)?
- Should I compare findings against your product?
Related Skills
- competitor-alternatives: For creating comparison/alternative pages from these profiles
- customer-research: For mining reviews and community sentiment in depth
- content-strategy: For using competitor content gaps to plan your own content
- seo-audit: For auditing your own site relative to competitors
- sales-enablement: For turning profiles into battle cards and sales collateral
- paid-ads: For analyzing competitor ad strategies
- pricing-strategy: For deeper pricing analysis informed by competitor profiles