Skill

Profile competitors from URLs with SEO and market data

A competitor-profiling skill combining Firecrawl site scraping and DataForSEO market data into structured, comparable profiles.

Works with firecrawldataforseog2capterraproducthunt

79
Spark score
out of 100
Updated 23 days ago
Version 2.6.0

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Why it matters

Generate comprehensive, structured competitor intelligence reports by scraping competitor websites, analyzing SEO metrics, gathering review data, and synthesizing findings into comparable profiles that reveal positioning, pricing, features, market presence, and strategic insights.

Outcomes

What it gets done

01

Scrape competitor websites to extract positioning, pricing, features, and messaging from key pages

02

Gather SEO metrics including domain authority, backlinks, organic keywords, and traffic estimates

03

Collect and analyze competitor reviews from G2, Capterra, and other platforms for sentiment themes

04

Synthesize raw data into structured markdown profiles with cross-competitor comparisons

Install

Add it to your toolbox

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-competitor-profiling | bash

Overview

Competitor Profiling

This skill scrapes competitor sites and reviews via Firecrawl, pulls SEO and market data via DataForSEO, and synthesizes structured, comparable competitor profiles with a cross-competitor summary document. Use it when researching, profiling, or analyzing competitors from their URLs. Defaults to a quick scan unless a deep profile or few competitors are specified.

What it does

This skill produces comprehensive, structured competitor profile documents by combining live site scraping with SEO and market data, first checking for existing product-marketing context to avoid re-asking known information. Four core principles guide it: facts over opinions, meaning every claim is traceable to a source and inferences are labeled; structured and comparable, meaning all profiles follow the same template for side-by-side comparison; current data, meaning dated snapshots with staleness flagged; and honest assessment, meaning no exaggerating weaknesses or downplaying strengths. Before synthesizing, it persists all raw scrape, SEO, and review data to a dated, per-competitor directory structure that is never overwritten by a later run, so profiles can be rebuilt or audited without re-running expensive API calls.

The research process runs three phases. The first maps a competitor's site to discover key pages - homepage, pricing, features, about, blog, customers or case studies, integrations, and changelog - scrapes each, and extracts specific fields per page type, such as the homepage's headline and value proposition, pricing tiers and billing terms, feature capabilities, founding story and team size, named customers and case study themes, integration count, and changelog release velocity, plus optional review scraping from sites like G2, Capterra, Product Hunt, and TrustRadius, extracting rating, review count, praise and complaint themes, and representative quotes. The second phase gathers SEO and market data: domain authority and backlinks, keyword and traffic intelligence including ranked keywords and estimated traffic and keyword gaps versus the user's own site, and competitive positioning data such as the competitor's closest organic rivals and highest-traffic pages. The third phase synthesizes the scraped content with the SEO data and cross-references claims against scale evidence, such as checking a claimed customer count against traffic and backlink scale.

Output is one markdown profile per competitor following a fixed template: an at-a-glance metrics table, positioning and messaging, product and features with capabilities and product-direction signals from the changelog, a pricing table, customers and social proof with review ratings, SEO and content strategy covering organic traffic and backlink profile, strengths and weaknesses with evidence sources, competitive implications covering opportunities and threats, and a raw data sources section. After all competitors are profiled, a cross-competitor summary document adds a landscape overview, a comparison table, a positioning map along axes like simple versus complex or cheap versus premium, key takeaways, and market gaps. It defaults to a faster, cheaper quick scan - homepage and pricing page only, with a domain-rank and keyword summary and no reviews or backlink detail - unless the user requests a deep profile or names three or fewer competitors, and for multiple competitors it parallelizes scraping by page type, uses consistent metrics across all of them for comparability, and builds the summary last. Updating an existing profile re-checks pricing first since it's the most volatile, re-pulls SEO metrics, scans the changelog, and logs what changed since the last snapshot.

When to use - and when NOT to

Use it when researching, profiling, or analyzing competitors from their URLs - competitor research, competitive intelligence, or a competitor deep dive.

Inputs and outputs

Given competitor URLs, a depth level, and optional focus areas, it produces per-competitor markdown profiles plus a cross-competitor summary, backed by persisted raw scrape, SEO, and review data for later re-use.

Integrations

Firecrawl for site and review scraping via map, scrape, and search, DataForSEO MCP tools for backlinks, ranked keywords, domain rank overview, competitor discovery, and top pages, plus related skills for comparison pages, prospecting, customer research, content strategy, SEO audits, sales enablement, ad analysis, and pricing.

Who it's for

Product marketers and competitive-intelligence analysts who need consistent, evidence-backed competitor profiles for positioning, sales enablement, or content-gap planning rather than one-off, inconsistent research notes.

Source README

Competitor Profiling

When to Use

Use this skill when you need when the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,'...

You are an expert competitive intelligence analyst. Your goal is to take a list of competitor URLs and produce comprehensive, structured competitor profile documents by combining live site scraping with SEO and market data.

Initial Assessment

Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered.

Before profiling, confirm:

  1. Competitor URLs - the list of competitor website URLs to profile
  2. Your product - what you do (if not in product marketing context)
  3. Depth level - quick scan (key facts only) or deep profile (full research)
  4. Focus areas - any specific dimensions to prioritize (e.g., pricing, positioning, SEO strength, content strategy)

If the user provides URLs and context is available, proceed without asking.


Core Principles

1. Facts Over Opinions

Every claim in a profile should be traceable to a source - scraped page content, review data, or SEO metrics. Label inferences clearly.

2. Structured and Comparable

All profiles follow the same template so they can be compared side by side. Consistency matters more than completeness on any single profile.

3. Current Data

Profiles are snapshots. Always include the date generated. Flag anything that looks stale (e.g., "pricing page last updated 2023").

4. Honest Assessment

Don't exaggerate competitor weaknesses or downplay their strengths. Accurate profiles are useful profiles.


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:

  1. Competitor landscape overview - one paragraph summarizing the competitive field
  2. Comparison table - key metrics side by side for all profiled competitors
  3. Positioning map - where each competitor sits (e.g., simple↔complex, cheap↔premium)
  4. Key takeaways - 3-5 strategic observations from the research
  5. 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:

  1. Parallelize scraping - scrape all competitors' homepages simultaneously, then pricing pages, etc.
  2. Use consistent metrics - pull the same DataForSEO metrics for every competitor so profiles are comparable
  3. Build the summary last - after all individual profiles are complete
  4. 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 Log section at the bottom

Task-Specific Questions

Only ask if not answered by context or input:

  1. What competitor URLs should I profile?
  2. Quick scan or deep profile?
  3. Any specific dimensions to focus on (pricing, SEO, positioning)?
  4. Should I compare findings against your product?

Related Skills

  • competitors: For creating comparison/alternative pages from these profiles
  • prospecting: For broader list-building qualification (this skill does deep research on specific accounts; prospecting builds the initial list)
  • 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
  • ads: For analyzing competitor ad strategies
  • pricing: For deeper pricing analysis informed by competitor profiles

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

FAQ

Common questions

Discussion

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