apify-easy-competitive-intelligence

Before you write a rival up for your own team, this reads their pricing pages, their customer reviews and their job ads as they stand today, and cites where every fact came from.

WHEN TO USE

SCOPE

USE FOR

Build a full battlecard on a competitor for a board presentation.
Compare a competitor's pricing tiers and add-ons in detail.
Summarize what customers say in reviews across sites like G2 and Reddit.
See what a competitor is hiring for as a signal of where they're investing.
Map out who the players are in a market and how they're positioned.

This is a saved copy of the skill's SKILL.md instructions. It may differ from the upstream file or the version you install.

In this document (8)

Competitive Intelligence

Real-time competitive intelligence powered by live web data via Apify actors. Never answer competitive questions from training knowledge alone. Always gather live data first, then analyze.

Prerequisites

Apify CLI v1.5.0+ (npm install -g apify-cli), or Apify MCP server
Authenticated session (apify login or APIFY_TOKEN env var)

CLI rules: Always pass --json, --user-agent apify-awesome-skills/apify-easy-competitive-intelligence, and 2>/dev/null.

Run actor: apify actors call "ACTOR_ID" -i 'INPUT' --user-agent apify-awesome-skills/apify-easy-competitive-intelligence --json 2>/dev/null → returns run metadata with defaultDatasetId
Fetch results: apify datasets get-items DATASET_ID --user-agent apify-awesome-skills/apify-easy-competitive-intelligence --format json > /tmp/results.json 2>/dev/null — save locally, parse from file:
- Quick extraction: jq '.[] | "\(.field1) | \(.field2)"' /tmp/results.json
- Aggregation: python3 -c "import json; d=json.load(open('/tmp/results.json')); ..."
- Tabular: --format csv > /tmp/results.csv + python3 with csv.DictReader
- Flags: --limit N, --offset N, --format json|jsonl|csv|xlsx|xml
- Output fields: apify datasets info DATASET_ID --json | jq .fields
Fetch schema: apify actors info "ACTOR_ID" --input --user-agent apify-awesome-skills/apify-easy-competitive-intelligence --json 2>/dev/null

If CLI is unavailable and Apify MCP server is connected, use MCP call-actor / fetch-actor-details / get-actor-output directly.

Authentication

If a CLI command fails with an auth error, authenticate using one of these methods:

OAuth (interactive): apify login (opens browser)
Environment variable: export APIFY_TOKEN=your_token_here
From .env file: source .env (if the file contains APIFY_TOKEN=...)

Generate token: https://console.apify.com/settings/integrations

Actor Registry

Every actor call follows three steps:

Read — find the actor's section in reference/actor-schemas.md. Use the exact verified input and follow the "How to find" instructions for URLs/slugs.
Discover — verify platform URLs and slugs (e.g. via SERP) as described in the actor's schema section. Do not guess — wrong slugs silently return empty or wrong data.
Run — call the actor with verified input.

Alternatively, fetch the live schema: apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-easy-competitive-intelligence --input --json 2>/dev/null

Data Need	Actor	Notes
Google SERP	`apify/google-search-scraper`	Supports country/language. SERP snippets contain ratings & review counts
Page scrape	`apify/website-content-crawler`	proxyConfiguration REQUIRED. Returns markdown
RAG browse	`apify/rag-web-browser`	Search + scrape in one call. Good fallback
LinkedIn company	`dev_fusion/Linkedin-Company-Scraper`	Output in KV store, not dataset
LinkedIn jobs	`curious_coder/linkedin-jobs-scraper`	Requires LinkedIn search URL, NOT keywords
Crunchbase	`pratikdani/crunchbase-companies-scraper`	Single company URL per call
Amazon product	`junglee/Amazon-crawler`	Product or category URLs
Amazon reviews	`web_wanderer/amazon-reviews-extractor`	May return 0 for some products
Walmart product	`e-commerce/walmart-product-detail-scraper`	May return empty
Google Maps reviews	`compass/Google-Maps-Reviews-Scraper`	Use full Google Maps place URL
G2 reviews	`automation-lab/g2-scraper`	NPS, ratings, switching data. $0.04/run
Capterra reviews	`zen-studio/capterra-reviews-scraper`	$1.99/1K
Gartner Peer Insights	—	No working actor. Use SERP snippet mining as fallback
Glassdoor	`memo23/glassdoor-scraper-ppr`	Reviews, salaries, culture, ratings
Reddit	`harshmaur/reddit-scraper`	Posts + full comment threads
Google Play reviews	`neatrat/google-play-store-reviews-scraper`	App ID or Play Store URL
App Store	`jdtpnjtp/apple-app-store-scraper`	Requires SHADER proxy — may not be available on all plans
SimilarWeb	`pro100chok/similarweb-scraper`	Minimum 10 domains per call
Google News	`data_xplorer/google-news-scraper-fast`	No boolean operators in keywords
Wayback Machine	`andok/wayback-machine-scraper`	Full URL including path

Core Workflow

Step 0: Understand the User (once, at start)

Clarify before gathering data:

Role — Analyzed company, competitor, investor, consultant?
Decision — Entering market, defending position, choosing vendor, building battlecard?
Autonomy — Checkpoints after initial findings, or autopilot?

Steps 1–7

Clarify scope — Identify competitors. Select module(s). Default geography: US.
Read module reference — Load reference/modules/<module>.md for gathering + analysis instructions.
Gather live data — For each actor call, follow the three-step pattern: Read (actor-schemas.md) → Discover (SERP for URLs) → Run (call actor). Use PRIMARILY actors from the Actor Registry above.
Checkpoint (if not autopilot) — Present first findings, confirm direction.
Analyze — Select framework, lead with narrative, support with tables.
Verify — Run pre-delivery verification (reference/verification-checklist.md). Check: every claim has a source URL, every major finding has a confidence label, inferences are labeled as such. Remove any ungrounded claims.
Deliver — End with strategic recommendations framed for the user's role.

Framework Selection

Situation	Framework
Profile one competitor	SWOT
Market dynamics & forces	Porter's Five Forces
Visual position comparison	Strategy Canvas (Blue Ocean)
Why customers switch	Jobs-to-be-Done
Find white space	Positioning Matrix (2x2)
Predict competitor reaction	Competitive Response Matrix

Data Collection Rules

Prefer structured actors over website-content-crawler when a dedicated actor exists.
Cost budget — 3-8 actor calls per snapshot. Track total, warn at 15+.
Parallelize independent call-actor calls in a single response.
Failures — Report every failure explicitly (actor, input, error). Retry with corrected input if the cause is obvious. If retry fails, try rag-web-browser as fallback. Never silently skip a failed data source.
Cite everything — Include source URLs for every data point.
Async for long runs — Set async: true for actors >30s, poll with get-actor-run.
Protected platforms — Do NOT use website-content-crawler or rag-web-browser for: g2.com, capterra.com, gartner.com, glassdoor.com, reddit.com, linkedin.com. Use dedicated actors.

Apify vs. WebSearch

Apify required: review sites (G2, Capterra, Gartner, Glassdoor), LinkedIn, Reddit, Amazon, Walmart, app stores, SimilarWeb, Crunchbase, Wayback Machine, Google Maps reviews, news (Google News actor).

WebSearch/WebFetch sufficient (Claude Code built-in tools): competitor discovery, general company info, blog posts, publicly accessible pricing pages.

Data Validation & Grounding

Every factual claim needs a source URL. No link = not a fact.
Confidence labels are mandatory. Mark every major finding: High (primary source), Medium (2+ third-party sources), Low (single third-party source). Format: [Confidence | Source]. No report without labels.
Data tiers: Verified (primary source) → Reported (third-party, attribute) → Inferred (label as "this suggests...") → Ungrounded (omit).
Numbers are dangerous — employee counts, revenue, funding change fast. Always cite source and date.
Empty results ARE intelligence — 0 jobs = not hiring, 0 SimilarWeb = small site, 12 reviews = low adoption.
Cross-reference — Single-source claims are unverified. Multi-source (G2 + Capterra + Reddit) = pattern.

Module Selection

User says...	Module	Reference
"Analyze [competitor]", "Tell me about [company]"	Competitor Snapshot	`reference/modules/competitor-snapshot.md`
"Compare pricing", "How much does [X] cost"	Pricing Intelligence	`reference/modules/pricing-intelligence.md`
"Pricing details", "per-use-case costs", "tiers", "add-ons"	Pricing Deep Dive	`reference/modules/pricing-deep-dive.md`
"What do customers think", "Reviews", "Pain points"	Review Intelligence	`reference/modules/review-intelligence.md`
"What are they hiring for", "Job postings"	Hiring Signals	`reference/modules/hiring-signals.md`
"How do they rank", "Content strategy", "SEO"	Content & SEO	`reference/modules/content-seo.md`
"Who are the players", "Market landscape"	Market Landscape	`reference/modules/market-landscape.md`
"Full battlecard", "Deep analysis", "Board prep"	Multi-Module	`reference/multi-module-playbook.md`

Account or credentials required

1 FOR YOU

01
Install and authenticate the Apify CLI
Install apify-cli (npm install -g apify-cli) and authenticate with apify login or an APIFY_TOKEN environment variable from Apify Console → Settings → Integrations.
```
npm install -g apify-cli
```
```
apify login
```

This skill ships inside the Apify Community Skills plugin.

Run this outside your AI tool, using Node.js 22.20.0 or newer. Skills CLI 1.7.2 skips skill selection; prompts cancel installation without an interactive terminal. If choosing Project when asked about installation scope, open your project's folder before running this.

Install checklist

Check selected tools if a picker appears; Claude Code may be unchecked under Additional agents. ↑/↓ moves, Space toggles selections, Enter confirms.
Without a tool picker, check Installing to: for your intended tool. Stop if it names a different tool.
If asked, choose Symlink (Recommended) for shared files or Copy to all agents for separate copies; review the summary before confirming installation.
Install the find-skills skill? defaults to Yes, adding another skill for all projects. Choose No if you don't want that extra installation.

Skills CLI 1.7.2 sends install data to skills.sh by default, including the source, skill names, target tools and file details; GitHub sources are reported only when GitHub confirms the repository is public, while other remote sources can also be reported. Confirmed-public GitHub sources also trigger a security-audit request. Before installing, set the environment variable DO_NOT_TRACK=1 or DISABLE_TELEMETRY=1 to disable both.

npx skills add apify/awesome-skills --skill "apify-easy-competitive-intelligence" --full-depth

After installing for Claude Code, open it in the installation project if you chose Project; Global makes the skill available across projects on this computer. Once Claude Code loads the skill, its description helps Claude decide when to use it.

If installation created a top-level skills folder that did not exist when your Claude Code session started, run /reload-skills in that session. Run it again after later changes in that folder.

View on GitHub

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