/apify-easy-competitive-intelligence

name: apify-easy-competitive-intelligence
description: >
  This skill should be used when the user asks to "analyze a competitor",
  "compare pricing", "competitive landscape", "market research",
  "what do customers think", "review intelligence", "hiring signals",
  "content strategy", "SEO battle", "build a battlecard", "competitive analysis",
  "who are the players", "who competes with", "market intelligence",
  "competitive positioning", "deep dive on a company", "board prep",
  "SWOT analysis", "how does [X] compare to [Y]",
  or mentions competitor analysis, pricing comparison, customer sentiment,
  or market landscape research. Requires Apify CLI or Apify MCP server.
author: chocholous
author_url: https://github.com/chocholous
metadata:
  keywords: "competitive-intelligence, battlecard, pricing, reviews, hiring, seo, market-landscape, g2, capterra, glassdoor, linkedin, crunchbase, similarweb, swot, competitor, analysis"

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:

1. **OAuth (interactive):** `apify login` (opens browser) 2. **Environment variable:** `export APIFY_TOKEN=your_token_here` 3. **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: 1. **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. 2. **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. 3. **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

1. **Clarify scope** — Identify competitors. Select module(s). Default geography: US. 2. **Read module reference** — Load `reference/modules/<module>.md` for gathering + analysis instructions. 3. **Gather live data** —