apify-competitor-intelligence

Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.

16 stars

Best use case

apify-competitor-intelligence is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.

Teams using apify-competitor-intelligence should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/apify-competitor-intelligence/SKILL.md --create-dirs "https://raw.githubusercontent.com/diegosouzapw/awesome-omni-skill/main/skills/backend/apify-competitor-intelligence/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/apify-competitor-intelligence/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How apify-competitor-intelligence Compares

Feature / Agentapify-competitor-intelligenceStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Competitor Intelligence

Analyze competitors using Apify Actors to extract data from multiple platforms.

## Prerequisites
(No need to check it upfront)

- `.env` file with `APIFY_TOKEN`
- Node.js 20.6+ (for native `--env-file` support)
- `mcpc` CLI tool: `npm install -g @apify/mcpc`

## Workflow

Copy this checklist and track progress:

```
Task Progress:
- [ ] Step 1: Identify competitor analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings
```

### Step 1: Identify Competitor Analysis Type

Select the appropriate Actor based on analysis needs:

| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Competitor business data | `compass/crawler-google-places` | Location analysis |
| Competitor contact discovery | `poidata/google-maps-email-extractor` | Email extraction |
| Feature benchmarking | `compass/google-maps-extractor` | Detailed business data |
| Competitor review analysis | `compass/Google-Maps-Reviews-Scraper` | Review comparison |
| Hotel competitor data | `voyager/booking-scraper` | Hotel benchmarking |
| Hotel review comparison | `voyager/booking-reviews-scraper` | Review analysis |
| Competitor ad strategies | `apify/facebook-ads-scraper` | Ad creative analysis |
| Competitor page metrics | `apify/facebook-pages-scraper` | Page performance |
| Competitor content analysis | `apify/facebook-posts-scraper` | Post strategies |
| Competitor reels performance | `apify/facebook-reels-scraper` | Reels analysis |
| Competitor audience analysis | `apify/facebook-comments-scraper` | Comment sentiment |
| Competitor event monitoring | `apify/facebook-events-scraper` | Event tracking |
| Competitor audience overlap | `apify/facebook-followers-following-scraper` | Follower analysis |
| Competitor review benchmarking | `apify/facebook-reviews-scraper` | Review comparison |
| Competitor ad monitoring | `apify/facebook-search-scraper` | Ad discovery |
| Competitor profile metrics | `apify/instagram-profile-scraper` | Profile analysis |
| Competitor content monitoring | `apify/instagram-post-scraper` | Post tracking |
| Competitor engagement analysis | `apify/instagram-comment-scraper` | Comment analysis |
| Competitor reel performance | `apify/instagram-reel-scraper` | Reel metrics |
| Competitor growth tracking | `apify/instagram-followers-count-scraper` | Follower tracking |
| Comprehensive competitor data | `apify/instagram-scraper` | Full analysis |
| API-based competitor analysis | `apify/instagram-api-scraper` | API access |
| Competitor video analysis | `streamers/youtube-scraper` | Video metrics |
| Competitor sentiment analysis | `streamers/youtube-comments-scraper` | Comment sentiment |
| Competitor channel metrics | `streamers/youtube-channel-scraper` | Channel analysis |
| TikTok competitor analysis | `clockworks/tiktok-scraper` | TikTok data |
| Competitor video strategies | `clockworks/tiktok-video-scraper` | Video analysis |
| Competitor TikTok profiles | `clockworks/tiktok-profile-scraper` | Profile data |

### Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

```bash
export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"
```

Replace `ACTOR_ID` with the selected Actor (e.g., `compass/crawler-google-places`).

This returns:
- Actor description and README
- Required and optional input parameters
- Output fields (if available)

### Step 3: Ask User Preferences

Before running, ask:
1. **Output format**:
   - **Quick answer** - Display top few results in chat (no file saved)
   - **CSV** - Full export with all fields
   - **JSON** - Full export in JSON format
2. **Number of results**: Based on character of use case

### Step 4: Run the Script

**Quick answer (display in chat, no file):**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'
```

**CSV:**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv
```

**JSON:**
```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json
```

### Step 5: Summarize Findings

After completion, report:
- Number of competitors analyzed
- File location and name
- Key competitive insights
- Suggested next steps (deeper analysis, benchmarking)


## Error Handling

`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
`mcpc not found` - Ask user to install `npm install -g @apify/mcpc`
`Actor not found` - Check Actor ID spelling
`Run FAILED` - Ask user to check Apify console link in error output
`Timeout` - Reduce input size or increase `--timeout`

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