apify-content-analytics

---
name: apify-content-analytics
description: Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
license: Apache-2.0
---

# Content Analytics

Track and analyze content performance using Apify Actors to extract engagement metrics from multiple platforms.

## Prerequisites
(No need to check it upfront)

- `.env` file with `APIFY_TOKEN`
- Node.js 20.6+ (for native `--env-file` support)

## Workflow

Copy this checklist and track progress:

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

### Step 1: Identify Content Analytics Type

Select the appropriate Actor based on analytics needs:

| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Post engagement metrics | `apify/instagram-post-scraper` | Post performance |
| Reel performance | `apify/instagram-reel-scraper` | Reel analytics |
| Follower growth tracking | `apify/instagram-followers-count-scraper` | Growth metrics |
| Comment engagement | `apify/instagram-comment-scraper` | Comment analysis |
| Hashtag performance | `apify/instagram-hashtag-scraper` | Branded hashtags |
| Mention tracking | `apify/instagram-tagged-scraper` | Tag tracking |
| Comprehensive metrics | `apify/instagram-scraper` | Full data |
| API-based analytics | `apify/instagram-api-scraper` | API access |
| Facebook post performance | `apify/facebook-posts-scraper` | Post metrics |
| Reaction analysis | `apify/facebook-likes-scraper` | Engagement types |
| Facebook Reels metrics | `apify/facebook-reels-scraper` | Reels performance |
| Ad performance tracking | `apify/facebook-ads-scraper` | Ad analytics |
| Facebook comment analysis | `apify/facebook-comments-scraper` | Comment engagement |
| Page performance audit | `apify/facebook-pages-scraper` | Page metrics |
| YouTube video metrics | `streamers/youtube-scraper` | Video performance |
| YouTube Shorts analytics | `streamers/youtube-shorts-scraper` | Shorts performance |
| TikTok content metrics | `clockworks/tiktok-scraper` | TikTok analytics |

### Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details:

```bash
node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/fetch_actor_details.js --actor "ACTOR_ID"
```

Replace `ACTOR_ID` with the selected Actor (e.g., `apify/instagram-post-scraper`).

This returns:
- Actor info (title, description, URL, categories, stats, rating)
- README summary
- Input schema (required and optional parameters)

### Step 3: Ask User Preferences

**Skip this step** for simple lookups (e.g., "what's Nike's follower count?", "find me 5 coffee shops in Prague") — just use quick answer mode and move to Step 4.

For larger scraping tasks, 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

**Cost safety**: Always set a sensible result limit in the Actor input (e.g., `maxResults`, `resultsLimit`, `maxCrawledPages`, or equivalent field from the input schema). Default to 100 results unless the user explicitly asks for more. Warn the user before running large scrapes (1000+ results) as they consume more Apify credits.

### 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 content pieces analyzed
- File location and name
- Key performance insights
- Suggested next steps (deeper analysis, content optimization)


## Error Handling

`APIFY_TOKEN not found` - Ask user to create `.env` with `APIFY_TOKEN=your_token`
`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`