/apify-content-analytics

name: apify-content-analytics
description: Track engagement metrics, measure campaign ROI, and analyze content performance across Instagram, Facebook, YouTube, and TikTok.
risk: critical
source: community

Content Analytics

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

When to Use

• You need engagement, growth, or ROI metrics for posts, reels, videos, ads, or hashtags.
• The task is to use Apify Actors to collect cross-platform content performance data.
• You need exported analytics results and a concise interpretation of what content is performing best.

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 content analytics type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] 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 dynamically using mcpc:

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., `apify/instagram-post-scraper`).

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):**

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

**CSV:**

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:**

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` `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`

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.