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apify-audience-analysis - Claude MCP Skill

Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.

SEO Guide: Enhance your AI agent with the apify-audience-analysis tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to understand audience demographics, preferences, behavior patterns, and engagement quality across face... Download and configure this skill to unlock new capabilities for your AI workflow.

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Documentation

SKILL.md
# Audience Analysis

Analyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior 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 audience 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 Audience Analysis Type

Select the appropriate Actor based on analysis needs:

| User Need | Actor ID | Best For |
|-----------|----------|----------|
| Facebook follower demographics | `apify/facebook-followers-following-scraper` | FB followers/following lists |
| Facebook engagement behavior | `apify/facebook-likes-scraper` | FB post likes analysis |
| Facebook video audience | `apify/facebook-reels-scraper` | FB Reels viewers |
| Facebook comment analysis | `apify/facebook-comments-scraper` | FB post/video comments |
| Facebook content engagement | `apify/facebook-posts-scraper` | FB post engagement metrics |
| Instagram audience sizing | `apify/instagram-profile-scraper` | IG profile demographics |
| Instagram location-based | `apify/instagram-search-scraper` | IG geo-tagged audience |
| Instagram tagged network | `apify/instagram-tagged-scraper` | IG tag network analysis |
| Instagram comprehensive | `apify/instagram-scraper` | Full IG audience data |
| Instagram API-based | `apify/instagram-api-scraper` | IG API access |
| Instagram follower counts | `apify/instagram-followers-count-scraper` | IG follower tracking |
| Instagram comment export | `apify/export-instagram-comments-posts` | IG comment bulk export |
| Instagram comment analysis | `apify/instagram-comment-scraper` | IG comment sentiment |
| YouTube viewer feedback | `streamers/youtube-comments-scraper` | YT comment analysis |
| YouTube channel audience | `streamers/youtube-channel-scraper` | YT channel subscribers |
| TikTok follower demographics | `clockworks/tiktok-followers-scraper` | TT follower lists |
| TikTok profile analysis | `clockworks/tiktok-profile-scraper` | TT profile demographics |
| TikTok comment analysis | `clockworks/tiktok-comments-scraper` | TT comment engagement |

### 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., `apify/facebook-followers-following-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):**
```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 audience members/profiles analyzed
- File location and name
- Key demographic insights
- Suggested next steps (deeper analysis, segmentation)

## 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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Information

Repository
arlenagreer/claude_configuration_docs
Author
arlenagreer
Last Sync
5/10/2026
Repo Updated
5/7/2026
Created
4/10/2026

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