apify

apify-audience-analysis

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# Install this skill:
npx skills add apify/agent-skills --skill "apify-audience-analysis"

Install specific skill from multi-skill repository

# Description

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

# SKILL.md


name: apify-audience-analysis
description: Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.


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 (for fetching Actor schemas)

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:

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):

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 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

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.