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apify-audience-analysis

Analyze audiences across Facebook, Instagram, YouTube, and TikTok using Apify Actors, tools that collect platform data. Gather follower, profile, or comment data, summarize audience characteristics and engagement patterns, and return results in chat, CSV, or JSON.

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原文查看原文说明

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

查看安装方法

适用场景

  • Understanding follower and profile characteristics
  • Analyzing audience reactions through comments
  • Exporting audience data as CSV or JSON
  • Comparing engagement patterns across social platforms

包含的文件(2)

  • SKILL.md5.2 KB
  • reference/scripts/run_actor.js11.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Audience Analysis

Analyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.

When to Use

  • You need audience demographics, engagement patterns, or follower behavior from social platforms.
  • The task is to choose and run Apify Actors for audience analysis across Facebook, Instagram, YouTube, or TikTok.
  • You need structured extraction plus a summarized interpretation of audience findings.

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 NeedActor IDBest For
Facebook follower demographicsapify/facebook-followers-following-scraperFB followers/following lists
Facebook engagement behaviorapify/facebook-likes-scraperFB post likes analysis
Facebook video audienceapify/facebook-reels-scraperFB Reels viewers
Facebook comment analysisapify/facebook-comments-scraperFB post/video comments
Facebook content engagementapify/facebook-posts-scraperFB post engagement metrics
Instagram audience sizingapify/instagram-profile-scraperIG profile demographics
Instagram location-basedapify/instagram-search-scraperIG geo-tagged audience
Instagram tagged networkapify/instagram-tagged-scraperIG tag network analysis
Instagram comprehensiveapify/instagram-scraperFull IG audience data
Instagram API-basedapify/instagram-api-scraperIG API access
Instagram follower countsapify/instagram-followers-count-scraperIG follower tracking
Instagram comment exportapify/export-instagram-comments-postsIG comment bulk export
Instagram comment analysisapify/instagram-comment-scraperIG comment sentiment
YouTube viewer feedbackstreamers/youtube-comments-scraperYT comment analysis
YouTube channel audiencestreamers/youtube-channel-scraperYT channel subscribers
TikTok follower demographicsclockworks/tiktok-followers-scraperTT follower lists
TikTok profile analysisclockworks/tiktok-profile-scraperTT profile demographics
TikTok comment analysisclockworks/tiktok-comments-scraperTT 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

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.

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