apify-audience-analysis

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)

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify audience analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema
- [ ] 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:

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/facebook-followers-following-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):

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 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