apify-audience-analysis
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
Best use case
apify-audience-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
Teams using apify-audience-analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/apify-audience-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How apify-audience-analysis Compares
| Feature / Agent | apify-audience-analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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`Related Skills
apify-ultimate-scraper
Universal AI-powered web scraper for any platform. Scrape data from Instagram, Facebook, TikTok, YouTube, Google Maps, Google Search, Google Trends, Booking.com, and TripAdvisor. Use for lead gener...
apify-trend-analysis
Discover and track emerging trends across Google Trends, Instagram, Facebook, YouTube, and TikTok to inform content strategy.
apify-market-research
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
apify-lead-generation
Generates B2B/B2C leads by scraping Google Maps, websites, Instagram, TikTok, Facebook, LinkedIn, YouTube, and Google Search. Use when user asks to find leads, prospects, businesses, build lead lis...
apify-influencer-discovery
Find and evaluate influencers for brand partnerships, verify authenticity, and track collaboration performance across Instagram, Facebook, YouTube, and TikTok.
apify-ecommerce
Scrape e-commerce data for pricing intelligence, customer reviews, and seller discovery across Amazon, Walmart, eBay, IKEA, and 50+ marketplaces. Use when user asks to monitor prices, track competi...
apify-brand-reputation-monitoring
Track reviews, ratings, sentiment, and brand mentions across Google Maps, Booking.com, TripAdvisor, Facebook, Instagram, YouTube, and TikTok. Use when user asks to monitor brand reputation, analyze...
Apify Automation
Automate web scraping and data extraction with Apify -- run Actors, manage datasets, create reusable tasks, and retrieve crawl results through the Composio Apify integration.
apify-actorization
Convert existing projects into Apify Actors - serverless cloud programs. Actorize JavaScript/TypeScript (SDK with Actor.init/exit), Python (async context manager), or any language (CLI wrapper). Us...
apify-actor-development
Develop, debug, and deploy Apify Actors - serverless cloud programs for web scraping, automation, and data processing. Use when creating new Actors, modifying existing ones, or troubleshooting Acto...
project-workflow-analysis-blueprint-generator
Comprehensive technology-agnostic prompt generator for documenting end-to-end application workflows. Automatically detects project architecture patterns, technology stacks, and data flow patterns to generate detailed implementation blueprints covering entry points, service layers, data access, error handling, and testing approaches across multiple technologies including .NET, Java/Spring, React, and microservices architectures.
stride-analysis-patterns
Apply STRIDE methodology to systematically identify threats. Use when analyzing system security, conducting threat modeling sessions, or creating security documentation.