# Build an audience from a competitor's whole feed

**Use case:** 

Do not stop at one post. Give a profile URL and the Actor scans their recent posts, pulls everyone who engaged across all of them, merges duplicates into a single person and ranks the list by how often each person engaged. The result is the warmest audience in a niche in one run - the people who keep showing up, not the ones who liked a single post.

## Input

```json
{
  "linkedin_profile_url": "https://www.linkedin.com/in/example-competitor",
  "timeframe": "last_30_days",
  "max_posts": 25,
  "include_commenters": true,
  "include_reactors": true,
  "include_reposters": false
}
```

## Output

```json
{
  "full_name": {
    "label": "Name",
    "format": "text"
  },
  "first_name": {
    "label": "First name",
    "format": "text"
  },
  "middle_name": {
    "label": "Middle name",
    "format": "text"
  },
  "last_name": {
    "label": "Last name",
    "format": "text"
  },
  "phone_number": {
    "label": "Phone",
    "format": "text"
  },
  "job_title": {
    "label": "Job title",
    "format": "text"
  },
  "profile_headline": {
    "label": "Headline",
    "format": "text"
  },
  "profile_about": {
    "label": "About",
    "format": "text"
  },
  "current_company_name": {
    "label": "Company",
    "format": "text"
  },
  "company_industry": {
    "label": "Industry",
    "format": "text"
  },
  "company_website": {
    "label": "Company website",
    "format": "link"
  },
  "company_id": {
    "label": "Company ID",
    "format": "text"
  },
  "current_company_linkedin_url": {
    "label": "Company LinkedIn",
    "format": "link"
  },
  "job_description": {
    "label": "Job description",
    "format": "text"
  },
  "location": {
    "label": "Location",
    "format": "text"
  },
  "country": {
    "label": "Country",
    "format": "text"
  },
  "profile_link": {
    "label": "LinkedIn",
    "format": "link"
  },
  "linkedin_sales_link": {
    "label": "Sales Navigator",
    "format": "link"
  },
  "username": {
    "label": "Username",
    "format": "text"
  },
  "linkedin_id": {
    "label": "LinkedIn member ID",
    "format": "text"
  },
  "connections": {
    "label": "Connections",
    "format": "number"
  },
  "followers": {
    "label": "Followers",
    "format": "number"
  },
  "twitter_link": {
    "label": "Twitter",
    "format": "link"
  },
  "is_premium": {
    "label": "Premium",
    "format": "boolean"
  },
  "engagement_type": {
    "label": "Engagement",
    "format": "text"
  },
  "comment_text": {
    "label": "Comment",
    "format": "text"
  },
  "comment_url": {
    "label": "Comment URL",
    "format": "link"
  },
  "reaction_type": {
    "label": "Reaction",
    "format": "text"
  },
  "post_url": {
    "label": "Post URL(s)",
    "format": "link"
  },
  "post_author": {
    "label": "Post author",
    "format": "text"
  },
  "post_author_linkedin_url": {
    "label": "Post author LinkedIn",
    "format": "link"
  },
  "post_text": {
    "label": "Post text",
    "format": "text"
  },
  "source_influencer_profile_url": {
    "label": "Source thought leader",
    "format": "link"
  },
  "engagement_count": {
    "label": "Engagement count",
    "format": "number"
  },
  "unique_posts_engaged": {
    "label": "Unique posts engaged",
    "format": "number"
  },
  "posts_engaged_with": {
    "label": "Posts engaged with",
    "format": "array"
  }
}
```

## About this Actor

This example demonstrates how to use [LinkedIn Profile Engagers Scraper](https://apify.com/data-slayer/linkedin-audience-email-finder-no-cookies.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/data-slayer/linkedin-audience-email-finder-no-cookies.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/data-slayer/linkedin-audience-email-finder-no-cookies.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).