# LinkedIn Brand Mentions — HubSpot Posts, Last 3 Months

**Use case:** 

Track who is talking about HubSpot on LinkedIn by collecting the public posts that mention the brand in the last 3 months, newest first, without a LinkedIn login or cookies. Each row has the post URL, full text, author name, type and follower count, exact publish date, likes, comment count, the first public comments, hashtags, tagged people and companies, and image or video links.

## Input

```json
{
  "urls": [
    "HubSpot"
  ],
  "maxPosts": 15,
  "sortBy": "date",
  "postedLimit": "3months",
  "scrapeComments": true,
  "maxComments": 5,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

## Output

```json
{
  "author.avatar": {
    "label": "Avatar",
    "format": "image"
  },
  "author.name": {
    "label": "Author",
    "format": "text"
  },
  "postedAt.date": {
    "label": "Posted at",
    "format": "date"
  },
  "mediaType": {
    "label": "Media type",
    "format": "string"
  },
  "content": {
    "label": "Post text",
    "format": "string"
  },
  "engagement.likes": {
    "label": "Likes",
    "format": "number"
  },
  "engagement.comments": {
    "label": "Comments",
    "format": "number"
  },
  "linkedinUrl": {
    "label": "Post URL",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The LinkedIn Post Search Scraper (No Cookies) Actor is ready to run with the inputs already set for "LinkedIn Brand Mentions — HubSpot Posts, Last 3 Months". [Sign up or log in](https://console.apify.com/create-task-from-example/GDaSS0hf0kc1mfwQS) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "LinkedIn Brand Mentions — HubSpot Posts, Last 3 Months" task

The LinkedIn Post Search Scraper (No Cookies) Actor will start running based on the input automatically. You can also change all the input fields, like 🔎 search queries, post links or profile links, 📊 max posts per search, and more, to match your specific use case.

### 3. Receive the "LinkedIn Brand Mentions — HubSpot Posts, Last 3 Months" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as avatar, author, posted at, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "LinkedIn Brand Mentions — HubSpot Posts, Last 3 Months" task via API](https://apify.com/insights_data/linkedin-post-search-scraper-no-cookies.md).

## About this Actor

This example demonstrates how to use [LinkedIn Post Search Scraper (No Cookies)](https://apify.com/insights_data/linkedin-post-search-scraper-no-cookies.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/insights_data/linkedin-post-search-scraper-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/insights_data/linkedin-post-search-scraper-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`).