# Find Agency Recommendation Requests on LinkedIn

**Use case:** 

This task retrieves LinkedIn posts specifically requesting agency recommendations, such as 'looking for SEO agency.' It focuses on posts made in the last month, providing insights into current engagement and demand for services. Ideal for understanding market needs and identifying potential leads.

## Input

```json
{
  "query": [
    "recommend agency",
    "looking for SEO agency"
  ],
  "excludeWords": "course webinar",
  "country": [
    "us",
    "gb"
  ],
  "hashtags": [
    "hiring",
    "ai"
  ],
  "contentType": "POST",
  "hasComments": "",
  "isHiring": "",
  "hasLink": "",
  "postedWithinHours": 48,
  "timeRelevance": "lastMonth",
  "postedAfter": "2026-09-01T00:00:00Z",
  "postedBefore": "2026-09-05T00:00:00Z",
  "parsedWithinHours": 24,
  "parsedAfter": "2026-09-01T00:00:00Z",
  "parsedBefore": "2026-09-02T00:00:00Z",
  "authorType": "any",
  "sortBy": "newest",
  "limit": 25,
  "offset": 0
}
```

## Output

```json
{
  "postKey": {
    "label": "Post Key",
    "format": "text"
  },
  "text": {
    "label": "Text",
    "format": "text"
  },
  "hashtags": {
    "label": "Hashtags",
    "format": "text"
  },
  "contentType": {
    "label": "Content Type",
    "format": "text"
  },
  "author": {
    "label": "Author",
    "format": "text"
  },
  "authorUrl": {
    "label": "Author URL",
    "format": "link"
  },
  "authorType": {
    "label": "Author Type",
    "format": "text"
  },
  "createdAt": {
    "label": "Posted At",
    "format": "text"
  },
  "geo": {
    "label": "Geo",
    "format": "text"
  },
  "likes": {
    "label": "Likes",
    "format": "number"
  },
  "commentsCount": {
    "label": "Comments",
    "format": "number"
  },
  "hasLink": {
    "label": "Has Link?",
    "format": "boolean"
  },
  "isHiring": {
    "label": "Hiring?",
    "format": "boolean"
  },
  "likesPerHour": {
    "label": "Likes / Hour",
    "format": "number"
  },
  "commentsPerHour": {
    "label": "Comments / Hour",
    "format": "number"
  },
  "postUrl": {
    "label": "Post URL",
    "format": "link"
  },
  "comments": {
    "label": "Parsed Comments",
    "format": "text"
  }
}
```

## How it works

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

The LinkedIn Posts Search - Bulk, Hiring, Country& Comments search Actor is ready to run with the inputs already set for "Find Agency Recommendation Requests on LinkedIn". [Sign up or log in](https://console.apify.com/create-task-from-example/tgZP7uk64il0paxFD) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Find Agency Recommendation Requests on LinkedIn" task

The LinkedIn Posts Search - Bulk, Hiring, Country& Comments search Actor will start running based on the input automatically. You can also change all the input fields, like search queries, exclude words, and more, to match your specific use case.

### 3. Receive the "Find Agency Recommendation Requests on LinkedIn" 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 post key, text, hashtags, 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 "Find Agency Recommendation Requests on LinkedIn" task via API](https://apify.com/sandhive/linkedin-posts-parser.md).

## About this Actor

This example demonstrates how to use [LinkedIn Posts Search - Bulk, Hiring, Country& Comments search](https://apify.com/sandhive/linkedin-posts-parser.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/sandhive/linkedin-posts-parser.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/sandhive/linkedin-posts-parser.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`).