# Track SaaS competitor product launches on LinkedIn

**Use case:** 

Discover public LinkedIn posts about SaaS product launches for competitive research. Collect AI-filtered announcements, post text, author links and available engagement in a spreadsheet. Replace the topic with a competitor or product name to focus your research. Results reflect publicly indexed posts, not every company announcement.

## Input

```json
{
  "keywords": [
    "SaaS product launch"
  ],
  "maxPostsPerKeyword": 10,
  "country": "us"
}
```

## Output

```json
{
  "imageUrl": {
    "label": "Main image",
    "format": "string"
  },
  "authorName": {
    "label": "Author name",
    "format": "string"
  },
  "authorHeadline": {
    "label": "Author headline",
    "format": "string"
  },
  "text": {
    "label": "Post text",
    "format": "string"
  },
  "reactionsCount": {
    "label": "Reactions",
    "format": "integer"
  },
  "commentsCount": {
    "label": "Comments",
    "format": "integer"
  },
  "postedAt": {
    "label": "Posted at",
    "format": "string"
  },
  "postUrl": {
    "label": "Post URL",
    "format": "string"
  },
  "searchKeyword": {
    "label": "Search topic",
    "format": "string"
  },
  "isRelevant": {
    "label": "AI relevant",
    "format": "boolean"
  },
  "relevanceProbability": {
    "label": "Relevance probability",
    "format": "number"
  }
}
```

## About this Actor

This example demonstrates how to use [LinkedIn Post Search Scraper 2$/1K](https://apify.com/lofomachines/linkedin-post-search-scraper.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/lofomachines/linkedin-post-search-scraper.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/lofomachines/linkedin-post-search-scraper.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`).