> ## Documentation Index
> Fetch the complete documentation index at: https://docs.smooth.sh/llms.txt
> Use this file to discover all available pages before exploring further.

# Real-time people enrichment

> Enrich contact profiles with real-time data

<Note>
  This guide demonstrates unauthenticated lookups. For authenticated access take a look at our [Guide: Scrape behind login walls](/guides/scrape-behind-login-walls).
</Note>

## Overview

This guide shows how to use Smooth to enrich people profiles with real-time social media data. You'll learn to extract public data from LinkedIn and Twitter, perfect for sales research, lead qualification, and competitive intelligence.

<Steps>
  <Step title="Find Latest LinkedIn Article">
    Extract the title and details of someone's most recent LinkedIn article or post.

    ```python Python theme={null}
    linkedin_enrichment_task = """
    Go to Bill Gates' LinkedIn profile and find his latest article.

    Extract:
    - Title of the latest article/post
    - Publication date
    - Brief summary of the content (2-3 sentences)
    - Number of likes/reactions if visible
    """
    ```
  </Step>

  <Step title="Execute LinkedIn Lookup">
    Run the enrichment task to get the latest LinkedIn article.

    ```python Python theme={null}
    from smooth import SmoothClient

    smooth_client = SmoothClient(api_key="cmzr-YOUR_API_KEY")

    task = smooth_client.run(
        task=linkedin_enrichment_task,
        enable_recording=True
    )

    print(f"Live URL: {task.live_url()}")
    task_result = task.result()
    print(f"Agent Response: {task_result.output}")
    print(f"Task Video: {task_result.recording_url}")
    ```

    The agent will navigate to the LinkedIn profile, identify the most recent article, and extract the relevant details.
  </Step>

  <Step title="Analyze Twitter Highlighted Posts">
    Extract topics and themes from someone's Twitter profile.

    ```python Python theme={null}
    twitter_enrichment_task = """
    Go to Bill Gates' Twitter profile and analyze the visible posts.

    Identify the top 3-5 themes or topics he frequently discusses.

    Return the top themes and topics he frequently discusses.
    """

    task = smooth_client.run(
        task=twitter_enrichment_task,
        enable_recording=True
    )

    result = task.result()
    print(f"Agent response: {result.output}")
    ```
  </Step>
</Steps>

## Use Cases

* **Sales Intelligence**: Research prospects before outreach calls
* **Competitive Analysis**: Track competitor executives' public statements
* **Partnership Research**: Understand potential partners' current focus areas
* **Media Monitoring**: Stay updated on key industry leaders' perspectives
* **Lead Qualification**: Assess prospect engagement and interests
* **Content Strategy**: Identify trending topics among target audiences

<Note>
  Smooth adapts and finds alternative ways to access the information even when social media platforms update their layouts.
</Note>

## Community

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  Join our community for support and showcases
</Card>