# Sales Navigator Search

## Sales Navigator Search

{% hint style="danger" %}
No emails will be found with this method. If emails are required, use [Parvenu](/apps/data-cleaning/data-cleaning-form/sources/parvenu.md) as a source instead. 
{% endhint %}

1. Connect your Linkedin account to Big Brain. 

{% hint style="info" %}
You must have a Sales Navigator account to use this feature. 
{% endhint %}

{% content-ref url="/pages/yZZiZaybxmHCo6r9K8Xf" %}
[Connect a New Linkedin Account](/apps/linkedin-outreach/accounts/connect-a-new-linkedin-account.md)
{% endcontent-ref %}

&#x20;  2\. Make a search in Sales Navigator<br>

An example Sales Navigator search

```
https://www.linkedin.com/sales/search/people?query=(recentSearchParam%3A(id%3A2154972922%2CdoLogHistory%3Atrue)%2Cfilters%3AList((type%3ACURRENT_TITLE%2Cvalues%3AList((text%3Acmo%2CselectionType%3AINCLUDED)))%2C(type%3AREGION%2Cvalues%3AList((id%3A101318387%2Ctext%3AFlorida%252C%2520United%2520States%2CselectionType%3AINCLUDED)))))&sessionId=JvpqspLLTomjxIEu3yi8lQ%3D%3D&viewAllFilters=true
```

{% hint style="info" %}
Each Sales Navigator search must be 2500 contacts or less. If your search has more than 2500 contacts, split it into smaller searches. IE if you have 10000 contacts in your search of the United States, try that same search with only California to return fewer results per search. Read more on how to do this [here](https://docs.parvenu.io/best-practices/splitting-large-searches).&#x20;
{% endhint %}

&#x20;  3\. Paste your Sales Navigator search URL in the Data Cleaning App.&#x20;

&#x20;   4\. Input a list name that describes the prospects in the search.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.big-brain.co/apps/data-cleaning/data-cleaning-form/sources/sales-navigator-search.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.