# LinkedIn data

Many companies are used to rely on LinkedIn as their source of truth, and Kernel offers the same data for companies migrating onto Kernel data to assist with change management.

#### Problem: Resolving the entity-LinkedIn matching

Many companies have multiple LinkedIn profiles (including duplicates and non-official pages). Typical data vendors often rely on LinkedIn as a source of truth for foundational company data. Still, they incorrectly assume that companies have only one LinkedIn profile or use the LinkedIn website itself as the source of truth. However, this approach is insufficient.

* Starbucks alone has 100+ LinkedIn profiles
* Google's [LinkedIn profile](https://www.linkedin.com/company/google) is associated with [`goo.gle/3DLEokh`](https://goo.gle/3DLEokh), a short link to their careers site.
* In your CRM, Frito-Lay may be incorrectly associated with `linkedin.com/company/frito-lay-inc/`, which looks correct, but isn't.

#### Kernel's LinkedIn matching research agent

To solve accurately for this, Kernel takes advantage of the entity data and a bespoke LinkedIn matching research agent.

Kernel's LinkedIn mapping takes place in two steps

{% stepper %}
{% step %}
**Candidate generation**

Kernel maintains a database of all LinkedIn profiles (updated monthly). For each company, Kernel generates a long list of potential candidates.
{% endstep %}

{% step %}
**Candidate ranking**

Kernel ranks all profiles using a custom algorithm that uses semantic similarity, headcount, LinkedIn followers, and how much of the LinkedIn profile is complete.
{% endstep %}

{% step %}
**Candidate selection**

Kernel uses an AI-based approach to candidate selection, comparing the data of the top candidates against unstructured data of the target account.
{% endstep %}
{% endstepper %}

The result is to add missing LinkedIn accounts to your CRM and replace incorrect mappings with correct ones, allowing the SDRs and AEs to look up the correct profile.

{% hint style="info" %}
Kernel provides all data points from a company's LinkedIn profile as part of its [foundational data](/data/foundational-data.md).
{% endhint %}

## LinkedIn fields

| Field                                | Source   |
| ------------------------------------ | -------- |
| Name                                 | LinkedIn |
| Company description                  | LinkedIn |
| Headcount - Associated profiles      | LinkedIn |
| Company size                         | LinkedIn |
| Industry                             | LinkedIn |
| Country                              | LinkedIn |
| State                                | LinkedIn |
| City                                 | LinkedIn |
| Company address                      | LinkedIn |
| Founded year                         | LinkedIn |
| Company type (e.g. "Privately held") | LinkedIn |
| Headcount growth (12 months)         | LinkedIn |
| Headcount growth (24 months)         | LinkedIn |
| Last funding round                   | LinkedIn |
| Funding amount                       | LinkedIn |
| Funding date                         | LinkedIn |

{% hint style="info" %}
For Kernel's own firmographic data like **Headcount**, **Revenue**, and **HQ**, see @Foundational data, which uses Kernel's research agents to actively research and determine these values across multiple sources.
{% endhint %}


---

# 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.kernel.ai/data/linkedin-data.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.