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

# Understanding attribution

> An introductory guide to first-party vs. in-platform attribution and how to interpret these numbers

***

## What is first-party attribution

First-party attributed conversions are conversions based on your first-party data that's tracked in Converge. This is based on tracking parameters that are added to the links of your ads, like `cvg_source=facebook`, and our ability to create profiles of your users.

Because users can have multiple sessions before they purchase, the same purchase can be attributed to different channels based on the [attribution model](/attribution/channels#changing-the-attribution-model-of-your-first-party-conversions) you pick.

In the flowchart below, based on a **first-touch** model, the purchase should be attributed to Meta. Based on a **last-touch** model, the purchase should be attributed to Google.

```mermaid actions={false} theme={null}
flowchart LR
  id1("Person visits website with source **Meta**") -. 5 days later .-> id2("Person visits website with source **Google**") --- id3(["**Purchase**  ✓ "])
  style id3 color:#02b802,stroke:none
```

## What is in-platform attribution

In-platform conversions are conversions as calculated by the attribution model of the ad platform itself. For example, when you use the *"7-day click, 1-day view"* model in Meta and look at the Facebook Ads Manager, you see all conversions that Facebook believes came from a click on the ad in the last 7 days or a view of the ad in the last day.

This is typically the model that the ad platform will use itself to optimize its ad targeting.

## Which attribution method should I choose to make decisions?

You should typically include both numbers in your decision-making, as they both have their own strengths and weaknesses.
You can find a summary of both methods below.

| Attribution Model           | Strengths                                                                                                                                               | Weaknesses                                                                                                                                                                                                   |
| --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **First-party attribution** | **Great for relative comparisons**: First-party metrics allow you to compare all channels based on the same attribution model.                          | **May be less accurate**: First-party attribution can't account for view-through conversions or stitch sessions across devices.                                                                              |
| **In-platform attribution** | **Better accuracy**: In-platform metrics are usually more accurate because ad platforms have more data to attribute (they know which users viewed ads). | **Hard to compare across traffic sources**: Every ad platform employs different attribution models, making it hard to compare conversions. Some channels (e.g., Organic) don't have in-platform attribution. |

As a general rule of thumb, first-party attribution is better for relative comparisons **across traffic sources**, and in-platform-based metrics are better for checking performance **within a traffic source** (e.g., comparing the number of different Meta campaigns against each other).

## Known limitations of first-party attribution in relative comparisons

Although first-party attribution is better for relative comparisons, it comes with some known limitations.

**First-party attribution typically underreports top-of-funnel channels** (e.g., Meta and TikTok)

Because first-party tracking doesn't work across devices and doesn't have any information on view-through conversions, it tends to underreport top-of-funnel activity (sessions early in the customer funnel). The longer an average customer takes to convert, the more underreported these channels will be.

**First-party attribution typically overreports conversions to search and brand traffic**

Because first-party tracking might miss earlier sessions until conversion, it tends to overreport channels that are later in the customer journey, such as brand or search traffic.