> For the complete documentation index, see [llms.txt](https://safary-1.gitbook.io/safary-doc-2.0/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://safary-1.gitbook.io/safary-doc-2.0/dashboards/attribution.md).
# Attribution
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## Table of Contents
1. [Tutorials](#tutorials) (Q3 2025)
2. [First click Attribution Model ](#first-click-attribution-model)
3. [Channels Source ](#channel-source)
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## Tutorials (Q3 2025)
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## First click Attribution Model
Safary uses **a "first click" attribution model.** This means the source is determined by where a user first came from. Users retain this source tag throughout their lifetime, even when they return through different channels. First click attribution works well for crypto because users typically visit websites multiple times before making decisions.
{% hint style="info" %}
Many crypto users are labeled as "Direct" traffic, meaning they access your website by typing its name directly into Google or their browser's URL bar. We recommend implementing the Safary script before launch to identify these users' true traffic sources before they develop the habit of accessing your site directly.
{% endhint %}
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## Visualize your Full Funnel
We built the attribution table to make it easy for you to recreate your full funnel and identify the conversion rates of your website.
* Add multiple columns based to visualize all your events
* Group by **channels, campaigns or device**
{% hint style="info" %}
The Attribution table will only show **Connected Users** and **Connect Wallets.** We exclude the users imported through CSV or the wallets imported through Farcaster or socials which haven't been connected to your website.
{% endhint %}