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

# Creating a Lookalike Model

> Learn how to set up a new lookalike model to expand your audience reach.

Lookalike models use machine learning to find users who behave similarly to a specific publisher "seed" audience. This guide walks you through the process of creating a new model.

## Prerequisites

Before you begin, ensure you have:

* A high-quality **publisher seed segment** (e.g., a custom cohort of email subscribers or converters).
* At least **1,000 unique users per day** in your seed segment for optimal accuracy.
* At least **10-20 active custom cohorts** in your project to provide enough behavioral signals.

<Steps>
  ### Access the Models Tab

  Log into the Permutive dashboard and navigate to **Modeled Cohorts** in the left-hand navigation bar. Then, click on the **Models** tab.

  ### Start a New Model

  Click the **+ Add Model** button. You will be prompted to choose the type of model you want to create. Select **Lookalike**.

  ### Select Your Publisher Seed Segment

  Choose the publisher cohort you want to use as your seed.

  <Note>
    Only matched cohorts or custom cohorts can be used as seed segments.
  </Note>

  ### Configure Advanced Settings (Optional)

  You can further refine your model by using the following options:

  * **Include Segments**: Restrict the model to only consider users within specific cohorts.
  * **Exclude Segments**: Ignore users in specific cohorts during the modeling process.
  * **Fixed Set**: Manually select the specific cohorts the model should use as behavioral signals (advanced users only).

  ### Build the Model

  Click **Build Lookalike Model**.
</Steps>

## What Happens Next?

Once you click build, Permutive starts the training process.

* **Training Time**: It typically takes up to **2 hours** for a model to finish training.
* **Status**: The model will show as "Updating" or "In Progress" until it is ready.
* **Result**: Once complete, you will see a **Precision vs. Reach** curve, which you can use to create lookalike cohorts.

<Warning>
  If your seed segment was created on the same day as the model, the build may fail or show 0 reach until a full day of data has been processed.
</Warning>