Building Lookalike Models

The Lookalike Model Builder provides an interface for marketers to quickly build custom machine learning models and Predictive Audiences based on customer data. In the Lytics UI, the Model Builder is located under the Lookalike Models tab within the Laboratory section.

To get started, click Create New Model at the top right.

This opens up the lookalike model builder.

Basic Configuration

For most use cases, building a model by setting the basic configuration parameters is sufficient. The only required parameters are the selection of a source and target audience, which are very important for building a usable model.

If you select audiences that are too dissimilar, the model may be unable to find lookalikes in the source audience. Learn more about selecting the right audiences for your use case. The size of each audience is also important.

When building a Lookalike Model, your source and target audience must have a minimum of 25 users and a maximum of 20 million users.

If your selected audience exceeds the maximum size, you can add filters to refine it. For example, if the source audience is “Unknown users” you could add a filter for “Active in the last 30 days” to ensure you aren’t targeting unknown users with stale cookie identifiers.

The basic model parameters are defined below.

Parameter	Description	Example
Source Audience	Select an existing audience as the source to find lookalikes from.	`users_who_signed_up_for_email`
Target Audience	Select an existing audience as the target (users you want to find more of).	`users_who_made_an_online_purchase`
Custom Model Name	If no custom model name is provided, the default name will be `Source_Segment_Slugname::Target_Segment_Slugname`. Cannot contain the characters: period, semicolon, forward slash, or back slash.	`my_model_name`
Auto Tune	Use an automated "intelligent" feature selection process and make a best attempt at building the healthiest model.	Checked
Model Training Only	Build a model without scoring users. Useful for testing and debugging purposes.	Checked

Even if you select Auto Tune, you can still specify advanced configuration options, like sample size. See the full list below.

Advanced Configuration

For additional model configuration, select the Advanced Options.

For manually built models (without Auto Tune), one or more features must be selected for the model build, such as Use Scores, Use Content, Additional Fields.

Parameter	Description	Example
Use Scores	Leverage Lytics Behavioral Scores as features for the model.	Checked
Use Content	Leverage Lytics Content Affinity as features for the model.	Checked
Additional Fields	Select fields in the user schema as features for the model.	`visit_count`
Blocked Fields	Select fields in the user schema to omit from the model.	`email_view`
Continuously Re-train	Retrains the model every week with a new training sample. If this option is not selected, the model will never re-train.	Unchecked
Sample Size	The sample size of users for the model training set. Allowable range: 100 - 50000 users.	`5000`