Understanding: How to map UTMs in Dreamdata

Updated by Steen Voersaa

Note: This article is the third in a series of three articles, each covering what you need to know to fully comprehend UTMs and their usage.

Check out the two previous ones: 
Understanding: Source, channel, and event
Understanding: UTM mapping rules

In this help document, we'll explain how Dreamdata's UTM mapping UI works and how you should treat the rules input.

Dreamdata provides a tool for mapping UTM parameters and referrer information into Channel and Source. These mappings are known as rules, and they will be applied to every session.

Rule Priority

The rule priority determines which rule to apply when multiple rules could apply. You specify priority by dragging individual rules up or down in the list of rules. Rules at the top of the list take priority over rules further down the list.

Rule Input: Event, UTM Source, UTM Medium, UTM Campaign, URL, Referrer.

In addition to priority, each rule is made up of six input fields: Event, UTM Source, UTM Medium, UTM Campaign, URL, and Referrer. Note that Event in this context means a tracking event.

For each input, you can use '%' as a wildcard. For instance, '%' means match anything, 'face%' means match anything that starts with 'face', and 'Facebook' means match exactly 'Facebook'. Matching is case-sensitive.

Rule Output: Channel, Source

On the right side of each rule is the output section, which is made up of two fields: Channel and Source. Channel is used to describe the main lead channel, e.g., Paid or Organic, and Source is used to describe the entity that sent the user, e.g., Google.

You can either set a value for the field directly, e.g., 'Paid', or you can pass the value of the utm_source parameter by using '[source]'.

Updating Data Models

When you modify the UTM mapping table, it will impact your model the next time we build the data models.

This normally happens everyday within 12 to 24 hours based on your plan. However, You can now trigger your own data model run so that you won't have to wait 12-24 hours. 

Mapping LLMs like ChatGPT, Gemini, and Perplexity

You can use UTM mapping to map LLMs to appropriate channels and sources.

Here we have mapped ChatGPT, Gemini, and Perplexity to Organic LLM channel

Updating Data Models

When you modify the UTM mapping table, it will impact your model the next time we build the data models.

This normally happens everyday within 12 to 24 hours based on your plan. However, You can now trigger your own data model run so that you won't have to wait 12-24 hours. 

We have a large set of default mappings that ensure that for most cases this happens out of the box. You can download the full list of utm mappings applied on your account by clicking the download button.

How did we do?