Default and Custom Attribution Models in Google Analytics

This article is in conjunction with the article: Beginners guide to Attribution Modelling in Google Analytics where I introduced the concept of attribution modelling in the context of Google Analytics and explained the various components of attribution modelling in great detail.

So if you have not already read that article, then I would strongly suggest you read it first. The knowledge acquired through that article will help you greatly in understanding the present article.

Introduction to Google Analytics attribution models

An attribution model is a set of rules that determine how credit for conversions should be attributed/distributed to various touchpoints in a conversion path.

In the context of Google Analytics, attribution models can be broadly classified into two categories:

  1. Default attribution models
  2. Custom attribution models

Introduction to default attribution models in Google Analytics

The default attribution model (also known as baseline model) are pre-built models that define how credit for conversion should be distributed to various interactions (or touchpoints) in a conversion path before the custom credit rules are applied.

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Different types of default attribution models in Google Analytics

Google Analytics provides eight different types of attribution models. They are:

  1. Last interaction attribution model (popularly known as last-touch attribution model)
  2. First interaction attribution model (popularly known as First touch attribution model)
  3. Linear attribution model
  4. Time Decay attribution model
  5. Position based attribution model
  6. Last non-direct click model
  7. Last Ad Click
  8. Data-Driven Attribution Model

#1 Last interaction attribution model

The Last interaction attribution model assigns 100% credit for a conversion to the last interaction (or touchpoint) in a conversion path.

Google Analytics uses this model by default for Multi-channel funnel reports.

#2 First interaction attribution model

The First interaction attribution model assigns 100% credit for a conversion to the first interaction (or touchpoint) in a conversion path.

#3 Linear attribution model

The Linear attribution model assigns equal credit for a conversion to each interaction in a conversion path.

#4 Time decay attribution model

The Time Decay attribution model assign more credit to the interactions which are closest in time to the conversion.

#5 Position-based attribution model

The Position-based attribution model assigns 40% credit to the first interaction, 20% credit to the middle interactions and 40% credit to the last interaction.

#6 Last non-direct click attribution model

The Last non-direct click model assigns all the credit for conversions to the last non-direct click in a conversion path.

Google Analytics uses this model by default for non-Multi channel funnel reports.

#7 The last ad click attribution model

The Last Ad Click model assigns all the credit for conversions to the last Google Ads click in a conversion path.

#8 Data-driven attribution model

The Data-driven attribution model uses an algorithm to assign credit for conversions to various touchpoints in a conversion path.

For now, this model is available only in Google Analytics 360 (aka Google Analytics Premium) accounts.

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Which attribution model to use in Google Analytics

There is no one size fit all attribution model. The selection of the attribution model depends mainly on your business model and your advertising objectives.

For example, use the last touch attribution model when the least amount of buying consideration is involved. Use the first touch attribution model, if brand building/brand awareness is very important for you.

To learn more about selecting an attribution model, read this article: Which Attribution Model to use in Google Analytics?

How to view default attribution models available to you in Google Analytics

To view the default attribution models available to you, follow the steps below:

Step-1: Navigate to ‘Model Comparison Tool’  (under Conversions > Attribution) in your Google Analytics view:

model comparison tool

Step-2: Click on ‘Select Model’ drop-down menu:

select model drop down menu

You can then see the list of all available default attribution models in your GA view:

attribution model lists

Note: If you don’t see ‘Data-driven attribution’ model in the ‘Select Model‘ dialog box and you use GA premium/360, then it means this model is not enabled for your GA view.

Read this article, to enable this model: How to set up Data-driven attribution model in Google Analytics

Custom attribution models in Google Analytics

As the name suggests these attribution models are developed by people like me and you. They are user-defined attribution models.

When you build your own attribution model, you create your own rules to assign credit to different interactions in a conversion path. These rules are known by the name ‘custom credit rules’ in Google Analytics.

The proportional Multi-Touch attribution model is a good example of a custom attribution modelI developed this attribution model.

This model assigns credit to interactions in proportion to their contribution to conversion. This model is not supported by Google Analytics.

You can learn more about creating your attribution models, through this article: How to create a Custom Attribution Model in Google Analytics.

   

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Himanshu Sharma

Digital Marketing Consultant and Founder of Optimizesmart.com

Himanshu helps business owners and marketing professionals in generating more sales and ROI by fixing their website tracking issues, helping them understand their true customers' purchase journey and helping them determine the most effective marketing channels for investment.

He has over 12 years of experience in digital analytics and digital marketing.

He was nominated for the Digital Analytics Association's Awards for Excellence. The Digital Analytics Association is a world-renowned not-for-profit association that helps organisations overcome the challenges of data acquisition and application.

He is the author of four best-selling books on analytics and conversion optimization:

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