Google Analytics Attribution Modelling: A Comprehensive Guide

Last Modified: December 29th, 2022

Google Analytics Attribution Model

Digital marketing has overtaken the traditional forms of advertising in nearly all fields. This can be attributed to the increasing number of online platforms that businesses can use to run their Digital Ad campaigns. Examples of such platforms include Facebook, Instagram, YouTube, and several others.

Many are the times you will find a single enterprise using different digital platforms to advertise their brand. Using such platforms to run digital marketing campaigns alone is not enough. Every business must track the outcome of each ad campaign to know more about its performance. 

Thanks to Google Analytics, a tool from Google that makes this easier for you. Google Analytics comes with a feature called Attribution Modeling that can help you identify the sources or channels that led to a particular desired outcome, like a sale or a subscription. This can help you know where to focus most of your effort on. In this article, we will be discussing Google Analytics Attribution Modelling and the method for setting it up. 

This can help the business know the platforms driving the highest number of conversions or sales and where there is a need for an improvement as it may be challenging to track the performance of digital ad campaigns manually. 

Table of Contents

Introduction to Google Analytics

Google Analytics Logo - Google Analytics Attribution Model
Image Source:

Google Analytics is a Web Analytics service that provides users with statistical and analytical information. It is highly useful & helps in managing Search Engine Optimization (SEO) and product marketing operations. It is free of cost service available to every Google user.

It visualizes data using its interactive features such as dashboard, motion charts, and scorecards to display real-time changes in data. Using Google Analytics, you can generate a custom report that meets your business requirements.

For further information on Google Analytics, you can check the official website here.

Understanding Attribution Modeling

Attribution Modeling Illustration - Google Analytics Attribution Model
Image Source:

An Attribution Model is a set of rules used to assign credit for conversions to the touchpoints in a customer’s journey. In most cases, a customer’s experience covers multiple site interactions and it’s good to know everything that drove their conversion. 

Attribution can be complicated when dealing with multiple channels. For example, a customer may click a Facebook link that takes them to an e-commerce website to view a product. The same consumer can also visit the same product page via an email promotion. Finally, the same customer may click an organic search listing, view the product, and consummate the purchase. 

Identifying the source that is responsible for the sale, whether Facebook, email, or organic search is called Attribution. 

Simplify your Data Analysis with Hevo’s No-code Data Pipelines

Hevo Data, a No-code Data Pipeline helps to transfer data from 100+ sources including 30+ Free sources like Google Analytics to a Data Warehouse/Destination of your choice to visualize it in your desired BI tool. Hevo is fully managed and completely automates the process of not only loading data from your desired source but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss.

It provides a consistent & reliable solution to manage data in real-time and always have analysis-ready data in your desired destination. It allows you to focus on key business needs and perform insightful analysis using a BI tool of your choice.


Check out what makes Hevo amazing:

  • Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
  • Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
  • Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
  • Hevo Is Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
  • Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
  • Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
  • Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.

Simplify your data analysis with Hevo today!


Default Google Analytics Attribution Models

Google Analytics has a total of seven default Attribution Models already built into the platform. You are free to choose any of these or switch to them, which you can do in just a few clicks. 

The following are the default Attribution Models offered in Google Analytics:

Google Analytics Attribution Model: Last-Touch Attribution

In this type of Attribution Model, 100% of the conversion’s credit is given to the last ad channel that the user interacted with, regardless of the number of interactions the user had made with the brand prior to conversion. 

Google Analytics Attribution Model: First-Touch Attribution

This is the opposite of the last-touch Attribution Model. It gives all credit to the first point of contact between the customer and the marketing channel. 

Google Analytics Attribution Model: Linear Attribution

In this type of Attribution Model, credit for the conversion is divided evenly across all the channels that the user came across in his path to conversion. 

Google Analytics Attribution Model: Time-Decay Attribution

In this model, more weight is given to the more recent points of contact. The last point of contact gets more credit, followed by the second last point of contact, and the credit continues to decline up the line until the first point of contact, which gets the least amount of credit. 

Google Analytics Attribution Model: Position-Based Attribution

This model gives the highest weight to the start and the finish of the path to conversion. The first and the last touch in the line of conversion are awarded 40% each. The remaining 20% of the touch is then distributed evenly among all the touches in the middle. 

Google Analytics Attribution Model: Last Non-Direct Click

In this model, Attribution is given to the last point of contact that did not result from a direct visit to a website. Google Analytics uses it as the default Attribution Model. This means that if you haven’t changed the Attribution Model in your dashboard, it’s the one your account is using. 

Google Analytics Attribution Model: Last Google Ads Click

In this model, credit is only given to the last touch with a Google Ads product. It becomes very useful when evaluating how Google Ads campaigns performed in isolation from other strategies. 

Some businesses find the above Attribution Models enough to give them insights and guide their marketing strategies. However, other businesses find them not adequate, hence, a more customized approach is needed. 

More documentation regarding Default Google Analytics Attribution Models can be found here.

Steps to Set up/Change your Google Analytics Attribution Model

The following steps will help you set up your Google Analytics Attribution Model or change from one to another:

  • Step 1: Open your Google Analytics account then click “Attribution” from the vertical navigation pane on the left. 
Navigation Pane - Google Analytics Attribution Model
Image Source: Self

This will open a window showing the different Attribution Models offered by the platform. 

  • Step 2: Open your first Campaign page, then click the Keywords tab to see the reporting table. 
  • Step 3: Click “Columns”, “Custom Conversions”, and then the “Google Analytics” button. 
  • Step 4: Click the “Create” button to build a new column. This is where you should choose an Attribution Model and the campaign data will be filtered based on the chosen model. If you simply want to change the current Attribution Model, just edit the existing column instead of creating a new one. 
  • Step 5: Select your metric from the list of the available options. This will be the Attribution Model to be used for contextualizing your data. 
  • Step 6: Click the “Save” button to save the changes and continue using the selected Attribution Model. 

Steps to Build a Custom Google Analytics Attribution Model

Some businesses don’t get the insights that they need from the default Attribution Models. Such businesses resort to creating custom Attribution Models. The following steps can help you create a custom Google Analytics Attribution Model:

  • Step 1: Select “Attribution” from the vertical navigation pane on the left. 
  • Step 2: Click the “Attribution Modeling Tool” from the left. 
  • Step 3: Select a Floodlight Configuration. 
  • Step 4: Click the first available Attribution Model and scroll downwards through the list of the available Attribution Models. Click the “Create new custom model” option. You can also edit the existing custom Attribution Models or copy them to create new ones. 
  • Step 5: Give a name to your custom model. 
  • Step 6: Select the baseline model. This is the Attribution Model that you need to modify. The customization options presented will depend on the baseline model that you choose. 
  • Step 7: For each area that you need to customize, click “Off” so as to turn the customization options on. 
  • Step 8: Click the “Save and Apply” button. 

The custom model will then be applied to your current setup. It will also be saved to the Floodlight configuration so that you can reuse it when running the Attribution Modeling Tool for the configuration. 

Limitations of Setting up Attribution Modeling in Google Analytics

The following are the limitations of setting up Attribution Modeling in Google Analytics:

  • All the default Attribution Models provided by Google Analytics don’t account for the true/real contribution of each channel towards a conversion. 
  • The process of creating a custom Attribution Model in Google Analytics is lengthy and complex. 
  • Attribution does not account for the offline to online effects that lead to conversions. 


In this article, you have learned about the basics of Attribution Modeling, the default Attribution Models offered by Google Analytics. You also learned the methods to set up or change Attribution Models in Google Analytics. There was also a description of the method to create a custom Attribution Model in Google Analytics.

Automated integration with your Data Warehouses/multiple data sources and the analytics database can make your choice much simpler as a lot of necessary features can be integrated readily.


Integrating and analyzing data from a huge set of diverse sources can be challenging, this is where Hevo comes into the picture. Hevo Data, a No-code Data Pipeline helps you transfer data from free sources like Google Analytics or a source of your choice in a fully automated and secure manner without having to write the code repeatedly. Hevo with its strong integration with 100+ sources & BI tools, allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.

Want to take Hevo for a spin?

SIGN UP and experience the feature-rich Hevo suite first hand.

Share your experience of understanding Google Analytics Attribution Modelling in the comments section below!

Nicholas Samuel
Freelance Technical Content Writer, Hevo Data

Skilled in freelance writing within the data industry, Nicholas is passionate about unraveling the complexities of data integration and data analysis through informative content for those delving deeper into these subjects.

No-code Data Pipeline For Your Data Warehouse