Attribution Model Comparison Tool in Google Analytics

  • Is organic search advertising (SEO) undervalued or overvalued?
  • If I invest in SEO, then how much incrementality does SEO can bring to my business bottom line?
  • How can I make my PPC campaigns more effective?
  • If I change my display advertising budget, how it will affect my website sales?

You can get answers to such questions by using the ‘Model Comparison Tool’ of Google Analytics.

Note: This article is related to attribution modelling in Google Analytics. If you are brand new to attribution modelling then I would suggest reading this article first: Beginners Guide to Google Analytics Attribution Modeling.

Introduction to The Model Comparison Tool

As the name suggests, the Model Comparison Tool (or Attribution Models Comparison Tool) is an attribution tool in Google Analytics, which is used to compare different attribution models to each other.

An attribution model is a set of rules which is used to determine how credit for conversions should be attributed to different marketing channels.

Through the Model Comparison Tool, you can compare different default and custom attribution models to each other. This comparison is carried out to determine how a marketing channel can be valued from a different perspective.

You can also use this tool to create custom attribution models in Google Analytics.

In order to access this tool, navigate to the Model Comparison Tool report  (under ‘Conversions’ > ‘Attribution) in your GA view:

In order to use this tool, select at least one attribution model from the ‘select model’ drop-down menu:

select-model

Note: You can compare up to three attribution models side by side through the Model Comparison Tool.

Attribution models in Google Analytics can be broadly classified into two categories:

  1. Default Attribution Models
  2. Custom Attribution Models

To learn more about baseline and custom attribution models, read this article: Default and Custom Attribution Models in Google Analytics

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Requirements for using The Model Comparison Tool

In order to use the Model Comparison Tool, you need to have ecommerce tracking and/or goal conversion tracking setup, in your GA reporting view.

Otherwise, you won’t see any data in the Model Comparison Tool report. What you will see instead when you navigate to the Model Comparison Tool report in GA, is the following message:

requires-tracking

In fact, without goals and/or ecommerce tracking set up, you can not use any multi-channel funnel and attribution report in GA.

Practical use of The Model Comparison Tool

Let us use the Model Comparison Tool to determine how organic search can be valued from a different perspective.

Follow the steps below:

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

Step-2: Set date range to the last three months or more.

Step-3: Compare the ‘last interaction’ model with ‘last non-direct click’ and ‘time decay’ models:

model comparison tool2

Now you may want to know, why I selected these three particular attribution models for analysis.

  • I selected the last interaction model because this is the default model used in multi-channel funnel reports in Google Analytics.
  • I selected the last non-direct click model because this is the default model used in non-multi-channel funnel reports in GA.
  • I selected the ‘time decay’ model because it is less crappy than other attribution models (First interaction, Linear, Last Adwords click and position based models).

Step-4: Select ‘Conversions and Value’ from the drop-down menu, located in the middle of your Model Comparison Tool report:

conversion and value

Step-5: Now look at the column named ‘% change in conversion (from last interaction)’ for ‘organic search’:percentage change in conversions

Form this report we can conclude that the % of change in conversion for organic search from the last interaction model to ‘last non-direct click’ attribution model is 21.61%.

What that means, if you use ‘last non-direct click’ attribution model (instead of last interaction model) to distribute credit for conversions to organic search, then the ‘organic search’ deserve 21.61% more credit for conversions.

In other words, ‘organic search’ is undervalued by 21.61% under last click attribution model (when this model is compared with ‘last non-direct click’ attribution model).

The upward green arrow next to 21.61% indicates a positive change in conversions from last interaction model.

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Similarly, the % of change in conversion for organic search from last interaction model to ‘time decay’ attribution model is 8.60%.

What that means, if you use ‘time decay’ attribution model (instead of last interaction model) to distribute credit for conversions to organic search then the ‘organic search’ deserves 8.60% more credit for conversions.

In other words, ‘organic search’ is undervalued by 8.60% under last click attribution model (when this model is compared with ‘time decay’ attribution model).

The upward grey arrow next to 8.60% indicates a positive change in conversions from last interaction model.

Now the million-dollar question, So what insight we have got from this analysis?

The insight is that overall organic search is undervalued by (21.61 + 8.60)/2 = 15.10%

You can now show this report to your client/boss and demand more budget for organic search campaign.

Note: Don’t take the value of 15.10% too seriously.

Conversely, if overall organic search turned out to be overvalued by …%, you know that your money would be better spent investing in other marketing channels or finding a new SEO service provider.

Similarly, through the Model Comparison Tool, you can evaluate other marketing channels like Paid Search, Email, Display, Social media, etc.

Other articles on Attribution Modelling

  1. How to analyse and report the true value of your SEO Campaign
  2. How to valuate Display Advertising through Attribution Modelling
  3. Understanding Shopping Carts for Analytics and Conversion Optimization
  4. 6 Keys to Digital Success in Attribution Modelling
  5. Google Analytics Attribution Modeling Tutorial
  6. How to Measure and Improve the Quality of SEO Traffic through Google Analytics
  7. How to explain attribution modelling to your clients
  8. Default and Custom Attribution Models in Google Analytics
  9. Understanding Missing Touchpoints in Attribution Modelling
  10. What You Should Know about Historical Data in Web Analytics
  11. Model Comparison Report Explained in Google Analytics Attribution
  12. Data-Driven Attribution Model in Google Analytics – Tutorial
  13. Conversion Lag Report Explained in Google Analytics Attribution
  14. Selecting the Best Attribution Model for Inbound Marketing
  15. How to do ROI Analysis in Google Analytics
  16. Conversion Credit Models Guide – Google Analytics Attribution
  17. Introduction to Nonline Analytics – True Multi Channel Analytics
  18. Conversion Types Explained in Google Analytics Attribution
  19. Attribution Channels Explained in Google Analytics Attribution
  20. Differences Between Google Attribution & Multi-Channel Funnel Reports
  21. Introduction to TV Attribution in Google Analytics Attribution 360
  22. Conversion Credit Distribution for Attribution Models in Google Analytics
  23. Conversion Paths Report Explained in Google Analytics Attribution
  24. Attribution Model Comparison Tool in Google Analytics
  25. Touchpoint Analysis in Google Analytics Attribution Modelling
  26. Attributed Conversions & Attributed Revenue Explained in Google Attribution
  27. Which Attribution Model to use in Google Analytics?
  28. Google Attribution Access and User Permissions – Tutorial
  29. Conversion Path Length Report Explained in Google Analytics Attribution
  30. How to set up a data-driven attribution model in Google Analytics
  31. View-Through Conversion Tracking in Google Analytics
  32. Offline Conversion Tracking in Google Analytics – Tutorial
  33. How to Create Custom Attribution Model in Google Analytics
  34. 8 Google Analytics Conversions Segments You Must Use
  35. You are doing Google Analytics all wrong. Here is why
  36. How to Use ZMOT to Increase Conversions and Sales Exponentially
  37. Connected Properties Explained in Google Analytics Attribution
  38. Marketing Mix Modelling or Attribution Modelling. Which one is for you?
  39. How is attribution modelling helpful for ecommerce and non-ecommerce websites?
  40. Conversion Time & Interaction Time Explained in Google Analytics Attribution
  41. How to Allocate Budgets in Multi Channel Marketing
  42. How Does Attribution Work?
  43. Data-Driven Attribution Model Explorer in Google Analytics
  44. Introduction to Attribution Beta – Attribution Project 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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