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 bottomline?

# How can I make my PPC campaigns more effective?

# If I change my display adverising budget, how it will effect 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 to read this article first: Beginners Guide to Google Analytics Attribution Modeling.

Introduction to Model Comparison Tool

As the name suggest, 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 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 different perspective.

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

In order to access this tool, navigate to ‘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 3 attribution models side by side through 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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Requirement 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 ‘Model Comparison Tool’

Let us use ‘Model Comparison Tool’ to determine how organic search can be valued from 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 3 particular attribution models for analysis.

I selected last interaction model because this is the default model used in multi-channel funnel reports in Google Analytics.

I selected last non-direct click model because this is the default model used in non-multi-channel funnel reports in GA.

I selected ‘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 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 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’ deserve 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 positive change in conversions from last interaction model.

Now the million dollars 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 spend in investing in other marketing channels or finding a new SEO service provider.

Similarly, through model comparison tool you can valuate other marketing channels like Paid Search, Email, Display, Social media etc.

Other articles on Attribution Modelling in Google Analytics

  1. Touch Point Analysis in Google Analytics Attribution Modelling
  2. 8 Google Analytics Conversions Segments You Must Use
  3. Default and Custom Attribution Models in Google Analytics
  4. Attribution Model Comparison Tool in Google Analytics
  5. Which Attribution Model to use in Google Analytics?
  6. How to create Custom Attribution Model in Google Analytics

  1. How to do ROI Analysis in Google Analytics
  2. Google Analytics Attribution Modelling – Complete Guide
  3. Guide to Data Driven Attribution Model in Google Analytics
  4. Conversion Credit distribution for Attribution Models in Google Analytics
  5. You are doing Google Analytics all wrong. Here is why

  1. Marketing Mix Modelling or Attribution Modelling. Which one is for you?
  2. Introduction to Nonline Analytics – True Multi Channel Analytics
  3. How to set up Data driven attribution model in Google Analytics
  4. How to valuate Display Advertising through Attribution Modelling
  5. Understanding Shopping Carts for Analytics and Conversion Optimization

  1. View-through conversion tracking in Google Analytics
  2. Understanding Missing Touch Points in Attribution Modelling
  3. Guide to Offline Conversion Tracking in Google Analytics
  4. How to explain attribution modelling to your clients
  5. 6 Keys to Digital Success in Attribution Modelling

  1. How to use ZMOT to increase Conversions and Sales exponentially
  2. How to Measure and Improve the Quality of SEO Traffic through Google Analytics
  3. How to analyse and report the true value of your SEO Campaign
  4. How to allocate Budgets in Multi Channel Marketing
  5. What You Should Know about Historical Data in Web Analytics

  1. Google Analytics Not Provided Keywords and how to unlock and analyze them
  2. Selecting the Best Attribution Model for Inbound Marketing
  3. Introduction to TV attribution in Google Analytics Attribution 360
  4. Cross Device Reports in Google Analytics via Google Signals
  5. Data-Driven Attribution Model Explorer in Google Analytics
  6. What is Attribution Modelling and why it is the ‘key’ to online business success?
  7. How Does Attribution Work?
  8. How is Attribution Modelling helpful for e-commerce and non-e-commerce websites?

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Himanshu Sharma

Certified web analyst and founder of OptimizeSmart.com

My name is Himanshu Sharma and I help businesses find and fix their Google Analytics and conversion issues. If you have any questions or comments please contact me.

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