The Model Comparison Tool (or Attribution Models 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.

Attribution models can be broadly classified into two categories:

  1. Baseline Attribution Models
  2. Custom Attribution Models

Baseline attribution models are the pre-built attribution models available in Universal Analytics.

Custom attribution models are user defined attribution models.

Following are the examples of baseline attribution models available in Universal Analytics:

  1. First touch attribution model
  2. Last touch attribution model
  3. Linear attribution model
  4. Position based attribution model
  5. Time Decay attribution model
  6. Last Non Direct click attribution model
  7. Last Adwords Click attribution model
  8. Data Driven Attribution model

 

If you want to learn more about these attribution models (including how to create custom attribution models), then please check out the following two posts:

  1. Google Analytics Attribution Modelling – Beginners Guide
  2. 6 Keys to Digital Success in Attribution Modelling

Through Model Comparison tool you can compare different baseline and custom attribution models to each other.

This comparison is carried out to determine how a marketing channel can be valued from different perspective.

For example let us determine how organic search can be valued from different perspective.

Follow the steps below:

Step-1: Click on ‘Model Comparison Tool’ link (under Conversions > Attribution menu) in your Universal Analytics View (or profile)

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-tool

Step-4: Select ‘Conversions and Value’ from the drop down menu located in the middle of your ‘model comparison tool’ report:

conversion-value

 

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

percent-change-conversion

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%.

That means that 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.

It also means that ‘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.

  • Universal Analytics make an arrow coloured when the change in conversions is 10% or more.
  • If the change is positive and is 10% or more than the arrow gets green color.
  • If the change is negative and 10% or more than the arrow gets red color.

Similarly,

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

That means that 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.

It also means that ‘organic search’ is undervalued by 8.60% under last click attribution model when this model is compared with ‘time decay’ attribution model.

The upward arrow next to 8.60% indicates positive change in conversions from last interaction model. Since the change in conversions is less than 10%, Universal Analytics has not made this arrow coloured.

 

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 because after all it is just an average value and we all are committed to report and analyse above average.

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 etc.

Now you may want to know why I picked these 3 particular attribution models for analysis: Last interaction, last non-direct click and time decay.

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

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

I selected ‘time decay’ model because it is less crappy than first click, linear, position based and last adwords click attribution models.

To know more about why other attribution models are more crappy, please read the post: 6 Keys to Digital Success in Attribution Modelling

 

But if I have the option to use ‘data driven attribution model’ then i would use it instead of ‘time decay’ model.

Other post you will find informative: How to use Agile Analytics to quickly solve your Conversion problems 


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Himanshu Sharma

Certified web analyst and founder of OptimizeSmart.com

My name is Himanshu Sharma and I help businesses in finding and fixing their Google Analytics and conversion issues.
  • More than ten years' experience in SEO, PPC and web analytics
  • Certified web analyst (master level) from MarketMotive.com
  • Google Analytics certified
  • Google AdWords certified
  • Nominated for Digital Analytics Association Award for Excellence
  • Bachelors degree in Internet Science
  • Founder of OptimizeSmart.com and EventEducation.com
I am also the author of the book Maths and Stats for Web Analytics and Conversion Optimization If you have any questions or comments please contact me