Data-Driven Attribution Model Explorer in Google Analytics
- What is Model Explorer in Google Analytics?
- Eligibility criteria for using Data-Driven Attribution Model Explorer
- How to access the Model Explorer report in Google Analytics
- How to read the Model Explorer report
- What is weighted average conversion credit?
- What exactly is ‘weight’?
- The colour coding used in the Model Explorer report
- How to determine the overall weight of marketing channels under data-driven attribution
- Downloading the MCF Data-Driven Attribution Model
What is Model Explorer in Google Analytics?
As the name suggests, the Model Explorer report is used to explore an attribution model.
The attribution model that is explored is the most recently generated MCF data-driven attribution model for the selected time period.
Through the Model Explorer report, you can do the following:
- Visualize and analyze your MCF DDA model.
- Determine how the DDA model distributed conversion credit to each of the marketing channels defined in the ‘default channel grouping’.
Eligibility criteria for using Data-Driven Attribution Model Explorer
The primary requirement for accessing and using the Model Explorer report is access to GA360. The Model Explorer report is not available in the standard version of Google Analytics.
Following are the other main requirements for using the Model Explorer:
- Goal conversion and/or ecommerce conversion data in your GA360 enabled reporting view.
- The cost data from Google Ads and/or non-Google ads campaign.
- The DDA model is enabled for your reporting view.
- At least 30 days of historical data in your reporting view in order to make the data statistically significant for data analysis. This data includes ecommerce data, goal conversion data, cost data, and website usage data.
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How to access the Model Explorer report in Google Analytics
To access the Model Explorer report follow the steps below:
- Navigate to the GA360 enabled reporting view.
- Make sure that the DDA model has been enabled and at least a week has elapsed since the model was last enabled.
- Navigate to Conversions > Multi-Channel Funnels > Model Explorer report
Note: The Model Explorer report is still in BETA at the time of writing.
How to read the Model Explorer report
Here is how the Model Explorer report may look like:
The Model Explorer shows the four most influential interactions within the 90 days prior to each conversion and for each marketing channel defined in the ‘default channel grouping’.
Now you may be asking yourself, why the Model Explorer shows only the four most influential interactions.
Why does it not show say 10 or 15 most influential interactions?
That’s because according to Google, for most customers, the last four interactions comprise more than 85% of conversions. The model explorer report is based on this assumption.
This report assigns weighted average conversion credit to each of the four most influential interactions and for each marketing channel.
What is weighted average conversion credit?
The weighted average conversion credit is the weighted average of the conversion credits assigned to a marketing channel in a particular position on a conversion path.
The MCF DDA model calculates these weighted averages algorithmically based on users’ path data.
In order to understand the concept of ‘weighted average’, you would first need to know about the average metric.
Following is the general formula to calculate the average metric:
Average = sum of numbers/count of numbers
For example, the average of 2 and 3 is: (2 + 3) / 2 = 5 / 2 = 2.5
The weighted average is the average of numbers where some numbers carry more weight (importance) than others.
For example, consider the following scenario:
- Let us suppose that the numbers 2 and 3 represent touchpoints on a conversion path.
- Let us suppose that touchpoint 2 is 70% important in influencing the purchase behaviour of a user and touchpoint 3 is 30% important in influencing the purchase behaviour.
So, the weighted average = ((2 X 70%) + (3 X 30%)) / 2 = (1.4 + 0.9) /2 = 1.15
What exactly is ‘weight’?
In the context of attribution modelling in GA, the weight refers to the adjustment made to the conversion credit.
A marketing channel receiving weight is actually receiving conversion credit.
If a marketing channel receives more weight, it receives more conversion credit in a particular position on a conversion path. The heavier the weight, the higher the conversion credit.
Conversely, a marketing channel receiving less weight means it is receiving less conversion credit in a particular position on a conversion path. The lower the weight, the lower the conversion credit.
The colour coding used in the Model Explorer report
The Model Explorer report uses a dark colour to represent a high weighted average conversion credit. The darker the colour, the higher the weighted average.
Conversely, the lighter the colour, the lower the weighted average:
Sometimes a marketing channel does not play any role in a particular position on a conversion path. Whenever this situation occurs the Model Explorer uses a white colour with a dash (-) to display the interaction on the conversion path:
How to determine the overall weight of marketing channels under data-driven attribution
In order to determine the overall weight of marketing channels under data-driven attribution and in a particular time period, follow the steps below:
Step-1: Navigate to the Model Explorer report.
Step-2: Select the time period for which you want to see the DDA model.
Step-3: At the top left-hand side of the report, you should see the ‘Conversions’ drop-down menu. Make sure that the ‘All’ option is selected:
Step-4: Look at the ‘Conversions’ column in the report:
The marketing channel with a higher volume of data-driven conversions carries more weight in the selected time period.
If you want to determine the weight of marketing channels for a particular conversion type then select the conversion type from the ‘Conversion’ drop-down menu at the top left-hand side of the report:
Downloading the MCF Data-Driven Attribution Model
Through the Model Explorer report, you can also download the latest DDA model into Excel as a CSV file for further analysis.
You can do this by clicking on the ‘Download the full model’ button at the top right-hand side of the model explorer report:
It is important to keep in mind that the data you see in the downloaded MCF DDA model is unlikely to match with the DDA Model data you see in the Model Explorer report. According to Google, this is expected.
The data that you see in the downloaded MCF DDA model only includes those conversions whose conversion path length is two or more interactions and which were recorded within 28 days from the time the DDA model was last generated.
Whereas, the DDA Model data that you see in the Model Explorer report shows conversions based on the conversion type and the time period you selected for the report.
Other articles on Attribution Modelling
- How to analyse and report the true value of your SEO Campaign
- How to valuate Display Advertising through Attribution Modelling
- Understanding Shopping Carts for Analytics and Conversion Optimization
- 6 Keys to Digital Success in Attribution Modelling
- Google Analytics Attribution Modeling Tutorial
- How to Measure and Improve the Quality of SEO Traffic through Google Analytics
- How to explain attribution modelling to your clients
- Default and Custom Attribution Models in Google Analytics
- Understanding Missing Touchpoints in Attribution Modelling
- What You Should Know about Historical Data in Web Analytics
- Model Comparison Report Explained in Google Analytics Attribution
- Data-Driven Attribution Model in Google Analytics – Tutorial
- Conversion Lag Report Explained in Google Analytics Attribution
- Selecting the Best Attribution Model for Inbound Marketing
- How to do ROI Analysis in Google Analytics
- Conversion Credit Models Guide – Google Analytics Attribution
- Introduction to Nonline Analytics – True Multi Channel Analytics
- Conversion Types Explained in Google Analytics Attribution
- Attribution Channels Explained in Google Analytics Attribution
- Differences Between Google Attribution & Multi-Channel Funnel Reports
- Introduction to TV Attribution in Google Analytics Attribution 360
- Conversion Credit Distribution for Attribution Models in Google Analytics
- Conversion Paths Report Explained in Google Analytics Attribution
- Attribution Model Comparison Tool in Google Analytics
- Touchpoint Analysis in Google Analytics Attribution Modelling
- Attributed Conversions & Attributed Revenue Explained in Google Attribution
- Which Attribution Model to use in Google Analytics?
- Google Attribution Access and User Permissions – Tutorial
- Conversion Path Length Report Explained in Google Analytics Attribution
- How to set up a data-driven attribution model in Google Analytics
- View-Through Conversion Tracking in Google Analytics
- Offline Conversion Tracking in Google Analytics – Tutorial
- How to Create Custom Attribution Model in Google Analytics
- 8 Google Analytics Conversions Segments You Must Use
- You are doing Google Analytics all wrong. Here is why
- How to Use ZMOT to Increase Conversions and Sales Exponentially
- Connected Properties Explained in Google Analytics Attribution
- Marketing Mix Modelling or Attribution Modelling. Which one is for you?
- How is attribution modelling helpful for ecommerce and non-ecommerce websites?
- Conversion Time & Interaction Time Explained in Google Analytics Attribution
- How to Allocate Budgets in Multi Channel Marketing
- How Does Attribution Work?
- Data-Driven Attribution Model Explorer in Google Analytics
- Introduction to Attribution Beta – Attribution Project in Google Analytics
- What is Model Explorer in Google Analytics?
- Eligibility criteria for using Data-Driven Attribution Model Explorer
- How to access the Model Explorer report in Google Analytics
- How to read the Model Explorer report
- What is weighted average conversion credit?
- What exactly is ‘weight’?
- The colour coding used in the Model Explorer report
- How to determine the overall weight of marketing channels under data-driven attribution
- Downloading the MCF Data-Driven Attribution Model
What is Model Explorer in Google Analytics?
As the name suggests, the Model Explorer report is used to explore an attribution model.
The attribution model that is explored is the most recently generated MCF data-driven attribution model for the selected time period.
Through the Model Explorer report, you can do the following:
- Visualize and analyze your MCF DDA model.
- Determine how the DDA model distributed conversion credit to each of the marketing channels defined in the ‘default channel grouping’.
Eligibility criteria for using Data-Driven Attribution Model Explorer
The primary requirement for accessing and using the Model Explorer report is access to GA360. The Model Explorer report is not available in the standard version of Google Analytics.
Following are the other main requirements for using the Model Explorer:
- Goal conversion and/or ecommerce conversion data in your GA360 enabled reporting view.
- The cost data from Google Ads and/or non-Google ads campaign.
- The DDA model is enabled for your reporting view.
- At least 30 days of historical data in your reporting view in order to make the data statistically significant for data analysis. This data includes ecommerce data, goal conversion data, cost data, and website usage data.
How to access the Model Explorer report in Google Analytics
To access the Model Explorer report follow the steps below:
- Navigate to the GA360 enabled reporting view.
- Make sure that the DDA model has been enabled and at least a week has elapsed since the model was last enabled.
- Navigate to Conversions > Multi-Channel Funnels > Model Explorer report
Note: The Model Explorer report is still in BETA at the time of writing.
How to read the Model Explorer report
Here is how the Model Explorer report may look like:
The Model Explorer shows the four most influential interactions within the 90 days prior to each conversion and for each marketing channel defined in the ‘default channel grouping’.
Now you may be asking yourself, why the Model Explorer shows only the four most influential interactions.
Why does it not show say 10 or 15 most influential interactions?
That’s because according to Google, for most customers, the last four interactions comprise more than 85% of conversions. The model explorer report is based on this assumption.
This report assigns weighted average conversion credit to each of the four most influential interactions and for each marketing channel.
What is weighted average conversion credit?
The weighted average conversion credit is the weighted average of the conversion credits assigned to a marketing channel in a particular position on a conversion path.
The MCF DDA model calculates these weighted averages algorithmically based on users’ path data.
In order to understand the concept of ‘weighted average’, you would first need to know about the average metric.
Following is the general formula to calculate the average metric:
Average = sum of numbers/count of numbers
For example, the average of 2 and 3 is: (2 + 3) / 2 = 5 / 2 = 2.5
The weighted average is the average of numbers where some numbers carry more weight (importance) than others.
For example, consider the following scenario:
- Let us suppose that the numbers 2 and 3 represent touchpoints on a conversion path.
- Let us suppose that touchpoint 2 is 70% important in influencing the purchase behaviour of a user and touchpoint 3 is 30% important in influencing the purchase behaviour.
So, the weighted average = ((2 X 70%) + (3 X 30%)) / 2 = (1.4 + 0.9) /2 = 1.15
What exactly is ‘weight’?
In the context of attribution modelling in GA, the weight refers to the adjustment made to the conversion credit.
A marketing channel receiving weight is actually receiving conversion credit.
If a marketing channel receives more weight, it receives more conversion credit in a particular position on a conversion path. The heavier the weight, the higher the conversion credit.
Conversely, a marketing channel receiving less weight means it is receiving less conversion credit in a particular position on a conversion path. The lower the weight, the lower the conversion credit.
The colour coding used in the Model Explorer report
The Model Explorer report uses a dark colour to represent a high weighted average conversion credit. The darker the colour, the higher the weighted average.
Conversely, the lighter the colour, the lower the weighted average:
Sometimes a marketing channel does not play any role in a particular position on a conversion path. Whenever this situation occurs the Model Explorer uses a white colour with a dash (-) to display the interaction on the conversion path:
How to determine the overall weight of marketing channels under data-driven attribution
In order to determine the overall weight of marketing channels under data-driven attribution and in a particular time period, follow the steps below:
Step-1: Navigate to the Model Explorer report.
Step-2: Select the time period for which you want to see the DDA model.
Step-3: At the top left-hand side of the report, you should see the ‘Conversions’ drop-down menu. Make sure that the ‘All’ option is selected:
Step-4: Look at the ‘Conversions’ column in the report:
The marketing channel with a higher volume of data-driven conversions carries more weight in the selected time period.
If you want to determine the weight of marketing channels for a particular conversion type then select the conversion type from the ‘Conversion’ drop-down menu at the top left-hand side of the report:
Downloading the MCF Data-Driven Attribution Model
Through the Model Explorer report, you can also download the latest DDA model into Excel as a CSV file for further analysis.
You can do this by clicking on the ‘Download the full model’ button at the top right-hand side of the model explorer report:
It is important to keep in mind that the data you see in the downloaded MCF DDA model is unlikely to match with the DDA Model data you see in the Model Explorer report. According to Google, this is expected.
The data that you see in the downloaded MCF DDA model only includes those conversions whose conversion path length is two or more interactions and which were recorded within 28 days from the time the DDA model was last generated.
Whereas, the DDA Model data that you see in the Model Explorer report shows conversions based on the conversion type and the time period you selected for the report.
Other articles on Attribution Modelling
- How to analyse and report the true value of your SEO Campaign
- How to valuate Display Advertising through Attribution Modelling
- Understanding Shopping Carts for Analytics and Conversion Optimization
- 6 Keys to Digital Success in Attribution Modelling
- Google Analytics Attribution Modeling Tutorial
- How to Measure and Improve the Quality of SEO Traffic through Google Analytics
- How to explain attribution modelling to your clients
- Default and Custom Attribution Models in Google Analytics
- Understanding Missing Touchpoints in Attribution Modelling
- What You Should Know about Historical Data in Web Analytics
- Model Comparison Report Explained in Google Analytics Attribution
- Data-Driven Attribution Model in Google Analytics – Tutorial
- Conversion Lag Report Explained in Google Analytics Attribution
- Selecting the Best Attribution Model for Inbound Marketing
- How to do ROI Analysis in Google Analytics
- Conversion Credit Models Guide – Google Analytics Attribution
- Introduction to Nonline Analytics – True Multi Channel Analytics
- Conversion Types Explained in Google Analytics Attribution
- Attribution Channels Explained in Google Analytics Attribution
- Differences Between Google Attribution & Multi-Channel Funnel Reports
- Introduction to TV Attribution in Google Analytics Attribution 360
- Conversion Credit Distribution for Attribution Models in Google Analytics
- Conversion Paths Report Explained in Google Analytics Attribution
- Attribution Model Comparison Tool in Google Analytics
- Touchpoint Analysis in Google Analytics Attribution Modelling
- Attributed Conversions & Attributed Revenue Explained in Google Attribution
- Which Attribution Model to use in Google Analytics?
- Google Attribution Access and User Permissions – Tutorial
- Conversion Path Length Report Explained in Google Analytics Attribution
- How to set up a data-driven attribution model in Google Analytics
- View-Through Conversion Tracking in Google Analytics
- Offline Conversion Tracking in Google Analytics – Tutorial
- How to Create Custom Attribution Model in Google Analytics
- 8 Google Analytics Conversions Segments You Must Use
- You are doing Google Analytics all wrong. Here is why
- How to Use ZMOT to Increase Conversions and Sales Exponentially
- Connected Properties Explained in Google Analytics Attribution
- Marketing Mix Modelling or Attribution Modelling. Which one is for you?
- How is attribution modelling helpful for ecommerce and non-ecommerce websites?
- Conversion Time & Interaction Time Explained in Google Analytics Attribution
- How to Allocate Budgets in Multi Channel Marketing
- How Does Attribution Work?
- Data-Driven Attribution Model Explorer in Google Analytics
- Introduction to Attribution Beta – Attribution Project in Google Analytics
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