Attribution modelling is the process of finding and fixing attribution issues, understanding the buying behaviour of your website users and determining the most effective marketing channels for investment at a particular point in time.
Following is the more technical definition of attribution modelling:
Attribution modelling is the process of understanding and assigning conversion credit to marketing touchpoints on a conversion path with the aim of achieving the following objectives:
Understand the customers’ purchase journey.
Determine the most effective investment marketing channels at a particular time.
In order to understand the definition of attribution modelling, you would first need to understand the following terms really well:
Conversion
Conversion credit
Conversion credit distribution
Digital vs. non-digital marketing channels
Touchpoints
Conversion paths
Attribution issues
Note: Attribution Modelling is full of jargon. If you do not understand the jargon, you will have a hard time understanding attribution reports and implementing attribution modelling.
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What is a Conversion in GA4?
Conversion is one of the goals or purposes for setting up a website or mobile app. A conversion is what you are trying to achieve through your website/app.
There can be one or many purposes for which you have set up your website or app.
These purposes can be something like:
Selling products
Generating leads
Branding
Selling advertising
Collecting donations
Fighting for a cause, etc.
If one of your website goals is to generate orders on your website, then ‘the number of ecommerce transactions’ (aka purchases) could be defined as a conversion.
Similarly,
If one of your website goals is to get sign-ups for your newsletter, then the ‘number of newsletter signups’ could be defined as a conversion.
The major purpose of setting up a website is known as a macro conversion and other minor purposes are known as micro conversions.
For example,
If your main purpose of setting up a website is to generate sales, then the ‘number of ecommerce transactions’ can be your macro conversion.
The other minor purposes like ‘newsletters signup’, ‘downloading a brochure’, ‘providing customer support’, ‘requesting a follow-up’ etc., can be your micro conversions.
The technical definition of conversion in the context of GA4
In the context of GA4, a conversion is defined as a conversion event.
Since GA4 collects all of the users’ activities in the form of events, the events which are most important to your business must be marked as conversions:
In GA4,
You can mark an existing event as a conversion.
You can stop marking an event as a conversion.
You can add a monetary value to a conversion event.
You can create a new conversion event based on an existing event.
Google Analytics 4 automatically designate the following events as conversions:
purchase (web and app)
first_open (app only)
in_app_purchase (app only)
app_store_subscription_convert (app only)
app_store_subscription_renew (app only)
In addition to these events, you can mark up to 30 additional events as conversions per GA4 property.
The two categories of Conversions
In the context of attribution modelling, there are two categories of conversions:
Ecommerce conversions
Goal conversions.
An ecommerce conversion is a conversion that is directly tied to a transaction.
For example, a ‘purchase’ is an example of ecommerce conversion because it is directly tied to a transaction.
A goal conversion is a conversion that is not directly tied to a transaction.
For example, ‘newsletter signup’ is an example of goal conversion as it is not directly tied to a transaction.
Why is the focus on digital marketing channels in attribution modelling?
In the case of attribution modelling, the marketing channels that we focus on are primarily digital but can also include non-digital marketing channels as long as these channels are used to measure and optimize a business’s online performance.
Here there is a strong focus on optimizing a business’s ‘online performance’.
The non-digital marketing channels can also be used to optimize a business’s ‘offline performance‘. But that is marketing mix modelling and not attribution modelling.
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What is a conversion path in attribution modelling?
A conversion path is a path a user took to complete a conversion on your website/app.
In the context of Google Analytics,
In the context of Google Analytics, a conversion path is a sequence of touchpoints (clicks, visits, impressions) with digital marketing channels during the 1 to 90 days period that leads to conversions.
The period of 1 to 90 days prior to conversions is known as the lookback window.
Consider the following hypothetical conversion path of a user:
Here the user is exposed to 6 marketing channels before purchasing.
Google Analytics will report this conversion path as:
Important points to remember about conversion paths
A conversion path is made up of one or more touchpoints.
The conversion path is created for each conversion recorded by Google Analytics.
An attribution issue occurs when you can not determine the primary source of conversion, or you do not know the conversion paths.
For example, you don’t really know where your sales came from.
You don’t really know which marketing channel or set of channels has the biggest impact on sales.
As a business, you have attribution issues when you can not put your finger on any one marketing activity and can not say with any degree of confidence that this is the marketing activity that has the most impact on your sales.
The following types of businesses are most likely to suffer from attribution issues:
Quick recap of the definition of GA4 Attribution Modelling
Attribution modelling is the process of understanding and assigning conversion credit to marketing touchpoints on a conversion path with the aim of achieving the following objectives:
Understand the customers’ purchase journey.
Determine the most effective marketing channels for investment at a particular point.
Find and fix attribution issues.
I hope now the definition of attribution modelling makes sense to you now.
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Understand the customer purchase journey across devices
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What are GA4 Attribution Models?
The attribution models in GA4 are rules or sets of rules or data-driven algorithms that are used to determine how conversion credit should be distributed to various marketing touchpoints on a conversion path.
The conversion path can include both website and mobile app touchpoints.
Categories of GA4 Attribution Models
There are four categories of GA4 attribution models:
Cross-channel rules-based models – This category includes Cross-channel last click, Cross-channel first click, Cross-channel linear, Cross-channel position-based and Time decay attribution models.
Ads-preferred rules-based model.
Data-driven attribution model
Reporting attribution model – This model is used to calculate conversion credit in all of your GA4 reports.
To learn more about GA4 attribution models, check out the following two articles:
A lookback window is the time period (measured in a number of days) that determines how far back in time a touchpoint (exposure to a marketing channel) is eligible for getting conversion credit.
For example, a 30 days lookback window means a touchpoint is eligible for getting conversion credit for up to 30 days from the day it first occurred.
Similarly,
90 days lookback window means a touchpoint is eligible for a conversion credit for up to 90 days from the day it occurred.
By default, GA4 uses the 30 days lookback window for Acquisition conversion events (‘first_open’, ‘first_visit’) and 90 days lookback window for other conversion events.
How to change the Lookback window in GA4?
GA4 uses the lookback window at the property level. At present, it is not possible to set different lookback windows for individual reports within the GA4 property.
If you want to change the lookback windows for Acquisition conversion events and/or other conversion events, then follow the steps below:
Step-1: Navigate to your GA4 property.
Step-2: Click on the ‘Admin’ link from the left-hand side navigation:
Step-3: Click on ‘Attribution Settings’ under the property column:
Step-4: Scroll down until you see the section named ‘Lookback window’.
Step-5: Change the lookback windows for Acquisition conversion events and/or other conversion events and then click on the ‘Save’ button:
Note(1): Changing the lookback window will only apply going forward, and these changes will be reflected in all reports within the GA4 property.
Note(2): The lookback window applies to all GA4 attribution models and all conversion types.
The Advertising Snapshot report is an advertising workspace in your GA4 property that gives an overview of your conversion performance and your customers’ purchase journeys.
It is made up of cards and reports through which you can get answers to questions like:
The GA4 Model Comparison report is used to compare different GA4 attribution models to each other. This comparison is carried out to identify new optimization opportunities.
If you are a large enterprise, you should invest in more robust attribution modelling solutions.
If your budget allows, then create and use in-house custom attribution modelling solutions.
With custom solutions, you get maximum flexibility in terms of creating attribution models and applying custom credit rules.
You can achieve very robust data integration capabilities. Above all, you get complete ownership of your data and solutions.
#2 You do not need perfect data in order to implement attribution modelling
If you seek perfection, then most of the time, you will procrastinate. This is because things are perfect only once in a while.
Do not spend the majority of your time trying to collect perfect data to make that perfect business decision.
Otherwise, there is a high probability that you will not take any decision or action at the end of the day.
Taking timely action is extremely important in today’s world of cut-throat competition. Imperfect action is always better than inaction. Moreover, no analytics tool is perfect.
You cannot expect 100% accurate data from any analytics tool out there, and Google Analytics is no exception.
So avoid being obsessed with collecting perfect data and be happy with good enough data.
#3 Attribution Modelling is not the be-all and end-all of solving all the problems around ROI
This is because attribution modelling is not optimization. Optimization is what SEO, PPC and Conversion professionals do.
Even with ideal budget allocation, you will not get optimum ROI across marketing channels if:
Your campaigns are being optimised poorly.
Your website is suffering from usability and credibility issues.
Your competitor is dominating your market.
False or unrealistic expectations from attribution modelling can disappoint decision-makers. It could make them not want to trust, use, and value the attribution data.
All of these are bad signs for getting budget allocation for attribution modelling efforts.
That’s why setting up realistic expectations from the very start is very important.
#4 Attribution modelling is not a one-time activity
The marketing channel or activity that helped you to generate a conversion today may not help you to generate the same conversion tomorrow.
That’s why it is important to continuously explore the role of different marketing channels and campaigns in assisting conversions.
The performance of marketing channels and campaigns improves or deteriorates over time.
So you need to continuously find and separate good and bad marketing channels, ads and campaigns.
You then need to either improve the performance of the bad campaigns or replace them with brand new campaigns.
That is why attribution modelling is not a one-time activity. You cannot do it once and then forget about it.
#5 Focusing on a single marketing channel is not attribution
In a multi-channel marketing world, no single channel is solely responsible for conversions.
Different marketing channels work together to create sales and other conversions.
That is why we do not focus on measuring and optimising just one marketing channel in attribution modelling.
We do not create attribution strategies around a single channel.
Other articles related to GA4 (Google Analytics 4)
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