This post will explain the Data Driven Attribution (DDA) GA4 property. DDA calculates the channel’s contribution to results and displays a weighted evaluation in the report. DDA can also be used for ads through tool linkage with GA4. This makes it easy to optimize operations based on the contributions when marketing measures are implemented in multiple media.
Needs of Attribution Evaluation
From the first contact with a website, internet users may come into contact with the website through multiple marketing channels and take actions such as purchasing products or requesting brochures. If such users took action through their first ad or their first visit to the website, evaluations can be done on that single channel. However, if the conversion was done on the website through multiple channels, it is necessary to consider how to allocate the evaluation to each channel.
If you can evaluate the channels that contributed to conversion correctly while users are using multiple channels, you can deepen your marketing measures to improve the results. The Attribution Model is a rule that allocate contributions to the channels used by users when they visit a website.
(Figure 1: Evaluation of channels that contributed to conversions)
What is Data Driven Attribution (DDA)?
Data Driven Attribution (DDA) is a model that uses machine learning to calculate the contribution of channels of contact based on user event data. The model is regularly updated with the latest data for flexible evaluation, following the user consideration behavior changes due to marketing measures.
Calculation of Data Driven Attribution
There are two stages in the DDA evaluation calculation.
- Analyze path data and build conversion rate models for a conversion event.
- Input the predictions of the conversion rate model to the algorithm and assign conversion contributions to ads and channels contacted.
(Figure 2: Calculation method of Data Driven Attribution (DDA))
1. Structure a conversion rate model based on the oath data
DDA uses user path data (data on both users who converted and those who did not) to analyze the effect of contact of marketing channels and their timing to conversions. Once the model is structured, it calculates the likelihood of conversions at each touch point of a specific ad or channel.
2. Algorithmically allocate conversion contributions to marketing touchpoints
DDA analyzes how the addition of a specific channel as a point of contact changes the likelihood of conversion and allocates conversion contribution. The algorithm calculates contributions using data such as time from first visit to the website, ad formats, and other queries.
(Figure 3: Data Driven Attribution (DDA) contribution allocation)
Difference of GA4 Data Driven Attribution (DDA) and UA
The new Google Analytics property, GA4, have significantly changed the behavior of DDA from UA properties.
With UA, you had to pay for GA360 to use DDA, and there were data volume requirements. In contrast, in GA4, these requirements were eliminated, and conversions are calculated by DDA by default. This makes it easier to evaluate conversion contribution measures in GA4 compared to UA.
(Figure 4: Comparison of GA4 and UA Data Driven Attribution)
Effectively using DDA
GA4 calculates conversions by DDA by default. This means that the conversions of Google Ads will be calculated with DDA just by linking Google Analytics and Google Ads with the default settings. This will allow you to evaluate YouTube and display ads, which are less likely to lead directly to conversions, and to optimize distributions by combining multiple media.
With DDA, ratings are assigned to measures that contributed to conversions based on data. GA4 uses DDA as the default attribution model not requiring additional configurations. If you wish to continue using the last touch model used in the UA property, you need to change the settings. Feel free to contact us if you have any issues or concerns regarding the implementation of GA4, its configuration, and usage.
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