Example with brand name ad rotation
Posted: Tue Dec 17, 2024 7:00 am
Using 'Lifetime Value' as a KPI
The ' lifetime value ' report in Google Analytics provides insight into the performance of returning visitors in the long term, up to 90 days. You can select different metrics. The data is then displayed at user level. This report provides an overview of the value of your visitors. You can also collect this data yourself via other reports, but Google has collected it for you in an overview here. Handy! Unfortunately, the data is not calculated cross-device for you.
Lifetime Value.
How can you use this to assess your branding? For example, for e-commerce websites, you can use the 'metric revenue per user' to make decisions based on lifetime value. This metric shows how many users on average generate revenue over the long term who have arrived at your website via a certain campaign or channel. This is therefore an ideal KPI that you can use to assess your branding.
See in the example below the big differences between campaigns. You see here for example that the campaign 'Brandname – Ad-rotation' has a high revenue per user (LTV).
Simulate a different attribution model with the Model Comparison Tool
Google Analytics (still) uses a model where conversions and transactions are attributed based on 'last non-direct click'. That is, the channel that delivers the last click in the customer journey (except direct traffic) gets the conversion. Not really a useful piece of data to qualify your branding traffic. Since branding mainly ensures a broad vietnam telegram data influx of users, who are often still in the orientation phase of a purchase process and therefore not exclusively in the decision phase.
Also read: Forget bounce rate, measure visit quality
You can simulate a different attribution model using Google Analytics' Model Comparison Tool . This way, you can temporarily move away from the 'last non-direct click' model and see how channels are assessed with different attribution rules.
Of course, it depends on your own marketing strategy and vision of what you mean by branded traffic. A logical hypothesis could be: “To be able to properly assess my branded traffic, I give each step in the customer journey the same value”. In this way, you are not only looking at the last channel that scores the conversion, but also at the channels that are higher or halfway in the funnel.
In the report below I compare the linear model with the last non-direct click model. This means: do not give all the credits to the channel at the end of the customer journey, but distribute the credits over all touch points. In the linear model, the display channel performs 36% better. Display therefore has more of a branding character than a performance character. Despite the low number of conversions, this indicates that the channel has more value than if you only look at the conversions. It therefore deserves more attention, and preferably also budget.
The ' lifetime value ' report in Google Analytics provides insight into the performance of returning visitors in the long term, up to 90 days. You can select different metrics. The data is then displayed at user level. This report provides an overview of the value of your visitors. You can also collect this data yourself via other reports, but Google has collected it for you in an overview here. Handy! Unfortunately, the data is not calculated cross-device for you.
Lifetime Value.
How can you use this to assess your branding? For example, for e-commerce websites, you can use the 'metric revenue per user' to make decisions based on lifetime value. This metric shows how many users on average generate revenue over the long term who have arrived at your website via a certain campaign or channel. This is therefore an ideal KPI that you can use to assess your branding.
See in the example below the big differences between campaigns. You see here for example that the campaign 'Brandname – Ad-rotation' has a high revenue per user (LTV).
Simulate a different attribution model with the Model Comparison Tool
Google Analytics (still) uses a model where conversions and transactions are attributed based on 'last non-direct click'. That is, the channel that delivers the last click in the customer journey (except direct traffic) gets the conversion. Not really a useful piece of data to qualify your branding traffic. Since branding mainly ensures a broad vietnam telegram data influx of users, who are often still in the orientation phase of a purchase process and therefore not exclusively in the decision phase.
Also read: Forget bounce rate, measure visit quality
You can simulate a different attribution model using Google Analytics' Model Comparison Tool . This way, you can temporarily move away from the 'last non-direct click' model and see how channels are assessed with different attribution rules.
Of course, it depends on your own marketing strategy and vision of what you mean by branded traffic. A logical hypothesis could be: “To be able to properly assess my branded traffic, I give each step in the customer journey the same value”. In this way, you are not only looking at the last channel that scores the conversion, but also at the channels that are higher or halfway in the funnel.
In the report below I compare the linear model with the last non-direct click model. This means: do not give all the credits to the channel at the end of the customer journey, but distribute the credits over all touch points. In the linear model, the display channel performs 36% better. Display therefore has more of a branding character than a performance character. Despite the low number of conversions, this indicates that the channel has more value than if you only look at the conversions. It therefore deserves more attention, and preferably also budget.