In the ever-evolving world of online advertising, understanding which digital channel is your most profitable one is crucial. Attribution Models help you do just that: they assign credit to different touchpoints in the customer journey to help you understand which channels and campaigns are most valuable to driving results.
In this blog post, we want to demystify Attribution Models and explain them in an easy and comprehensible way.
What Are Attribution Models?
The path to conversion is rarely linear and often includes multiple steps before a user takes a valuable action on your website, such as purchase, signup or phone call. On this journey, users might find your website through different channels and mediums, for example, Google paid search, organic search, retargeting campaigns or social media posts.
In Google Analytics, a journey to conversion can look like this:
You can find this data in your Google Analytics 4 account by going to Advertising > Attribution > Conversion Paths.
Each step in this path is crucial to lead the user to the final conversion. If one of these steps didn’t occur, chances are high that the user would have been lost on the journey and not be turned into a customer.
However, some steps are more important than others and this is where attribution models come into play. Depending on the model you choose, more credit for the conversion might be given to one step than the others.
Which Attribution Models Are Available?
Let’s break them down:
1) Last-click attribution
Last-click attribution is one of the two single-touch models and attributes the full credit to the last ad or marketing touchpoint the user interacted with before making the conversion. While it is simple and straightforward, it ignores the preceding touchpoints and doesn’t provide a comprehensive view on the journey to conversion.
2) First-click attribution
First-click is the opposite to last-click attribution: here, all credit is given to the very first ad or marketing touchpoint the user has with your business, regardless of how many steps follow before the conversion happens. Again, it’s easy to grasp but doesn’t capture the big picture.
3) Linear attribution
Linear attribution is the first multi-touch model in our list. It gives equal credit to every step on the journey to conversion and is therefore a great step forward in understanding the bigger picture. The drawback is that it assumes every step in the conversion path is of equal importance which is rarely the case.
4) Time Decay attribution
Time Decay gives more credit to touchpoints closer to the conversion. Assuming that the later interactions are more important than the earlier ones, this model acknowledges the ads and marketing touchpoints in the immediate lead-up to a conversion.
5) Position-based attribution
Position-based attribution can be imagined as a U-shaped model since it attributes 40% to both the first and last interaction while the remaining 20% is distributed to the steps in between. Rather than focusing on the last steps before the conversion, it highlights the importance of both the first and last interaction.
6) Data-Driven attribution
Data-driven is the most recent and most complex model as it uses machine learning algorithms to analyse conversion paths based on your specific data. It is a dynamic model that uses advanced statistical techniques to work out how important each individual step in the conversion path was and assigns a credit accordingly.
Conclusion
Each model has their advantages and disadvantages and it is crucial to have your marketing goals and complexity of the customer journey in mind when picking an attribution model.
In general, first- and last-click are rather simple models and often don’t reflect the complexity of today’s customer journeys meaning you might misinterpret the importance of certain channels.
Linear, time-decay and position-based are multi-touch attribution models and a great step forward compared to first- and last-click. Our recommendation is to select Data-Driven attribution if it is available in your account and your campaigns generate enough data. It currently is the most sophisticated model available and can help you generate valuable insights to drive better campaign results.
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