Understanding attribution models in Google Analytics is key to understanding your website performance. Multiple attribution models can be used within Google Analytics.
In this article, we’ll dive a bit deeper into the different attribution models and how these can be used in Google Analytics.
- What is an attribution model in Google Analytics?
- What is the default attribution model used in Google Analytics?
- What other attribution models are there?
- What are the advantages and disadvantages of different attribution models?
- Final Thoughts
Let’s dive in!
What is an attribution model in Google Analytics?
An attribution model is a set of rules that help you understand how people find your website and what makes them decide to buy something from you.
For example, let's say someone clicks on an ad for your website on Facebook, then visit your website, and finally buy something from you. In this case, the attribution model would determine how much credit to give to each of those three steps in the customer journey: the Facebook ad click, the website visit, and the purchase.
The goal of using an attribution model is to figure out which parts of your marketing strategy are most effective at getting people to buy something from you so that you can spend more money on the things that work and less on the things that do not.
What is the default attribution model used in Google Analytics?
The default attribution model in Google Analytics is the last-click model. This means that, by default, when someone clicks on an ad for your website on Facebook, visits your website, and then makes a purchase, all of the credit for the purchase will be given to the website visit. This means that the Facebook ad click will not be credited with any merit for sale.
Google Analytics offers other built-in attribution models that you can use instead of the default model.
What other attribution models are there?
There are several built-in attribution models available in Google Analytics. Here is a more detailed look at each of these models:
- There is the last-click model, which we already discussed.
- First-click model: this model gives all credit for a sale or conversion to the first touchpoint in the customer journey. For example, if someone clicks a Facebook ad for your website, visits the website, and makes a purchase, the first-click model will give all of the credit for the purchase to the Facebook ad click.
- Linear model: This model evenly distributes credit for a sale or conversion across all touchpoints in the customer journey. For example, if someone clicks on an ad for your website on Facebook, visits your website, and then makes a purchase, the linear model would give one-third of the credit for the purchase to the Facebook ad click, one-third to the website visit, and one-third to the purchase itself.
- Time decay model: This model gives more credit to touchpoints closer to the sale or conversion. For example, if someone clicks on an ad for your website on Facebook, visits your website a week later, and then makes a purchase a week after that, the time decay model will give more credit to the website visit and the purchase than to the Facebook ad click because those touchpoints were closer in time to the sale.
- Position-based model: This model gives more credit to the first and last touchpoints in the customer journey and evenly distributes the remaining credit among the other touchpoints. Let's say someone clicks on an ad for your website on Facebook on Friday, visits your website, and buys nothing. If they later click a different ad, land on your website, and makes a purchase, the first ad and the website visit would get 40% of the credit for the purchase, while the second ad would only get 20%.
These are just some examples of the built-in attribution models in Google Analytics. You can also create custom attribution models tailored to your specific business needs.
What are the advantages and disadvantages of different attribution models?
Each of the different attribution models has its own advantages and disadvantages. Here are some of the pros and cons of the most common attribution models:
- Last-click model:
- Advantages: this model is simple and easy to understand and can help identify which marketing channels drive the most conversions.
- Disadvantages: it does not consider the other touchpoints in the customer journey. So, it may not provide a complete picture of how different marketing channels contribute to conversions.
- First-click model:
- Advantages: This model gives credit to the first touchpoint in the customer journey, which can help identify which marketing channels are driving initial interest in your product or service.
- Disadvantages: much like the last-click model,e the first-click model only takes a single touchpoint into account and may not provide a complete picture.
- Linear model:
- Advantages: This model evenly distributes credit across all touchpoints in the customer journey, providing a more balanced view of how different marketing channels contribute to conversions.
- Disadvantages: The linear model may not accurately reflect the relative importance of different touchpoints in the customer journey.
- Time decay model:
- Advantages: This model gives more credit to touchpoints closer to the sale or conversion, which can help identify which marketing channels are driving immediate sales or conversions.
- Disadvantages: the time decay model may underrate the importance of the touchpoints that drive the initial interest from the customer.
- Position-based model:
- Advantages: This model gives more credit to the first and last touchpoints in the customer journey, which can provide a more balanced view of how different marketing channels are contributing to conversions.
- Disadvantages: The position-based model sometimes underestimates the importance of intermediate touchpoints in the customer journey.
Final Thoughts
There are multiple attribution models to pick from. You should choose the attribution model that best fits your business needs and goals. There is no one-size-fits-all solution, and different models may be more or less effective depending on your specific situation.
It's also worth noting that you can create custom attribution models in Google Analytics tailored to your particular situation. Take note that adding custom attribution models is quite complex. Google Analytics is by default a complex analytics tool that requires experience or training.
If you are looking for a simple analytics tool that gives you the website insights you need in a straightforward dashboard, Google Analytics is not the right tool for you. This is also the reason we built Simple Analytics (what’s in the name, right?]. Feel free to check us out