One of the reports I enjoy most about Google Analytics is being able to analyze the type of attribution that should be given to a conversion (sale or download) as a result of a digital advertising campaign.
A few years ago, it was practically impossible to analyze this type of information. With Google Ads you could know the advertisement that had generated a sale, but knowing the time and space within the consumer journey or customer journey that had a click in relation to the conversion was impossible.
As expected, Google Analytics has already established a couple of models to be able to correctly attribute the result of marketing efforts and understand the impact of each of your actions, by channel and click.
This represents a great opportunity to intelligently optimize the budget of advertising campaigns. It also benefits decision-making and positively impacts marketing teams to predict and establish real parameters within the desired growth expectations.
Suppose that a user entered your site when they clicked on a Google Ads ad and returned the following week through a post on social networks to visit some pages without achieving a conversion, the user returns on a third visit as a result of an email campaign and finally converts a few hours later when entering the site directly. To which channel should the sale be attributed in relation to the following models?
Google Analytics attribution models are used to help determine how conversion credit should be distributed across the different marketing channels that contributed to the conversion. There are several main attribution models in Google Analytics.
Below I will explain each of them to you. These attribution models can be analyzed from many perspectives and of course there is no general rule.
In marketing, the last interaction attribution model is a method for assigning credit for a conversion to the most recent touchpoint in the customer journey. In other words, it's the belief that the last advertisement or campaign a customer sees before converting is responsible for their conversion. This attribution model is often used by marketers because it's easy to understand and measure. However, the use of this model has some drawbacks. On the one hand, it doesn't take into account all the interactions a customer has had with your brand. In addition, it can be difficult to accurately attribute credit when there are multiple touchpoints involved. Ultimately, you'll have to weigh the pros and cons of using the last interaction attribution model to decide if it's right for your business.
The first-interaction attribution model is a type of marketing attribution model that assigns credit for a conversion to the first point of contact a customer has with a brand. In other words, it attributes credit for a sale to the first time a customer is exposed to a brand, regardless of whether they ultimately make a purchase. This type of attribution can be beneficial for marketers looking to increase brand awareness and create initial relationships with customers. However, it can also be limiting, since it doesn't take into account the role that other touch points may have played in the customer's decision process. Therefore, the first-interaction attribution model must be used in conjunction with other types of marketing attribution models to obtain a complete picture of how customers interact with a brand.
The last-click attribution model is one of the most commonly used methods for determining which marketing efforts are most effective. Under this model, credit is given to the last point of contact a customer has with a brand before making a purchase. This could be the ad you clicked on, the email you opened, or even the search term you used. While last-click attribution can be useful in identifying which channels are driving conversions, it has some limitations. For example, it doesn't take into account the role that other touchpoints may have played in the customer journey. It also doesn't take into account potential credit card fraud or return visits. However, last-click attribution is still a widely used method for evaluating marketing effectiveness.
The Linear Attribution Model is a great tool for understanding how your marketing efforts are working. In a nutshell, it allows you to attribute each sale (or other desired result) to a specific marketing channel. This way, you can see which channels are generating the most results and adjust your budget accordingly.
To use the Linear Attribution Model, simply keep track of the source of each sale (or other desired outcome). In other words, this model attributes a portion of the sale to each marketing channel that has intervened in the customer journey. For example, if a customer saw a Facebook ad, clicked on an email link, and then made a purchase on your website, you would attribute a portion of the sale to each channel.
The linear attribution model is a great way to understand which marketing channels are working best for your business. By attributing sales to specific channels, you can identify which channels are generating the most results and adjust your budget accordingly. If you don't already use the Linear Attribution Model, we strongly recommend that you try it out. Without a doubt, this model gives credit to each of your marketing efforts and is one of my favorites.
The time-wasting attribution model is one of the most popular options, and is especially suitable for websites where the sales cycle is relatively long. In this model, credit for a conversion is assigned to the touchpoints that occur at the end of the conversion itself — from lowest to highest. So, if a user converts to your website after seeing an ad, then clicks on an email link and visits your site three times, and then is followed by an ad on Facebook, most of the credit would be attributed to Facebook followed by email campaigns. This model has the advantage of being relatively simple to understand and apply, but it has some shortcomings, namely that it does not take into account the fact that the first points of contact may have influenced the user's conversion decision.
There are many different models that attribution systems use to track the user's journey and ultimately attribute a conversion to the right marketing channel. The position-based model is an option that examines the first and last points of contact before the conversion occurs. This model assigns 40% of the credit to the first point of contact and 40% to the last, so the remaining 20% is divided by all the intermediate interactions.
The data-based attribution model is a statistical approach that uses data patterns to attribute credit for conversion events to touchpoints in the customer journey. This attribution model can be used for digital marketing channels, such as search, viewing, email, social media and other online platforms. The data-driven attribution model is based on the belief that all touchpoints in the customer journey contribute to conversion. This attribution model attributes credit to each touchpoint based on its weight in the data pattern. The data-based attribution model has many advantages, including that it takes into account the entire customer journey, not just the last click. In addition, this attribution model can be used for any type of conversion event, not just sales. However, one limitation of the data-based attribution model is that it requires a large amount of data to be effective. Another limitation is that it can be difficult to attribute credit to specific touchpoints when there are many different factors contributing to the conversion. Overall, the data-based attribution model is a powerful tool that can be used to attribute credit for conversion events, however, it's important to consider its limitations when using this tool.
Now, it's time to choose the right one for your strategy. Which one is the best? It depends on the circumstances, but I'm going to give you the same advice I give to my clients. There comes a time when you review the data, something internal (your intuition) tells you which one most closely matches the reality of your marketing efforts.
All attribution models are part of the Google Analytics platform and are very easy to implement.
Luck.
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