There are tons of data in today’s multi-channel world that provide ideas on how consumers interacted with your company and their path to conversion. Performance with multichannel marketing is essential to understand, which can be accomplished by attribution modelling. Attribution means assigning value to something for the role it played in the final conversion (a channel, touch point, etc.). An attribution model is a rule or set of regulations that properly allocates this value to the correct channel or touchpoint.
The main distinction between the two is that the attribution of AdWords is restricted to the channels available on the platform, while Google Analytics can be used for a multitude of channels, allowing you to truly understand how all your marketing attempts affect the user journey.
This blog post will concentrate on the attribution of AdWords and will move on to the attribution of Google Analytics.
Google AdWords Attribution
Historically, AdWords supplied the last-click attribution or five rules-based models. These are discussed in more detail below.
This is the standard model most advertisers use. It provides the last-clicked ad all the credit for the conversion. The big issue with this model is that consumers are likely to connect with your brand across various touchpoints and channels in today’s multichannel globe.
For instance, a user can press on an original non-branded keyword, then a display remarketing ad, and then transform through a branded keyword. Clearly, credit is due to the first two touchpoints–it could be asserted in this situation that the most significant was the first non-branded keyword. To guarantee effective optimisation, regions of your account that have the greatest effect need to obtain the budget.
To guarantee effective optimization, your account areas that have the greatest effect need to receive the budgets they deserve. Using the attribution last-click can pull a curtain over these attempts, which could lead to stifling areas that actually play a vital part in the actual conversion. Other models are accessible to combat this; they are described below.
This gives the first touchpoint all the credit. Since it is becoming difficult and harder to attract the attention of customers, this model seems helpful as it credits the first interaction of the brand.
Similar to the last click, however, this channel only rewards one aspect of your account and may stop certain advertisements from obtaining due credit.
linear attribution gives equal credit to each touchpoint on the conversion path, so if there are 10 touches each, they will receive 10 percent of the credit. This model is the first step towards multichannel attribution and will enable you to optimize your customer journey instead of individual touchpoints.
While this model is an excellent first move, it has constraints–particularly that each channel gets the same credit, so it will be difficult to comprehend which touchpoints have the biggest effect on the customer journey.
As the name indicates, time decay will offer the most credit to one of the most recent conversion points. Again, it’s another big step towards multichannel allocation. Within Google AdWords, it operates by providing a seven-day half-life attribution credit, meaning a transformation that occurred eight days earlier would get half as much credit as it did one day ago.
This model is appropriate for multi-touchpoint companies with a short sales cycle. However, owing to time decay, longer cycles may not be suited as it would not give adequate credit to the first interaction, which may be the most important for some.
The position-based system allocates 40% of the credit to both the first and last touchpoints and spreads the remaining 20% uniformly among all others (disclosure: this model is my personal favourite). Using this model will enable you to guarantee that all touchpoints are rewarded, but will also highlight the first and last points, which I think may be the most important.
The first touchpoint is crucial for introducing customers to your brand and generating original interest, and the last touchpoint is crucial to guarantee that you are prepared to close the conversion (including for branded keywords, to stop rivals from taking customers when they are at the conversion stage).One downside to position-based attribution is that you can start optimizing towards the first and last touchpoints without factoring in anything in between that may not be appropriate for the goals of your business and the policies you have in place.
Data-driven attribution is the latest available model and is based on an algorithmic attribution strategy. This model uses machine learning to assess all of your users ‘ conversion and non-conversion routes, their interactions with advertisements, and a vast range of other variables such as ad creativity and keyword efficiency to know where credit should be allocated across your account.
The model’s primary focus is on understanding how individuals act and then becoming your business’s customers. Using this attribution model will enable you to take advantage of the strength of Google’s machine learning and take the guesswork from what rules-based model works best for your company.
Google Analytics Attribution
Google Analytics attribution operates in the same manner as AdWords, but on a bigger scale, and can encompass all of your channels. It is certainly suggested to always use Google Analytics to know how your channels work together and how your customers navigate through organic search, email, paid social… the list goes on.
The one important distinction between Google Analytics and AdWords is the model of the default attribution. Google Analytics utilizes the last non-direct click, which guarantees that the credit is allocated to the channel that a customer went through, as many consumers can bookmark a site and then buy it directly at a later stage.
It is vital to use AdWords attribution when maximizing channels within your account, but looking at the overall picture in Google Analytics can lead to some differences in the information. For example, if a user clicks a paid search ad and then converts to your campaigns in AdWords and organic search in Google Analytics a few days later, the credit will be assigned to your campaigns.
So which model should you use?
It is essential to know how many touchpoints are in play for your client and their company objectives with any attribution model and then use that to determine which model will function best. My suggestion would be to use attribution driven by data wherever possible. However, if your account is smaller than the requirement, a rule-based model that values all touchpoints to some extent would work best (meaning time decay, position-based or linear based on what you want to accomplish).
Contact our team today to learn more about attribution and how you can use data to drive your company forward.