MARKETING ATTRIBUTION MODELS AND HOW THEY WORK

Updated: Apr 28


How’d you love for a visitor to find your blog or click on one of your ads and immediately convert into a qualified lead, or even a sale? Of course, you would, but how often, in reality, does that happen? We can count them on the fingers of one hand.

Most of the time people will visit your site multiple times before converting. They'll pass by, read your blog post, come right back a week later, click on a retargeting ad the next day and then, eventually, they might convert.

Here's where the classic question arises: which marketing channel should you attribute the conversion of this lead to? Was it your blog that was responsible for the new sale? Or maybe it was the Facebook ad? These days, there are multiple touch points in the buyer's journey and each channel plays a crucial part.

For that reason, we have to rely on an attribution model that tells us which channel works best for the buyers on your site. Let’s start with a simple question:

What are marketing attribution models?

Attribution models provide a framework for analysing which touchpoints, or marketing channels, lead to a conversion. Each attribution model distributes the value of a conversion at each touchpoint differently.

A model comparison tool allows you to analyse how each model distributes the value of a conversion. There are four common attribution models: last interaction, first interaction, last undirected click, and linear.

Attribution models are extremely useful, but they also represent one of the most complicated topics in marketing. By analysing each attribution model, you can get a better idea of the ROI for each marketing channel, and you can compare performance in each model to understand the importance of multiple touch points in the customer journey.

Determining which marketing channel to attribute a conversion to depends on the type of online activity your company does. It's not about using one attribution model all the time, but trying to combine the best ones together to analyse what led the user to take a particular action.

By comparing multiple attribution models, it will be easier to understand how two (or more) marketing channels work together to generate conversions, so that you can assign a conversion value to each channel.

Understanding customers’ steps before conversion can be just as valuable to marketers as the sale itself. In this article, we'll outline the primary attribution models and when to use them.


What are the different types of attribution models?


1. Last Interaction Attribution


Last interaction attribution is also referred to as "last click" or "last touch." As the name suggests, this model attributes 100% of the credit to the last interaction your company had with a lead before conversion. This represents the default attribution model in most platforms, including Google Analytics. If you look at the standard conversion reports in Google Analytics, you'll see each goal attributed to the last interaction your customer had with your business.

The main disadvantage is that this model ignores everything that happens before the final interaction. In fact, many of the interconnections and touchpoints prior to that last click should be just as valuable.

This model might be better suited to a company that has a shorter purchase cycle. If there aren't many touchpoints before the conversion, just tracking the last one will give you a good idea of your strongest channels.

2. First Interaction Attribution


First Interaction is similar to Last Interaction as it assigns 100% of the credit to a click/interaction. This model, (also called "First Click") assigns all credit for a conversion to your company’s first interaction with the customer. For example, if a customer first finds your business on Pinterest, the latter gets full credit for any sales that occurred after that interaction. It doesn't matter if the customer found you on Pinterest, then clicked on a display ad a week later, and then went directly to your site. Pinterest, in this case, gets full credit.

The main attraction of using First Interaction Attribution is how simple and straightforward it is. However, this model ignores the effects of any potentially important marketing channels that kick in later on. Here again, the model results to be useful if your industry has a short buying cycle. 3. The Undirected Last Click


The ‘undirected last click’ model is slightly more useful than a standard last click model. 100% of the value is still assigned to a single interaction. However, with undirected last click, all "direct" interactions that occur right before conversion are not taken into account.

Direct traffic occurs when someone accesses your site directly by manually entering your URL or clicking on a link added to bookmarks. So, the visitor already knows about your company. But how did they hear about it? What made them visit your website directly? By eliminating direct traffic as this model suggests, you can assign more value to the marketing strategy that led to the conversion. This model is more intuitive than the ‘last interaction’ one, however, it still assigns 100% of the value to an interaction. Hence, if your customer had four touch points before that last non-direct click, they will be completely ignored. 4. Linear Attribution


With a linear attribution model, companies divide the conversion equally among all the interactions which the customer has had with their business. This model offers a more balanced look at the entire marketing strategy than a single-event attribution one. However, this means that the model assigns equal importance to everything, underestimating those marketing strategies which are more effective than others.

If you are looking for an attribution model that is simple and easy to explain to customers, linear attribution might be a good option for you. It's a great way to demonstrate how each channel has its own value.

Today, marketers invest in multiple channels and digital media platforms, so getting a unified view of a customer's journey is becoming increasingly difficult. And, given the increasing fragmentation of platforms and media types that marketers have at their disposal, attribution has never been more important.

However, these attribution models still represent a static view of what happens in a potential buyer's interactions. They don't provide the weight of how all the various platforms impact on the final data. H

Hopefully, in the future, we will see the development of variance analysis solutions within platforms that will allow marketers to better understand the existing impact of their strategies. And perhaps, companies will have a more comprehensive view of how to give proper weight to the various marketing channels that resulted in a conversion.

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