Marketing attribution: an overlooked approach- CXL Course Review

Continuing our series of the CXL Course reviews, today we will dive deep into the Marketing Attribution course. It is the last one from the "Data Analytics" section in the Growth Marketing Minidegree.

Attribution - An overlooked powerful tool

As a marketer, I've been obsessed with what the customers think and want. In a world full of touchpoints and channels, it is often hard to exactly understand what drove a conversion.

In this course, Russell McAthy explores how to solve this problem by truly understanding users behavior using attribution.

In a few words, marketing attribution is how we analyze and identify which marketing tactics are contributing to sales and conversions.

The professor begins the course showing that attribution is known by its different mathematical models but, indeed, it is much broader than it. To really benefit from marketing attribution, the companies must understand the philosophy beyond the mathematics and incorporate its insights into their strategy.

He demonstrates that it is possible to leverage attribution to understand the role of each channel in the customer journey, expanding the sight from how a user converted to what, in his entire journey, contributed to that conversion.

The professor goes on to say that we're facing a huge transformation in marketing attribution, where marketers can track a user not only across digital media but also across the physical ones.

Attribution models

Russel introduces the different mathematical models that can be used to attribute values to each of the touchpoints that lead a customer to the conversion. 

The first model presented is the last non-direct click, in which the conversion cost is attributed to the last non-direct source. It is a basic one, that considers that the user had previous contact with the brand or product and then directly accessed the site to finish the purchase or sign up.

The next model is the last interaction attribution, which considers the last touchpoint as the responsible for the conversion. This one, as explained, is good for short-time conversions and to track PPC conversions, for instance. However, it is not good to take into account the display and SEO influences on the user's behavior.

Those first two models aren't good to understand the entire journey. So, Russel proceeds to present other options that aim to tackle this problem.

The Linear attribution, for instance, consider that all the previous touchpoints contribute evenly to the conversion. The Time Decay Attribution, on the other hand, considers that the closer the touchpoint is to the final interaction, the higher the value it must have. So, the conversion value is distributed among the touchpoints, scaling up as it gets closer to the last one.

Then, the professor introduces the Position-based attribution, also known as the bathtub model, in which the highest values are attributed to the first touchpoint - where the user got to know the brand - and the last one, which triggered the conversion.

Finally, he wraps up the models by claiming that the best attribution model today is AI and data-based, considering a range of factors to come up with an accurate portrait of the user's behavior.

Attribution Tactics

The next classes are dedicated to explaining how the attribution approach can be used for a range of marketing tactics.

For CRO and PPC, you can use attribution to understand whether the landing/offer page had indeed the most of the influence on the customer. It is possible, for instance, to identify whether different offers interact among themselves and what offers to invest in.

For Display and SEO, attribution should consider the role both of them play to convert the user. As it relates to display, you must consider that the click rates will be indeed very low, but the impression could be impacting your user, prompting here to convert in the future.

When it comes to SEO, you can have your user engaging with content on your website that will be indoctrinating them to convert in the future as well.

For affiliates, the professor demonstrates that you can often overlook those who contribute to introduce your brand to the customers. He alerts that your company could be making a wonderful work convincing the client to convert, just to have an affiliate at the end of the funnel, offering a discount coupon that will close the deal. Thus, it is important to use attribution to correctly evaluate and reward your affiliate efforts.

For email and direct email, it is possible to use attribution to track whether an email content contributed to advance the customer through the journey. Russel advises marketers to consider not only the pages that are visited by a user but the emails they read before converting.

Finally, for TV, you can use attribution in an aggregate form to overlay the TV audience data over the digital behavior, tracking whether an advertisement affected your users.

Marketing Attribution Strategies

Finished the tactics section, the professor explains that above the specific tactics, we should consider the main business strategies in which we can apply the marketing attribution insights.

The first and most clear one is the customer journey. Instead of just thinking about the myriad of touchpoints a user can have, the main focus here should be how to reduce the journey and make the user convert as soon as possible. To achieve this, Russel introduces the concept of "Next Best Action". Which prompts the marketing strategist to think about the direct next thing it should be made to enhance the user journey.

Finally, the professor explains that attribution is also useful when you need to assess the value of a brand or analyze the client's lifetime value.

My considerations

As part of the "Growth Marketing" Minidegree, the Attribution course wraps up the Data Analytics trainings, giving insight about how to truly understand user's behavior beyond all the technology and mathematical apparel.

The professor gives real-life examples and is very didactical in his explanations. The downside of the course is the lack of visual tools, with no slide deck or other resources.

This Data Analytics section comes to an end with a strong analytical basis made of Google Analytics, Google Tag Manager, and Marketing Attribution - with high delivery in all of them.