Marketing attribution is a widely used term in the digital marketing world, encompassing several complex concepts. But what exactly lies behind this term? Is there a right or wrong way to approach attribution? How has attribution evolved in recent years, and where do we stand today? In this article, Wizaly provides comprehensive answers to all your questions about attribution models.
Motivations: Why Are Attribution Models Important?
To grasp the value of attribution, it’s crucial to understand the concept of a consumer journey, which comprises all the interactions a consumer has with your brand. Each interaction is considered a touchpoint in the consumer’s journey. For instance, a consumer may first discover your website through social media, then click on a sponsored link in a search engine, and later make a purchase after receiving a retargeting email. In this example, the consumer journey consists of three touchpoints: SOCIAL > SEA > RETARGETING.
The key question that arises is: Which touchpoint played the most significant role in the purchasing decision? This is where attribution models come into play.
Types of Attribution Models: Predefined and Algorithmic
There are two main types of attribution models: predefined and algorithmic.
Predefined models, such as single touch point and multi touch point models, have been widely used. Single touch point models, popularized by Google, attribute the entire purchase decision to a single touchpoint. For example, the “Last Click” model assigns all credit to the last touchpoint, while the “First Click” model credits the first touchpoint as the sole influencer. Although these models are common, they offer a limited view of reality by focusing on a single interaction and disregarding the role of other touchpoints that contribute to traffic acquisition and finalizing a sale.
In response to the limitations of predefined models, digital marketers have shifted to multi touch point models. These models consider the entire purchase journey, distributing credit among different touchpoints based on arbitrary rules. For example, the “Linear” model evenly distributes credit across all touchpoints. While these models provide a broader perspective, they lack flexibility to accommodate diverse consumer behaviors and changes in media mix.
Algorithmic Attribution: A Realistic Approach
To address the weaknesses of predefined models and leverage big data, new attribution methodologies based on algorithms have emerged. These algorithmic attribution models analyze data collected within your digital ecosystem to understand the impact of each channel in the conversion process without preconceived assumptions.
Wizaly’s Algorithmic Attribution Model stands out by being entirely data-driven and adaptive. It considers all visitor paths, whether they result in a conversion or not, and dynamically adjusts to changes in the media plan and consumer behavior. The model analyzes various characteristics of each touchpoint, including channel, medium, source, time before conversion, engagement, and interaction type. By comparing paths with different characteristics, the model assesses their impact on the conversion rate and assigns appropriate weights accordingly.
In conclusion, predefined single touch point and multi touch point models are now considered outdated in today’s complex digital ecosystem. To obtain a complete and granular understanding of your campaigns’ performance, algorithmic attribution models offer the necessary flexibility and accuracy.
