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In e-commerce, successful businesses understand the importance of a data-driven attribution model. Marketing attribution is the process of determining how your marketing channels contribute to sales and revenue. It is essential to try to predict as well as you can "What marketing affects the buyer journey?", "what marketing is just an unnecessary path to get to your website?" and everything in between. But what is an attribution model, and how does it impact the growth of your e-commerce business? In this blog post, we will explore the key benefits of a smart attribution model and offer tips on implementing this approach for optimal e-commerce profitability.

Traditional attribution models like 'last click' should not be trusted

Traditional attribution models like 'last click' and 'linear' are popular among e-commerce businesses but have limitations. Most importantly, the 'last click' model only rewards the final touchpoint in the buyer's journey, which often is a googling of the brand name when the decision to buy is already made, thanks to an ad on Instagram, for example. The 'linear' model assigns equal credit to all touchpoints in the customer's path to purchase. The problem with these models is that they need to account for the nuances and complexity of the customer journey, which could lead to biased decisions. This is where the smart attribution model comes in.

You need a data-driven attribution model

An innovative attribution model uses machine learning algorithms processing to view customer interactions across channels comprehensively. This approach provides a more accurate understanding of the buyer's journey, making it possible to assign credit to each marketing touchpoint based on its contribution to the sale. With an intelligent attribution model, businesses get more insight into how their marketing channels work together, enabling them to make data-driven decisions that will increase e-commerce profitability.

No attribution model is perfect

However, it's important to note that despite an intelligent attribution model's improvements, it will only capture part of the customer journey. Tracking is never 100%, leading to missing data and a less-than-perfect solution. However, that's not a reason to settle for the traditional models. Instead, it should encourage businesses to continue looking for ways to improve their models and tracking, for example, by applying server-side tracking.


In conclusion, an intelligent attribution model is crucial for e-commerce businesses looking to optimize their profitability. Traditional attribution models mislead the organization by giving credit to marketing channels based on a "one-journey-fits-all" attribution model. It becomes increasingly essential for businesses to adopt a more advanced approach. By using machine learning algorithms, companies can comprehensively view their customer interactions and more accurately assign credit to each marketing touchpoint. If you're an e-commerce business owner, consider evaluating your current attribution model and transitioning to a smart one for increased profitability.

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