For a considerable time, Amazon provided advertisers with a singular way to gauge the success of their marketing campaigns, utilizing a model referred to as last-touch attribution. This model attributes the entirety of a conversion event's success to the last marketing touchpoint or final ad interaction before a sale is made. Regardless of the multitude of touch points the customer might have engaged with during their buying journey, only the final interaction garners conversion credit. While this approach is simplistic and straightforward, it's not always representative of the customer's journey, as it fails to consider the entire path leading to a conversion event.
In 2021, a significant evolution occurred with the introduction of Amazon Marketing Cloud. Leveraging advanced data and analytics, Amazon revolutionized how marketers attribute success by incorporating the capability to allocate conversion credit to not just the last interaction, but to every single touchpoint along the customer's journey. This was a paradigm shift from the conventional business model of last-touch attribution, signaling a move towards what we call multi-channel attribution or multi-touch attribution.
As the name implies, multi-touch attribution models assign credit to multiple marketing touchpoints that a customer engages with during their buying journey. Unlike the single-touch attribution models (first touch and last-touch), multi-touch models distribute conversion credit across various touchpoints. This recognition of different models is a testimony to the complex and intricate nature of the buyer’s journey, involving interactions with several marketing channels, each warranting a degree of attribution.
The world of brands is abuzz with excitement about the prospects of applying multi-touch attribution on Amazon's platform. The tantalizing idea of crediting multiple ads in a customer's journey seems to offer a level of insight previously unavailable. However, we often caution that as appealing as it may sound, it might not necessarily be the most suitable choice for all. Understanding its efficacy for your brand requires a deep understanding of your customer's journey, a thorough analysis of your marketing strategy, and examining how different channels contribute to the conversion rate.
The science behind Multi-Touch Attribution
Multi-touch attribution recognizes the reality that the average buyer interacts with several ads across different channels before ultimately purchasing a product. We have come to acknowledge that the buying process is rarely a linear journey from viewing a display ad to making a purchase. Instead, it's a labyrinthine path comprising multiple touchpoints, and each interaction could potentially influence the final purchasing decision.
For example, a customer's journey might commence with viewing a blog post, followed by clicking on a social media ad, visiting product pages, responding to a direct mail piece, and finally completing the purchase after clicking through from an email campaign. With a single-touch model, only the email campaign gets the credit, while the value of the other touch points is overlooked. Multi-touch attribution, however, attributes the success to each of these touchpoints, offering a more comprehensive view of the marketing process and revealing the full picture of a customer's journey.
Multi-touch attribution presents a balanced view by providing equal credit to all touchpoints or weighing them based on their significance. There are several types of multi-touch attribution models that brands can consider. The linear attribution model gives equal credit to all touchpoints, the time-decay model attributes more credit to the touchpoints closer to the sale, the u-shaped model gives most credit to the first and last touchpoints, and the w-shaped model splits most credit among the first touchpoint, the lead creation, and the opportunity creation stages.
With the evolution of machine learning and data-driven models, custom multi-touch attribution models have emerged, which assign credit based on the patterns and behaviors specific to a brand's target audience. Google Analytics and Google Ads offer such custom model features, and there are several multi-touch attribution tools in the market that leverage machine learning to allocate conversion credit based on historical data.
The ability to credit every ad in the journey provides a wealth of data, equipping marketers with valuable insights. You could discover previously unnoticed victories and defeats in your ad campaigns, which might have been overlooked under the last-touch model.
Unlocking new possibilities: The power of Multi-Touch Attribution
By crediting multiple ads in a customer's journey, multi-touch attribution provides a more nuanced understanding and helps optimize your marketing strategy.
Testing the success of top-of-funnel ads
If your marketing strategy includes a significant focus on top-of-funnel ads, such as DSP or CTV ads, multi-touch attribution could be an invaluable tool. These types of ads often function primarily as awareness drivers, introducing potential customers to your brand or product. With the traditional last-touch model, these ads might not get the credit they deserve for initiating the customer journey. Multi-touch attribution can reveal the impact these ads have on initiating the customer journey.
Identifying ad successes
Another advantage of multi-touch attribution is the potential to uncover hidden successes in your ad campaigns. An ad that doesn't immediately lead to a sale under the last-touch model might be written off as ineffective. But with multi-touch attribution, you might discover that an ad you had previously dismissed was, in fact, influencing many customers' decision-making process. This ad could be a critical part of the customer's journey, guiding them towards the final purchase.
Effective Ad Combinations
Multi-touch attribution provides the ability to track how different ads work together. This ability offers a deep understanding of which series of ads are most likely to convert a new customer and in what sequence these ads should be served for maximum effect. By observing the patterns in your customers' journeys, you can optimize your ad sequence to increase conversions.
With Xmars' Amazon Marketing Cloud (AMC) solutions, we can help identify patterns in your customer journeys. For example, you might discover that a particular sequence of a DSP ad, a Sponsored Brands ad, and a Sponsored Products ad has the highest conversion rate among all sequences involving these three ad types. You could then focus more on promoting this specific sequence in future marketing campaigns.
A word of caution
While the prospects of multi-touch attribution seem enthralling, it's essential to note that not every brand will benefit equally. In some cases, the last-touch attribution model could still provide a realistic representation of your customer's journey. For instance, if most of your conversions come from users who see a single ad and immediately make a purchase, a multi-touch model might not offer much additional insight. In such cases, focusing on refining your ads for immediate conversion could be the most effective strategy.
Furthermore, brands that rely heavily on offline marketing efforts, like direct mail, may find it challenging to incorporate these touchpoints into a multi-touch attribution model. These activities don't offer the kind of readily available digital data that can be easily incorporated into the model. However, it's worth considering ways to bridge the gap between offline and online data, such as unique offer codes or tracking URLs, to ensure these efforts are also captured in your attribution model.
Remember that implementing a multi-touch attribution model isn't just about crediting all your ads; it's about understanding the customer's journey and learning how to influence that journey to drive conversions. While every interaction matters, the goal is to identify those crucial touchpoints that tip the balance and convince a customer to make a purchase. With this insight, you can make more informed marketing decisions, optimize your ad campaigns, and ultimately, improve your bottom line.
Conclusions
Adopting a multi-touch attribution model could be a game-changer for your brand, transforming the way you interpret your ad campaigns' success and your understanding of the customer's journey. It could be the key to uncovering hidden victories, testing the success of top-of-funnel ads, and identifying effective combinations of ads. But like any other tool, its success hinges on its correct application, and understanding its strengths and limitations is vital. With careful consideration and thoughtful application, multi-touch attribution could open new avenues for your marketing efforts and take your brand to new heights.
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