DMP vs DSP: Differences & Similarities Explained
by Cat Hausler
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6 Min Read
When running numerous campaigns across various channels, it can be challenging to know exactly which ads are most responsible for guiding your target audience to a purchase. That’s where marketing attribution models come in.
Attribution is the process of identifying which advertising and marketing strategies are effectively driving conversions. Each attribution model takes a unique approach to analyzing and assigning credit to the marketing touchpoints in a customer’s journey. Some of the more well-known TV attribution models include:
Each of these attribution models has its own pros and cons, but in this article, we’ll be specifically diving into time-decay attribution.
Time-decay attribution focuses on the timing of a customer’s interactions with marketing materials, giving more credit to those that occur just before the customer makes a purchase. The central idea in the time-decay attribution model is that, although all marketing efforts contribute to the customer’s journey, those occurring closest to the purchase are pivotal in swaying the customer’s decision. This model aims to strike a balance, recognizing the cumulative effect of all marketing activities while emphasizing the importance of the last few interactions.
Time-decay attribution acknowledges that multiple touchpoints influence a customer’s decision-making process, and it focuses on the timing of those interactions. The process begins with tracking all the interactions a customer has with a brand. This could include steps like seeing an ad, visiting a website, engaging with a social media post, or clicking an email link. Each touchpoint is time-stamped to indicate when the interaction occurred relative to the eventual purchase or conversion.
The recorded interactions are then arranged chronologically, creating a timeline from the first engagement to the conversion. The time-decay formula is then applied to assign value to each interaction based on its proximity to the conversion. The assigned value varies but usually uses an exponential-decay function, meaning the credit given to each interaction decreases exponentially as you move back in time from the point of conversion. For example, an interaction that takes place one day before a conversion might be worth twice as much as an interaction that happens two days earlier.
Imagine a customer’s journey in which they first click on a digital ad, visit the brand’s website a week later, and finally — two days before making a purchase — click on a retargeting ad. In the time-decay model, the retargeting ad (being the closest to the purchase) gets the most credit, followed by the website visit. The ad click would get the least amount of credit in this scenario.
The time-decay attribution model offers several key advantages that make it an appealing choice for marketers aiming to optimize their strategies. Its core benefits include:
Although the time-decay attribution model offers numerous benefits, it also has limitations. Understanding these drawbacks is crucial for marketers to leverage the model effectively. Notable disadvantages include:
Many of the more traditional attribution models have their own disadvantages, and time-decay attribution is no exception. However, time-decay attribution can offer valuable insights for the right campaigns.
Imagine that you own a clothing store, and you’re aiming to boost sales for your new summer collection. A customer first encounters your brand through a social media ad, a month before making a purchase. A couple of weeks later, they click on a promotional email. Then, a week before making the purchase, they visit your website through an organic search. Finally, two days before they make the purchase, they click on a retargeting ad for the summer collection.
In the time-decay attribution model, the retargeting ad receives the most credit because it was the closest to the purchase. The website visit via organic search, being a week before the purchase, gets less credit than the retargeting ad but more than the earlier interactions. The promotional email gets even less credit, and the initial social media ad, being the furthest from the point of purchase, receives the least credit.
This distribution acknowledges that the earlier interactions played a role in making the customer aware of your brand and keeping them engaged, but the retargeting ad was more influential in the final decision to buy from your summer collection.
Interest in Connected TV (CTV) is on the rise, and as a result more and more advertisers are turning to this growing channel to reach consumers. As advertising evolves with the rise of interconnectivity, accurate TV attribution is essential for optimizing your CTV marketing campaigns. So while models like time-decay attribution have been useful in the past, they no longer accurately reflect how consumers interact with and absorb the ads they see on their TV screens and beyond. That’s why MNTN created Verified Visits™, which can facilitate the most accurate attribution in CTV today. Here’s how it works:
While the time-decay attribution model offers a unique view of how different advertisements affect consumer behaviors, it ultimately falls short when it comes to marketing campaigns aimed at building long-term brand awareness and customer relationships. It also fails to appropriately credit advertisements that inspire initial engagement and build interest over time. By working with a partner like MNTN, brands can ensure that their attribution is measuring up in a world that is more interconnected than ever.
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