Position-Based Attribution Model: What Is It and How Does It Work?

Position-Based Attribution Model: What Is It and How Does It Work?

6 Min Read

Marketing spend in the U.S. reached nearly $481 billion last year, but where is that money going? This is why marketing attribution is vital: to determine which of your marketing efforts are leading to conversions. There are several marketing attribution models, each with their own approach to analyzing and assigning credit to different marketing touchpoints in a customer’s journey. These include:

Among these various methods for mapping a customer’s journey is the popular position-based attribution model

What Is Position-Based Attribution?

Also known as U-shaped attribution, position-based attribution evaluates the impact of different marketing touchpoints by acknowledging that a customer’s ultimate purchase decision is influenced by multiple interactions with a brand. Unlike simpler, single-touch attribution models, position-based attribution gives more credit to specific touchpoints — namely the customer’s first and last interactions with your brand. These interactions are considered the most influential in sparking a consumer’s initial interest and driving their final purchase decision.

How Does Position-Based Attribution Work?

The first step in the position-based attribution model maps out a customer’s journey by identifying each touchpoint where the customer interacts with your brand. 

Position-based attribution is also known as U-shaped attribution because of how it assigns credit to different consumer touchpoints. It separates touchpoints into three categories: 

  • First touchpoint: This is a consumer’s initial engagement with a brand; it (presumably) sparks their interest or awareness
  • Last touchpoint: This is the final nudge that leads to a conversion; it’s when the customer ultimately decides to purchase
  • Middle touchpoints: These represent the middle part of the customer’s journey; it’s where they gain familiarity with your brand and build interest toward making a purchase

Position-based attribution assigns 40% of the credit to the first touchpoint and 40% to the last touchpoint. The remaining 20% is evenly distributed across all of the middle touchpoints. If you were to view this credit distribution on a bar chart, it would appear to create a U shape — hence the nickname.

By attributing the most value to both the first and last interactions before a conversion, while still acknowledging the importance of the journey in between, position-based attribution offers a comprehensive view of a customer’s path and a balanced, data-driven approach to understanding the influence of different marketing interactions.

Advantages of the Position-Based Attribution Model

The position-based attribution model offers several advantages, both compared to other models and in general, including:

  • Balanced credit distribution: The position-based attribution model acknowledges the importance of the entire journey by allocating significant amounts of credit to both the first and last touchpoints and distributing the remaining credit across the middle interactions. This balanced distribution helps you understand how customers are initially attracted to your brand, what keeps them engaged, and what finally convinces them to make a purchase.
  • Data-driven decision-making: By analyzing which touchpoints are most effective, marketers can make informed decisions about where to invest their efforts to maximize their return on investment.
  • A holistic view of the customer journey: Unlike single-touch models that only credit the first or last interaction, the position-based model provides a bird’s-eye view that recognizes that a customer’s decision-making process is influenced by multiple interactions with your brand over time.

Disadvantages of the Position-Based Attribution Model

While the position-based attribution model offers a more nuanced approach to understanding marketing touchpoints compared to single-touch models, it does also have several disadvantages, which include:

  • Arbitrary weight assignment:: One of the primary criticisms of this model is the somewhat arbitrary nature of its 40-20-40 distribution. Some feel the model may not accurately reflect the actual influence of each touchpoint in a customer’s decision-making process, especially considering that many different touchpoints in the middle of a customer’s journey have to share that 20% allocation.
  • Overlooking complex customer journeys: Modern customer journeys can be highly complex and nonlinear, involving multiple channels and touchpoints. The position-based model doesn’t always fully capture this complexity.
  • Potential undervaluation of middle touchpoints: While the model recognizes the importance of middle touchpoints, the way it allocates only 20% of the credit to them can undervalue their impact, especially in scenarios where these interactions play a crucial role in nurturing the customer toward a conversion.

Use Cases and Examples

To further understand how position-based attribution works, imagine that you own a fitness center and want to increase your membership numbers. 

A potential member first searches for “fitness centers near me” and clicks on your paid search ad. They then search for “affordable gym memberships” and “best gym facilities,” each time engaging with your ads. Finally, they sign up for a membership after searching for “best fitness center for weight training” and clicking on your ad. In this case, the position-based attribution model assigns 40% of the credit to both “fitness centers near me” and “best fitness center for weight training,” while “affordable gym memberships” and “best gym facilities” each get 10% of the credit.

In the context of TV attribution, the example looks a little different, but the same principles apply. Imagine that you’re the owner of a travel booking website. A potential customer sees a TV ad for your booking site while watching a travel documentary. They later see another ad during a cooking show featuring international cuisine. Then, they encounter your ad during a late-night talk show. Finally, they book a vacation package on your site after seeing an ad during a special travel-themed TV event. The ads during the travel documentary and the travel-themed event would each get 40% of the credit, and the cooking and late-night talk show ads would each receive 10% of the credit.

The Rise of TV Attribution

With Connected TV advertising on the rise in the U.S., TV attribution has become all but vital for brands of all sizes. And while basic models like position-based attribution may be helpful starting points, they haven’t been able to accurately assess the value of CTV ads. To rise above the attribution models that fall short in TV advertisingMNTN developed Verified Visits™.

Verified Visits™ ensures that MNTN ads get credit only when credit is due. It does this through four simple steps:

  1. A potential customer sees your non-skippable MNTN ad on a premium streaming network.
  2. The potential customer visits your site within a time window defined by you (this usually varies across advertisers and depends a lot on your sales cycle).
  3. MNTN validates the visiting device was in the same household that was first served a CTV ad.
  4. If the visit meets the parameters of Verified Visits™, only then does MNTN take credit. If another media source other than MNTN prompted the visit, we do not take credit for that visit.

MNTN’s Verified Visits™ is the best way to be sure that an ad is taking credit for a potential customer visiting your site only when it’s due.

Position-Based Attribution: Final Thoughts

The position-based attribution model offers a balanced and insightful view of advertising effectiveness. While it has its disadvantages, its advantages in providing a comprehensive view of the customer journey are undeniable. Ultimately, custom attribution models can offer you more accurate insights for a more nuanced solution in TV attribution.