Build a Strong Attribution Strategy to Fight Fragmentation

Today’s average path to purchase involves 56 touch points across various platforms. This proliferation of channels introduces a new layer of complexity and complicates creative alignment, as disjointed campaigns lead to consumer distrust and frustration. 

If marketers can’t identify which combinations of channels are working or, more importantly, which ones aren’t, effectively prioritizing ad spend becomes nearly impossible. With the right attribution model, marketers can centralize metrics to visualize the entire customer journey, prioritize budgets to maximize ad spend, and make data-backed recommendations to leadership. These tools help centralize and normalize data and ensure that it is clean, deduplicated, and ready for deeper analysis. 

Choosing the right attribution model can be complicated. Here are the most common types, along with their pros and cons.

Full-path model 

This model is the most extensive and technical since it provides the most comprehensive tracking of a customer’s journey, recording every marketing interaction they encounter from the first touch point to the final conversion. It accounts for all marketing efforts, such as display ads, social media interactions, email campaigns, and even post-purchase engagements, making it highly effective for in-depth analysis of what works and what doesn’t. 

It provides a detailed, end-to-end view of the customer journey, allowing marketers to accurately attribute revenue to specific marketing efforts. It also helps optimize budget allocation by highlighting the most influential touch points in the customer journey and supports strategic decision-making by revealing how different channels work together to influence conversions. 

However, it requires significant resources, including advanced analytics tools and skilled personnel to manage and interpret the data, and can be time-consuming to set up and maintain. 

Linear attribution 

This model assigns equal value to all touch points in a customer’s journey. For example, if a customer finds you on Facebook, then signs up for your newsletter, and finally clicks an email link before making a purchase, each touch point would receive equal credit for the conversion. 

It’s relatively easy to implement and understand, making it a practical option for teams with limited resources or those just beginning to explore multi-touch attribution. Assigning equal credit to all touch points in the customer journey emphasizes the value of every interaction. A downside, though, is that it lacks nuanced insights because it doesn’t account for the varying influence that different interactions may have on the final conversion. 

Time decay model 

Unlike the linear model, where each interaction gets equal credit, the time decay model assigns varying credit to all marketing touch points in a customer’s journey. It weighs them based on their proximity to the final conversion. 

For example, if a customer first encounters your brand through an email but later clicks a button on your website, the email would receive minimal credit, while the website click would receive the most, reflecting its more significant influence on the point of purchase.

Giving more credit to later touch points emphasizes nurturing leads and building relationships over time. This model is more useful for businesses with extended sales processes, where multiple touch points are needed to guide the customer toward a decision. 

The cons of this model are that it’s less effective for short sales cycles, as it undervalues critical early touch points. It may also provide limited insights into the effectiveness of upper-funnel activities, which are essential for initial brand awareness and interest. 

W-shaped model

The W-shaped model follows a very set pattern: 90% of the credit is evenly split between the first, third, and last marketing touch points. These three stages—visit, lead, and sale—are considered the most critical in the customer journey. The last 10% is divided between the second and fourth touch points, hence the W shape.

Highlighting the visit, lead, and sale stages showcases the most influential moments that drive conversions. This model is well-suited for businesses with multistep sales processes, where specific interactions are crucial for progressing customers through the funnel. It benefits marketers who want to highlight the critical stages in the customer journey without completely disregarding the value of intermediate interactions. While its biggest flaw is that it overlooks touch points outside of these stages, it highlights key interactions in the funnel.

However, by adhering to a set pattern, it can overlook various influences for other touch points that contribute to the overall customer experience. Its rigid structure may only fit some customer journeys, particularly those with nonlinear or more complex paths.

U-shaped model 

Like the W-shaped model, a U-shaped model gives 80% of the credit to the first and last interactions—typically the initial visit and the final conversion. The remaining 20% is distributed among the middle touch points, reflecting their supportive role in moving the customer along the path to purchase. 

This model is great for businesses that want to focus on the most influential touch points—attracting customers and driving conversions—without entirely ignoring the value of the middle touch points. It simplifies attribution by focusing on the most critical stages, making it easier to understand and implement, and prioritizes initial engagement and final conversion, making it ideal for strategies heavily focused on these areas. 

But giving less credit to middle touch points may undervalue the role of nurturing activities between the first and last stages. This model is less effective for businesses with longer or complex sales cycles where middle touch points significantly impact the final conversion. 

Custom models 

Attribution models can be tailored to a company’s specific needs, incorporating elements from standard models rather than creating something entirely new, which allows for precise control over credit distribution for conversions and across touch points. However, developing and maintaining custom models can be time-consuming and expensive. A more practical approach is to use pre-built attribution models and adjust them as needed. 

Turning insights into action 

As privacy regulations tighten and third-party cookies slowly fade, understanding customer behavior at every touch point becomes more critical than ever. But multi-touch attribution is not a one-size-fits-all solution; it’s a dynamic process that requires ongoing analysis and adjustments. Marketers should be prepared to toggle between different models and ask critical questions to ensure their strategies remain effective.

Marketers who regularly adjust their attribution models and ask the right questions will be better equipped to turn insights into actionable strategies. By doing so, they can optimize their campaigns, make data-driven decisions, and ultimately drive meaningful outcomes in an ever-evolving advertising ecosystem.