Fractional attribution, also known as multi-touch attribution, is a methodology used in marketing and advertising to assign value or credit to different touchpoints or marketing channels along the customer journey. Unlike traditional single-touch attribution models that assign all credit to a single touchpoint, fractional attribution aims to distribute credit across multiple touchpoints based on their influence in driving conversions or desired actions. 

Why does it matter? 

Fractional attribution is essential because customer journeys are often complex and involve multiple interactions across various marketing channels. By accurately attributing value to different touchpoints, marketers can better understand the effectiveness of their marketing efforts, optimize their strategies, and allocate resources more efficiently. Fractional attribution provides insights into the customer journey, allowing marketers to make data-driven decisions and optimize their marketing mix. 

Methodologies 

There are several methodologies for fractional attribution, including: 

  1. Linear Attribution: In linear attribution, equal credit is assigned to each touchpoint along the customer journey. For example, if a customer journey involves five touchpoints, each touchpoint would receive 20% credit for the conversion or desired action. 
  2. Time Decay Attribution: Time decay attribution assigns more credit to touchpoints that occur closer to the conversion. The closer a touchpoint is to the conversion, the higher the credit it receives. This approach acknowledges that touchpoints closer to the conversion may have had a more significant impact on the customer’s decision-making process. 
  3. U-Shaped Attribution (Position-Based Attribution): U-shaped attribution gives more credit to the first and last touchpoints, with the remaining credit distributed evenly across the intermediate touchpoints. This model recognizes the importance of initial brand awareness and the final touchpoint that led to the conversion. 
  4. Algorithmic Attribution: Algorithmic attribution models use advanced statistical and machine learning techniques to analyze historical data and determine the optimal credit distribution for each touchpoint. These models take into account various factors such as conversion rates, order of touchpoints, time lags, and customer behavior patterns to attribute credit accurately. 

Benefits and Considerations 

Fractional attribution provides several benefits for marketers: 

  • Holistic View of the Customer Journey: By considering multiple touchpoints, fractional attribution offers a more comprehensive understanding of the customer journey, highlighting the influence of various marketing channels and touchpoints. 
  • Optimized Marketing Mix: Fractional attribution helps marketers identify the most effective marketing channels and touchpoints, allowing them to optimize their marketing mix and allocate resources strategically. 
  • Improved Budget Allocation: With fractional attribution, marketers can allocate their budgets based on the value and impact of different touchpoints, ensuring efficient resource allocation and maximizing return on investment (ROI).