Definitions – Attribution Models

AI Definitions

Attribution Models are frameworks or approaches used in marketing and analytics to allocate credit or value to numerous touchpoints or marketing channels that contribute to a desired outcome, such as a conversion, sale, or other quantifiable action. They determine how credit for sales and conversions is assigned to different channels across different touchpoints in the buyer journey.  

The purpose of attribution modeling is to increase the chances of converting more prospects by identifying areas of the buyer’s journey that can be improved, determining the ROI for each channel or touchpoint, surfacing the most effective ways to spend your marketing budget, and tailoring marketing campaigns and content to unique personas. 

There are several types of attribution models, each weighing channels and touchpoints differently: 

  • Multi-Touch Attribution Modeling: Considers every channel and touchpoint that a customer interacted with throughout the buyer’s journey, up until they decided to convert. 
  • Cross-Channel Attribution Modeling: Designates value to each marketing channel (such as paid, organic, or social media) but doesn’t look at the specific touchpoints within those channels. 
  • Linear Attribution Modeling: Assigns equal credit to each touchpoint along the customer’s journey. 

By using attribution models, marketers can understand how different channels and touchpoints contribute to each sale.