What is it?

Attribution bias refers to systematic errors in assigning credit for outcomes, often caused by oversimplified models or incomplete data.

It affects decision-making and investment.

Examples in Action

• Over-crediting last-touch channels
  
• Ignoring assistive interactions
  
• Misinterpreting cross-device behaviour
  
• Inflated channel performance claims
  

Typical Outcomes / Results

• Misallocation of resources
  
• Reduced ROI
  
• Improved clarity with better modelling
  
• More balanced decision-making
  

This glossary entry reflects common attribution challenges.