What is probabilistic attribution?

Probabilistic attribution is a method of tracking and assigning credit for user conversions or actions across different marketing touchpoints when deterministic (exact) tracking isn’t possible. Instead of relying on exact user identification (like cookies or user IDs), probabilistic attribution uses statistical modeling and machine learning to make educated guesses about whether different devices or touchpoints belong to the same user. 

The model analyzes various data points such as IP addresses, browser types, device characteristics, usage patterns, and geographical locations to create a probability score that different interactions came from the same user. It enables marketers to connect multiple devices to one user by analyzing common patterns and builds unified customer profiles from scattered digital footprints. This helps track the customer journey even when exact user identification isn’t possible.