What are the limitations of DDA?

Here are some key limitations of standard Data-Driven Attribution models (DDA):

Data volume requirements

• DDA typically needs a significant amount of conversion data to function effectively.

• Google recommends at least 300 conversions in the past 30 days and 3,000 ad interactions across Google Ads platforms.

• Businesses with low conversion volumes may not be able to use DDA effectively.

Limited scope

• DDA primarily focuses on digital touchpoints and may not capture offline interactions or other non-click channels.

Cross-device limitations

• Accurately tracking user journeys across multiple devices remains a challenge for DDA models.

Doesn't Measure Incrementality

• DDA doesn't directly measure incrementality and instead model's impact based on historical data.

Attribution window constraints

• DDA models may struggle with long sales cycles that extend beyond typical attribution windows.

  
  

These limitations highlight why it's important for businesses to carefully consider their specific needs and capabilities when implementing Data-Driven Attribution.

To solve for these limitations, we created Incrementality-based Attribution that combines incrementality testing with data-driven attribution to give marketers the most accurate measurement based on incrementality.