What is the multi channel attribution problem?

The multi-channel attribution problem refers to the challenge of accurately determining how much credit each marketing channel or touchpoint should receive for driving conversions or sales when customers interact with multiple channels before converting. Some key aspects of this problem include:

1. Complex customer journeys: Modern customers often interact with brands across many touchpoints (social media, search ads, email, etc.) before making a purchase, making it difficult to isolate the impact of any single channel.

   
   

2. Data fragmentation: Data from different channels and platforms is often siloed, making it challenging to get a holistic view of the customer journey.

   
   

3. Time delays: There can be significant time lags between initial touchpoints and final conversions, complicating attribution.

   
   

4. Cross-device tracking: Customers may use multiple devices throughout their journey, making it hard to track interactions across devices.

   
   

5. Offline interactions: Many businesses have both online and offline touchpoints, but offline interactions are harder to track and attribute.

   
   

6. Model selection: There are various attribution models (e.g. last-click, first-click, linear, time decay), each with pros and cons. Choosing the right model is challenging.

   
   

7. Incrementality: It's difficult to determine the true incremental impact of each touchpoint - would the conversion have happened anyway without that particular interaction? WorkMagic's Incrementality-adjust attribution model is a solution for this.

   
   

8. Changing consumer behavior: Attribution models need to adapt to evolving customer behaviors and new channels.

   
   

9. Privacy concerns: Increasing privacy regulations and restrictions on tracking make it harder to collect comprehensive customer journey data.

   
   

10. Technical implementation: Implementing robust multi-channel attribution requires significant technical resources and expertise.

    
    

Solving the multi-channel attribution problem is crucial for marketers to optimize their marketing mix and budgets effectively. Data-driven attribution models that use machine learning and Incrementality-based Attribution that factor in incrementality tests are a great solution for cross-channel measurement.