- transaction-level attribution with Markov models and Shapley value;
- real-time attribution with Markov model and Shapley value. You can train the model once and than use it for performing attribution on new customer-journeys without retraining;
- Markov model and Shapley value with odds that showed the best performance in terms of generated revenue with respect the main adopted attribution methods;
- combine attribution performed by a multi-touch model and a media-mix model at transaction level;
- elaborate huge datasets containing customer journey one line at a time without loading them in memory.
- out-of-sample validation algorithm for choosing the best Markov model order also for highly imbalanced data;
- multiprocessing for a faster execution of large sized attribution problems;
- preconfigured Docker containers with RStudio or Jupyter and ChannelAttribution Pro installed;
Deepen the features of ChannelAttribution Pro reading our Handbook.
Read out Paper about marketing attribution and budget allocation and see how Markov model outperforms the most used attribution models.Try ChannelAttribution Pro for free!