The key strength of digital marketing lies in the the abilities to measure their customer journey and identify how the different channels were resonated with their customers. Within the context of E-commerce, we could use the information to understand which path our customers comes through before they purchase the products on your site or sign up for your memberships. Since Google and Facebook is gradually shifting more traffic to their paid channles, it is essential for any business to build differnet models on their marketing attributions.
In this marketing-attribution project, we will apply following models:
- Rule Based: Last-Click, Time Decay
- Data-Driven Models:
- Shapley Value Models - (Google Analytics is using Shapley Value, However, there is an limitation based on minimum conversions.)
- Markov Chain
It's remarkbale to think that old-fashioned marketing attribution models until recently that was rule-based is now adopting data-driven models by data analyst across different industry. However, Nothing is perfect and even google analytics data-drive models have a limitations on minimum conversions.
In this project, we will go through rule-based marketing attribution models first and then move on to shapley value model and and markov chain model. We will use the sample marketing data from Kaggle. This dataset is the most straight-forward dataset that I came across and we wouldn't spend too much time on data manipulation in this project. For more data cleaning teachniques, check out my data cleaning project.