Skip to content

Marketing Channel Attribution with Markov Chains in Python

Notifications You must be signed in to change notification settings

anitatea/marketing_attribution_markov

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Marketing Channel Attribution with Markov Chains in Python

Markov chains, in the context of channel attribution, gives us a framework to statistically model user journeys and how each channel factors into the users traveling from one channel to another to eventually convert (or not). By using these transition probabilities, we can identify the statistical impact a single channel has on our total conversions.

Overview

More so today than ever, digital marketing is an integral step in establishing a brand. There are various channels in which this takes place. Did my Google Ad bring in more customers or paid influencers on Instagram?

Use Cases

  • CPG products - your grocery items
  • Retail - does your product have more of an impact when advertised by a local influencer?
  • Delivery services - web-based vs. mobile ads

✍️ this project is a WIP ✍️ - Stay Tuned!

Data source: https://nijianmo.github.io/amazon/index.html

About

Marketing Channel Attribution with Markov Chains in Python

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published