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Clickstream Analytics with Markov Chains

Covers key concepts of clickstream analysis and Markov Chains. Followed by 3 practical applications with the R language: - Frequent path analysis - Future click prediction - Transition probabilities mapping

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Clickstream Analytics
with Markov Chains
MeasureCamp #12
Alexandros Papageorgiou
analyst@alex-papageo.com
Next 30 mins
● What is the clickstream
● Markov Chains overview
● Practical examples and techniques
● Discussion
About me
Account Strategist @ Google Ireland
Consumer behaviour analyst @ WhatClinic.com
Analyst @ alex-papageo.com
Why Clickstream
● Enable advanced types of analysis eg. Data mining/Machine Learning
● Get closer to the voices of our customers
● Go beyond standard segmentation analysis
Alternatives ?
What’s clickstream exactly ?
A tidy example

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Clickstream Analytics with Markov Chains

  • 1. Clickstream Analytics with Markov Chains MeasureCamp #12 Alexandros Papageorgiou analyst@alex-papageo.com
  • 2. Next 30 mins ● What is the clickstream ● Markov Chains overview ● Practical examples and techniques ● Discussion
  • 3. About me Account Strategist @ Google Ireland Consumer behaviour analyst @ WhatClinic.com Analyst @ alex-papageo.com
  • 4. Why Clickstream ● Enable advanced types of analysis eg. Data mining/Machine Learning ● Get closer to the voices of our customers ● Go beyond standard segmentation analysis
  • 6. What’s clickstream exactly ? A tidy example
  • 8. 3 useful applications ● Frequent Path analysis ● Future Click prediction w/ Markov Chains ● Transition Probabilities mapping w/ Markov Chains
  • 9. Markov Chains ● It’s a 100+ year old theory. ● Hidden Markov Models, Markov Chain Monte Carlo, higher order Markov Chains ● Used widely in science from physics to finance information science ● Models the evolution of dynamic systems in time
  • 10. Markov Chains ● Page Rank ● Attribution Models ● Clickstream
  • 11. Markov Chains key concepts Media Exposure through the Funnel: A Model of Multi-Stage Attribution Abhishek, Vibhanshu & Fader, Peter & Hosanagar, Kartik. (2012) repository.cmu.edu/cgi/viewcontent.cgi?article=1399&context=heinzworks
  • 12. The clickstream R package. Package Author: Michael Scholz - Cluster your clickstream - Model the clickstream clusters as a markov chain - Visualise and calculate transition probabilities - Predict next click given a submitted click sequence. - Convert the clickstream to an object that is ready for association rules
  • 14. Final thoughts Clickstream analysis has been an academic research topic for quite some time Development of practical applications is now becoming more accessible thanks to open source tools and libraries There are several other methods that play nicely with the clickstream such as clustering, network analysis and association rules.
  • 15. Useful References Clickstream package article on the Journal of Statistical Software www.jstatsoft.org/article/view/v074i04 Supercharging websites with a real-time R API http://code.markedmondson.me/predictClickOpenCPU/supercharge Wikipedia clickstream rabbit holes https://blog.wikimedia.org/2018/01/18/on-that-net-neutrality-clickstream-diagram/ MeaureCamp session Clickstream notebook https://github.com/papageorgiou/measurecamp12-clickstream