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WNW streaming A/B test project for my Applied Analytics subject at university

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ab-test-project

WNW streaming A/B testing project from my Applied Analytics subject at university.
The final report can be viewed via https://carimo198.github.io/ab-test-project/

Background

WNW is a streaming company which is refining their recommendation engine to provide better recommendation to customers.
Better recommendations improve user engagement and importantly increase the average hours watched per user per day, a key metric used to price ads for 3rd party marketing companies.

The executives at WNW want to know if the new recommendation engine algorithm is worth rolling out to all their subscribers. They have asked you to analyse the results from a recent change they made in their recommendation engine and present the results to the executive team.

The sample data

The executives are also interested in any other insights you may learn from the sample data (available to download on my ab-test-project repository). In particular, they are curious about the following:

  • Is there any bias in the data collection?
  • How could any bias be corrected?
  • What improvements could be made to future A/B tests?

The sample data shows the effect of an A/B test conducted to measure the effectiveness of a change to the recommendation engine used on some subscribers, but not others. The change to the recommendation went live at 1-minute past midnight on the 18th of July.
Those customers who were unknowingly using the new recommendation engine to suggest what to watch next are labelled as group B, while group A was used as a control group.

The data set has the following fields:

  • date in format dd/mm
  • gender of the customer
  • age of the customer
  • social metric, which is a combined metric based on previous viewing habits
  • number of months since the customer signed up
  • demographic number
  • group (A/B) where A is the control and B is the treated group
  • number of hours watched in that day

The streaming_data.csv contains the dataset.
The complete code for the project is available via the ab_testing_project.Rmd file.
The final report can be viewed via https://carimo198.github.io/ab-test-project/

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WNW streaming A/B test project for my Applied Analytics subject at university

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