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This project includes a performance for an A/B testing method to test whether an added new webpage to an e-commerce website has an impact on increasing the conversion rate for this website or not.

HTML 69.97% Jupyter Notebook 30.03%
webpage ab-testing python jupyter-notebook regression-models regression logistic-regression ecommerce-website ecommerce conversion-rate

a-b-test-website's Introduction

Motivation

I built this project to evaluate the performance for an A/B testing method that tests whether an added new webpage to an e-commerce website has an impact on increasing the conversion rate for this website or not.

Conclusions

This project aimed at conducting an A/B Test for an e-commerce website for a new webpage. After conducting the test and looking into the results, it's shown that this new page has no statistically significant impact on increasing the conversions for the website. In fact, it shows a negative effect which isn't significant too. So it's recommended to:

  • Either do not implement this new webpage.
  • Or conduct another test taking into consideration other factor like the duration because perhaps the test just needs to be run an additional period of time to observe significant results.

Inspiration

This project helped me later on working in Growth Data Analytics roles where I build & test hypotheses to evaluate:

  • Marketing campaign templates
  • New product features
  • Changes in app UX

a-b-test-website's People

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