User Experience & Customer Journey Analysis — Gaining valuable insights into the behavior of website visitors for a beauty and personal care brand

This project was carried out as part of the TechLabs “Digital Shaper Program” in Münster (summer term 2021).

Abstract

Our project aimed to analyze the user experience and customer journey of a beauty and care brand website. We used a Markov chain analysis to identify the most common entries, exits, and webpage transitions. Furthermore, we relied on descriptive statistics to understand which website content performs best and which webpages still have room for improvement. Additionally, we performed a cluster analysis to determine segments of website visitors. As for our last step, we worked out managerial implications and recommendations for website optimization.

  • How do website users move around?
  • Where do users exit the website?
  • Which content performs best?
  • How can the users be clustered?
  • … which content on the website performs best and which specific categories and webpages still need optimization.
  • … that the website visitors can be clustered into six meaningful segments based on their specific needs.

Sources

Lantz, Brett (2013), Machine learning with R. Birmingham, UK: Packt Publishing Ltd.

The team

Sabina Almaschij Data Science: R

Mentor

Marcus Cramer

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