• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site
For visually-impairedUser profile (HSE staff only)SearchMenu

Possibilities of Predicting User Loyalty Based on Data on Interaction with the Product

Student: Lara Mishchenko

Supervisor: Valentina Kuskova

Faculty: International laboratory for Applied Network Research

Educational Programme: Applied Statistics with Network Analysis (Master)

Year of Graduation: 2021

The purpose of this project is to develop a model that predicts user loyalty based on data about their interaction with the product. Loyalty is one of the key factors of business success [NPS-consumer confidence index, 2020], which is currently (quite often) measured using the methodology developed by F. Reichheld back in 2003 [Reichheld, 2003]. The study was conducted on the product data of one of the largest IT companies in Russia. In order to answer the research question, it was necessary to: 1) perform an NPS measurement; 2) select the predictors that will be used for building the model/models; 3) collect data on the selected predictor; 4) build a model / models that predict user loyalty and summarize the results of the study. As a result, all the above steps were completed: NPS was measured, a list of predictors for the model was formed (thanks to a series of expert interviews and work with the literature), the data necessary for the analysis was collected and several models were built. As a result of the analysis using the Random Forest and XGBoost algorithms, it was not possible to identify a stable model with a prediction accuracy of more than 50%. This fact calls into question the validity of the NPS indicator as a metric related to loyalty and subsequent user retention, since the calculations obtained demonstrate that, regardless of the user experience of interacting with the product, the NPS score can vary.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses