University of Twente Student Theses
How can machine learning help in Churn prediction for DeJong and Laan?
Telang, A. (2022) How can machine learning help in Churn prediction for DeJong and Laan?
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| Abstract: | This report is of a study conducted at the company DeJong and Laan and deals with applying machine learning to their customer data to predict customer churn. We begin this process by understanding churn exists in parts and is a dynamic presence in the customer journey. It is also a key performance indicator of a business’s health and in this specific case, it is a function of customer satisfaction and loyalty as well as several constraints. The operationalisation of partial churn is done using several variables measuring demographics and the degree of recency, frequency, and significance[monetary] of customers’ purchasing behaviour at the company. The created data set is run under a binary logistic regression model with customer exit acting as the Boolean variable. The attempt is to identify which customers are likely to leave to further strategize their retention. |
| Item Type: | Essay (Bachelor) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Programme: | International Business Administration BSc (50952) |
| Link to this item: | https://purl.utwente.nl/essays/92822 |
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