Customer Loyalty Management Using Data Clustering

Srimathi Ravisankar, B.Tech.

Diplomová práce

Abstract:

Customer data loyalty management is becoming a more essential source of advantage for businesses as the market becomes more competitive. Existing churn prediction algorithms, however, cannot operate well when dealing with huge data in the sector. Furthermore, decision-makers are constantly confronted with sloppy operational management. To address these issues, the semantic-driven subtractive clustering method (SDSCM) is presented as a novel clustering methodology. The Mean shift clustering algorithm is used for further optimising the clustering of data points. The Marketing strategy is proposed by using the customer relationship management tool (CRM). The primary purpose of algorithm design is to reduce the loss of customer loyalty. The CRM is used to provide marketing strategy solutions to the customer who has high risk of leaving the company.

Keywords

Customer loyalty, Probability of transition, Customer relationship management

Jazyk práce: angličtina

Datum vytvoření / odevzdání či podání práce: 26. 3. 2022

Obhajoba závěrečné práce

• Vedoucí: doc. Ing. Tomáš Macák, Ph.D.

Česká zemědělská univerzita v Praze

Provozně ekonomická fakulta

Magisterský studijní program:
Informatics