Segmentation Analysis of Companies’ Natural Gas Consumption by Soft Clustering

Doğan, Onur

doi:10.1007/978-3-030-51156-2_7

Cited by 1 publication

(4 citation statements)

References 19 publications

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“…[22] used location data using a beacon network and explained a novel customer segmentation method. [4] proposed a segmentation method considering the number of visiting a shopping mall. They created customers' routes from location data and applied FCM clustering algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Soft computing methods have been used in customer segmentation research as data-based methods. Soft com-puting approaches shape future segmentation studies because of the special applications [4,5,6]. As a soft computing method, fuzzy-based clustering methods are considered the most notable methods [7,4].…”

Section: Introductionmentioning

confidence: 99%

“…Soft com-puting approaches shape future segmentation studies because of the special applications [4,5,6]. As a soft computing method, fuzzy-based clustering methods are considered the most notable methods [7,4]. Recent literature includes different versions of the fuzzy clustering methods employed in various domains such as segmentation [8,9] computer vision [10], customer path segmentation [4].…”

Section: Introductionmentioning

confidence: 99%

“…As a soft computing method, fuzzy-based clustering methods are considered the most notable methods [7,4]. Recent literature includes different versions of the fuzzy clustering methods employed in various domains such as segmentation [8,9] computer vision [10], customer path segmentation [4]. This study adopts the FCM technique, one of the most popular fuzzy-based clustering methods.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Fuzzy RFM Analysis in Car Rental Sector

Doğan¹,

Öztayşi²,

Isik³

2021

Int. j. technol. eng. stud.

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Recency, Frequency, Monetary (RFM) technique is a common and useful way for customer segmentation analysis, which is a must in sales, marketing, and operation management. RFM mainly uses transaction data to investigate customer's shopping behaviour. This study applied a fuzzy-based RFM method that uses renting data from a car rental company. First, data were extracted from the database and were transformed to R, F, and M parameters. Second, R, F, and M parameters were normalized and converted to fuzzy numbers. A fuzzy c -means FCM clustering algorithm was applied to transform fuzzy R, F, and M numbers to make groups for customers. As a result, some customers were regarded as regular customers, where as others could be divided into wintertime and summertime customers. Managers in the company could make better decisions and offer more relevant promotions for specific customer groups.

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Section: Literature Reviewmentioning

confidence: 99%