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Dergiler / İşletme Araştırmaları Dergisi / 2018 / Cilt: 10 - Sayı: 4

Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study

Damla ASLAN
METEHAN TOLON
Sayfa
887–900
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The successful clusters are obtained by k-means application.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Customer segmentation is an essential activity for marketing executives.
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Temel Bulgular & Veri:To penetrate to target market, they should analyze their clients very well.
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Sonuç & Katkı:The successful clusters are obtained by k-means application.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Özet

Customer segmentation is an essential activity for marketing executives. To penetrate to target market, they should analyze their clients very well. Undoubtfully customer lifetime value (CLV) is a compact calculation method to understand customer behaviors and their values. Various models are presented for CLV interpretation in literature. Two of them are statistical hypothesis tests and k-means. This case study provides the comparison these methods for a B2B IT company. The methodology can easily be used for similar purposes in other organizations. The successful clusters are obtained by k-means application.

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Bu Makaleye Atıf Yap

ASLAN, D., TOLON, M. (2018). Comparing Customer Segmentation With CLV Using Data Mining and Statistics: A Case Study. İşletme Araştırmaları Dergisi, Cilt: 10 - Sayı: 4, 887–900. https://ajindex.com/articles/269470

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Kaynakça (15)

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