Müşteri davranış tahmini için bir model: Bankacılık sektörü için uygulama

Öz

Son yıllarda kampanya temelli satışlar çok büyük bir hızla artmaya devam etmektedir. Günümüzde birçok sektörde satışlar kampanyaya dayalı olarak gerçekleşmektedir. Bu nedenle kampanya yönetimi oldukça önemli bir konu haline gelmiştir. Literatürde kampanya planlaması ve yönetimi konusunda detaylı bir çalışma bulunmamaktadır. Bu makalede, bankacılık sektöründe kampanya yönetimi ve müşterilerin kampanyaya yönelik ileriye dönük davranışlarının tahmini için bir model geliştirilmiştir. Bankacılık sektörüne özgü geliştirilen birliktelik analizi yapısı kullanılarak bir Portekiz bankasına ait kampanya verilerinden yaygın öğe kümeleri ve birliktelik kuralları oluşturulmuştur. Elde edilen kurallarla kampanyaya katılan müşterilerin ileriye dönük davranışları tahmin edilmiştir. Ayrıca, müşterilerin davranışlarını etkileyen öznitelikler belirlenmiştir. Deneysel sonuçlar, en çok medeni hal ve kredi durumunun müşteri davranışını etkilediğini göstermiştir. Müşterilerin kampanyaya katılıp katılmayacakları geliştirilen model kullanılarak tahmin edilmiştir. Müşterilerin kampanyaya katılım tahmininde %87 oranında başarı sağlanmıştır.

Anahtar Kelimeler

• Büyük veri analitiği
• Veri madenciliği
• Birliktelik analizi
• Banka pazarlama kampanyası

A model for prediction of customer behavior: A case study for banking sector

Abstract

Campaign based sales continue to increase at a very rapid rate in recent years. Today, sales in many sectors are based on the campaign. Therefore, campaign management has become a very important issue. There is no detailed study on campaign planning and management in the literature. In this article, a model is developed for campaign management in the banking sector and prediction of prospective behaviors of customers towards the campaign. Using the association analysis structure developed specifically for the banking sector, frequent itemsets and association rules were created from the campaign data of a Portuguese bank. The prospective behavior of the customers participating in the campaign was estimated with the rules obtained. In addition, attributes that affect the behavior of customers have been identified. Experimental results have shown that marital status and credit status affect customer behavior the most. Using the developed model, a prediction is made on whether the customers will participate in the campaign or not. 87% success was achieved in the prediction of customers' participation in the campaign.

Keywords

• Big data analysis
• Data mining
• Association analysis
• Bank marketing campaign

Kaynakça

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