Etkin Bir Pazarlama Stratejisi Oluşturmak için Apriori Algoritması Temelinde Müşteri Satın Alma Davranışının Ölçülmesi

Year 2023, Volume: 38 Issue: 3, 751 - 764, 18.10.2023

Murat Akcıl , Serap Akcan

https://doi.org/10.21605/cukurovaumfd.1377741

Abstract

Teknolojik gelişmeler ve rekabet koşulları nedeniyle müşteri kazanmak ve elde tutmak giderek daha önemli hale gelmektedir. Birliktelik kuralları, hangi ürün ve hizmetlerin müşteriler tarafından birlikte daha önemli ve tercih edildiğinin belirlenmesi amacıyla etkin olarak kullanılan yöntemlerden biridir. Bu çalışmanın amacı, orman ürünleri sektöründe faaliyet gösteren bir firmanın, maliyeti en çok etkileyen, üretimde yoğun olarak kullanılan ve planlanması zor olan dekor kağıdı verilerini kullanarak, satın aldığı desen türlerinin belirlenmesidir. Bu çalışma, birliktelik analizinde yaygın olarak kullanılan WEKA'daki Apriori algoritması ile gerçekleştirilmiştir. Bu çalışmadan elde edilen birliktelik kurallarının firmanın yurt dışı model trendlerini ve birlikteliklerini ortaya çıkararak müşterilerinin satın alma davranışlarını belirlemesine olanak sağlayacağı düşünülmektedir. Ayrıca bu çalışma firmanın pazarlama stratejisini belirleme aşamasında firmaya ışık tutacaktır.

Keywords

Büyük veri, Veri madenciliği, Birliktelik kuralları, Apriori algoritması, Pazar sepeti analizi

Measuring Customer Purchasing Behavior based on Apriori Algorithm for Creating an Efficient Marketing Strategy

Abstract

Due to technological developments and competitive conditions, it is becoming more and more important to gain customers and keep them. Association rules are one of the methods used effectively to determine which products and services are more important and preferred by customers together. The aim of this study is to determine the types of patterns purchased by a company operating in the forest products sector, using the data of decor paper, which affects the cost the most, is used extensively in production and is difficult to plan. This study was carried out with the Apriori algorithm in WEKA, which is widely used in association analysis. It is thought that the association rules obtained from this study will enable the firm to determine the purchasing behaviors of its customers by revealing the overseas model trends and associations. In addition, this study will shed light on the company at the stage of determining the marketing strategy of the company.

Keywords

Big data, Data mining, Association rules, Apriori algorithm, Market basket analysis

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