Customer Segmentation using Data Mining Technique: A case study of Retail Industries in Nigeria

Onyianta John Chiedozie, Musa Ibrahim Umar, Agbo Jonathan Chukwunwike


The importance of retail industries are seen in the exchange of goods and services. Retail industries are the meeting point where different producers and wholesalers have direct contact with the final consumer. Other than distributing goods to the consumers, they are also involved in providing essential services to their clients. Recently, due to the rapid growth in information technology, such as availability of networks, fast internet and mobile devices, the present-day retail industries has also witnessed a significant change. There are challenges involves in the use of IT in retail business such as security risk and operation cost. Despite these risks, in other to stay ahead of other competitors, it is important to adopt the use of information technology to maximise profit and improve customer satisfaction. The aim of this study is to apply K-nearest Neighbour (KNN) classification algorithm on customer driven data such as their shopping pattern, choice of product, amount spent after shopping and average time spent on shopping to properly predict and classify the customer’s class of income earning.


Customer Segmentation, Data Mining Technique, Retail Industries

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