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Customer Segmentation using K-Means Algorithm

  • Customer segmentation simply means grouping your customers according to various characteristics (for example grouping customers by age).

  • There are different methodologies for customer segmentation, and they depend on four types of parameters:

    • Geographic

    Geographic customer segmentation is very simple, it’s all about the user’s location. This can be implemented in various ways. You can group by country, state, city, or zip code.

    • Demographic

    Demographic segmentation is related to the structure, size, and movements of customers over space and time. Many companies use gender differences to create and market products. Parental status is another important feature. You can obtain data like this from customer surveys.

    • Behaviora

    Behavioral customer segmentation is based on past observed behaviors of customers that can be used to predict future actions. For example, brands that customers purchase, or moments when they buy the most. The behavioral aspect of customer segmentation not only tries to understand reasons for purchase but also how those reasons change throughout the year.

    • Psychological

    Psychological segmentation of customers generally deals with things like personality traits, attitudes, or beliefs. This data is obtained using customer surveys, and it can be used to gauge customer sentiment.

Implementing customer segmentation leads to plenty of new business opportunities. You can do a lot of optimization in:

1- budgeting

2- product design

3- promotion

4- marketing

5- customer satisfaction

One very common machine learning algorithm that's suitable for customer segmentation problems is the K-Means clustering algorithm.

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Customer Segmentation using K-Means Algorithm

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