RFM Customer Segmentation with K-Means

Rafael Duarte

Data Scientist
Python
Overview 🔎
Customer Segmentation is extremely important for any kind of business. Deeply understanding your customers can help you have greater retention and more sales, which provides more profitability for the business.
Problem & Solution 🤝
In this case, we provided a similar solution to a client, and I created this version of the project with public data, to protect the client's data and identity.
The main goal of the project was to understand customer behavior to better direct marketing strategies, in order to achieve: • Better customer retention • New opportunities for good clients that hadn't purchased for a long time • Better understanding of what went wrong with the customers that never bought from them again.
Process 🛣
First, I had to create a score for each category of the RFM Segmentation. With that score, I was able to segment them further using K-Means, which also gave us insights into clients that would be perfect targets for marketing strategies and actions that could take them into a better category.
Results 🎁
We were able to find opportunities that would help the business have more loyal and frequent clients, which makes the business more profitable.
Takeaways 📣
It was impressive to see how much can be done when customers are properly segmented. It gives the business a macro vision of its clients, which helps decision-makers steer the company in a more profitable and sustainable direction.
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