Hello, everyone! Let’s try to apply K-Nearest Neighbors (KNN) — which is one of the Machine Learning algorithms — for Customer Segmentation on the Online Retail Dataset. We will know each customer segmentation’s characteristics using RFM Analysis. It's fully documented here! https://fiqey.medium.com/customer-segmentation-using-knn-with-rfm-analysis-52c7fd65b8d1
But, you can know the concept here~
Customer segmentation describes the process of identifying groups or segments of a company’s customers who have similar characteristics or factors.
The goal of this segmentation is to optimize marketing for each segment. Customer segmentation is important and vital for
- Optimizing marketing strategies,
- Maximizing customer value to the business, and
- Improving customer satisfaction and experience.
Grouping customers and prospects into customer segments with similar characteristics will help businesses to identify their target customer base. That way, a business’s marketing strategies can be effective and appropriate (not offensive, efficient, and relevant). So knowing customer segmentation will not only save time and money but will enhance the benefits as well.
Now that you understand why it’s important to segment your customers, let’s get started. This project will use the online retail dataset in Kaggle.
RFM (Recency, Frequency, and Monetary) is a key customer trait. These metrics indicate the behavior of customers because the frequency and monetary affect a customer’s lifetime value and recency which affect retention.
Because of that, the RFM analysis is a marketing technique used to quantitatively rank and group customers based on the recency, frequency, and monetary total of their recent transactions to identify the best customers and perform targeted marketing campaigns. All three of these measures have proven to be effective predictors of a customer’s willingness to engage in marketing messages and offers.
Conducting an RFM analysis on our customer base and sending personalized campaigns to high-value targets has massive benefits for our eCommerce store.
- Personalization: By creating effective customer segments, you can create relevant, personalized offers.
- Improve Conversion Rates: Personalized offers will yield higher conversion rates because our customers are engaging with products they care about.
- Improve unit economics
- Increase revenue and profits
- Feature Creation to RFM
Thank you, everyone!