Identify Potential Customers With Unsupervised and Supervised Machine Learning
Unleash new opportunities with data
Bringing new customers to a service is a common business problem, which can be solved by analyzing data of existing customers and the general population.
In this blog post, I would like to talk about how a company can bring new customers through customer segmentation and analyzing the general population using supervised and unsupervised machine learning.
Outline of the post:
1. Explaining types of customer segmentation
2. Getting to know the data
3. Data cleaning
4. Data preprocessing
5. Applying k-means clustering to find segments within existing customers
6. Calculating Euclidean distances to find similar people in the general population
7. Predicting customer’s subscription using XGBoost and Gradient Boosting classifiers and Kaggle competition
1. Types of customer segmentation
In today’s increasing competition within markets, it is important to understand the different behaviours, types, and interests of customers. Using market segmentation, marketers can tailor…
