Power BI Basics: Customer Segmentation with K-means Clustering (Coffee Shop Case Study) [Video]

In this Power BI session, we will start with customer segmentation using one of the most powerful unsupervised clustering algorithms, the K-means algorithm. We will begin with a real-life case study of a coffee shop and show the identification of different groups of customers based on their purchase behavior and preferences.

In this section, we will walk you through how to perform K-means clustering using Power BI, step by step, from data preparation to building a model and insightful data visualization to find the hidden patterns and trends in your customer data for certain marketing strategy tuning.

Be it owner, marketer, or even data analyst, the session shall equip one with knowledge and skills on leveraging customer segmentation. Find how to do the following:
1. Understand the basic principle behind K-means clustering and then apply this process in the segmentation of customers.
2. Prepare and import the customer data into the environment of Power BI.
3. Deploy the K-means Algorithm inside Power BI to then segment your customers.
4. See how to present the visualized outcomes of K means clustering analysis.
5. Gain actionable insights into how to better target customers and enhance marketing campaigns for business growth.

Don’t be left out; unlock all the secrets of your customer base to make data-driven decisions that will drive your business forward. Subscribe to our channel for more informative Power BI tutorials and insights on everything Power BI.

Drop your questions as comments so that we can discuss those on the next Power BI episode. 🙂

For more information, check out my website: https://yasumiwickramasinghe.com/