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80% of data scientists struggle with finding customer segments. This is how I do Customer Segmentation with Python and AI. 🧵
The challenge is 2-fold. 1. Identifying segments 2. Understanding those segments 3. Marketing decisions for the segments This is where ML and AI come in.
1. Machine Learning Segmentation Machine learning is great at step 1, identifying segments. I use Scikit Learn Clustering Algorithms for smaller datasets. Larger data sets I use H2O K-means.
2. AI for understanding segments ML produces numeric labels. But these have no meaning. The challenge is understanding what the segments mean. This is where AI can help.
3. Building an AI Customer Segmentation Agent To provide marketing decisions, I created a customer segmentation agent. This helps with: 1. Labeling the segments with easy-to-understand categories ("Frequent buyers, interested in learning Python) 2. Making decisions on how to market to them.
4. Problem: Companies need Custom AI Agents that do Customer Segmentation SOLUTION: On Wednesday, May 21st, I'm sharing how to build one of my best AI Projects: AI Customer Segmentation Agent with Python Register here (limit 500 seats): <a target="_blank" href="https://learn.business-science.io/ai-register" color="blue">learn.business-science.io/ai-register</a>
