85% of data scientists do customer segmentation the WRONG WAY.
AI Agents fix this—here's how I made an AI that clusters customers & recommends marketing actions (and you can too). 🧵
Traditional K-Means finds clusters, but that's just the start.
The real challenge?
Interpreting clusters for business value.
AI Agents summarize clusters, spot hidden patterns, and suggest personalized strategies.
My AI Customer Segmentation Agent uses ML for clustering + LangChain for intelligent exploration.
It turns raw data into actionable recommendations— like targeting high-value segments with tailored offers.
So, you need to learn how to make an AI Customer Segmentation Agent:
- Scikit learn
- LangChain
- OpenAI
- LangGraph
- K-means
PROBLEM: You'll have to figure it out on your own.
Or...
SOLUTION: AI for Customer Segmentation Analysis Agents
On Wednesday, July 23rd, I'm sharing one of my best AI Projects: Customer Segmentation Agent with AI
Register here to learn how to build AI customer segmentation agents (500 seats): learn.business-science.io/ai-register
That's a wrap! Over the next 24 days, I'm sharing the 24 concepts that helped me become a data scientist.
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