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Smarter Marketing with Machine Learning – Building a Segmentation Engine

Built a machine learning-powered segmentation engine that enabled data-driven, personalised marketing at scale.

Smarter Marketing with Machine Learning – Building a Segmentation Engine

Marketing without data is like shooting in the dark. At EY, I helped a large dairy co-op change that by building a smart segmentation engine that drove hyper-personalised marketing campaigns using Azure ML and Python.

The engine clustered customers based on behaviour, preferences, and purchase history. Then, using real-time data pipelines, we automatically triggered campaigns through integrated systems. Think email, SMS, even targeted promotions via CRM tools.

By applying predictive modelling, we were able to identify churn risks, optimise messaging, and increase engagement significantly. On the backend, serverless tools like Azure Functions and Logic Apps kept the system lean and cost-effective.

This project was a textbook example of how machine learning and cloud-native thinking can turn raw data into real customer value.

Conclusion

Data-driven marketing is no longer a competitive edge - it’s the standard. By combining machine learning with real-time automation and cloud-native architecture, we transformed customer engagement into a scalable, intelligent engine. The segmentation platform not only personalised outreach but also delivered measurable business impact. It’s proof that with the right tech stack and strategic thinking, raw data can become one of your most powerful marketing assets.

GitHub Projects, Open Source
1 min read
Jan 30, 2025
By Vishnu Devarajan
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