Consumer Behavior Insights Engine for Online Retail

Added Jun 2025 3 design docs

Online retailers sit on rich behavioral data about what shoppers browse, abandon, and buy, but most lack the analytical muscle to turn it into decisions, so pricing and promotions continue to run on intuition. The gap between collecting consumer data and acting on it is exactly where growth stalls. The intern builds an insights engine where agentic AI does the analysis. Real-time sales and behavioral events flow into MySQL, and AI agents mine the data to segment customers, detect emerging demand trends, run sentiment analysis over reviews and feedback, and generate concrete marketing recommendations with the supporting evidence attached. A Node.js backend orchestrates the agents and data pipelines, while a Next.js frontend delivers interactive dashboards where merchandisers explore segments, track campaign performance, and accept or dismiss AI suggestions. Docker keeps deployment consistent across environments, and secure user management separates analyst, marketer, and administrator roles. Completing the project demonstrates how to operationalize AI in commerce: reliable data pipelines, agent workflows that produce accountable recommendations, and dashboard experiences that busy business users actually trust.

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