How to Turn Unstructured Customer Feedback into Structured Insights with AI
Hosted by Yogabalaji G and Shaw Talebi
Unstructured feedback → actionable insights
Transform unstructured customer feedback into actionable insights using AI
Text processing pipeline at scale
Build a pipeline that processes unstructured text at scale
Fortune 500 case study
See a real case study from a Fortune 500 engagement showing this approach in production
A retailer was losing $283M in sales and couldn't explain why. Pricing, seasonality, and supply chain analysis all came up empty. Yogabalaji G used an LLM pipeline on raw customer survey comments and surfaced the real cause: anti-theft locks on electrical items were driving million-dollar contractors to competitors. He walks through the full build so you can run the same play on your own feedback data.
Yogabalaji G
Data Scientist @ Mu Sigma
Yogabalaji G is a Data Scientist at Mu Sigma, specializing in AI, data analytics, and predictive modeling for Fortune 500 organizations. He has addressed 10,000+ students and professionals as a keynote speaker across academic and industry platforms, and serves as a selector for the Ellison Scholars Program (Harvard) and the Rhodes Scholarship (Oxford).
Shaw Talebi
Ex-Toyota Data Scientist with 8+ years in AI. Teaching over 100k learners.
Shaw Talebi is an AI educator and builder, teaching 100,000+ builders on YouTube. He earned his PhD from the University of Texas at Dallas, where he worked as an applied AI researcher. He later created the AI Builders Bootcamp, a top-rated Maven course (4.7★ from 75 reviews) that trained builders from companies including Google, Microsoft, Meta, and AWS while he continues shipping SaaS products.