HEAR YOUR CUSTOMERS, AT SCALE
An AI Assistant to analyze customer service issues.
Challenge
A multi-location service brand was losing customers but couldn’t pinpoint why. Reviews lived across Google, Yelp, and forums without structure, making it impossible to compare locations, spot emerging issues, or tie feedback to action.
Solution
We ingested reviews via APIs/scraping, applied sentiment and multi-label classification (e.g., service speed, quality, receptionist knowledge, technician expertise, cleanliness), and stored normalized results for analysis. The corpus also powers a knowledge base for thematic comparisons and action planning.
Results
Leaders gained a decision-grade dataset that surfaces store-level trends and root causes in days, not months. Teams can compare top vs. bottom locations, target training precisely, and track changes over time—turning scattered comments into systematic service improvements.