Naman Gandhi
Naman Gandhi
Data Science Manager at ZS
Naman is a Data Science Manager in the ZS’s Seattle office and has ~10 years of data science and advanced analytics experience with a focus across Consumer and Travel & Hospitality practice. He works closely with clients on formulating and designing varied structured and unstructured data analytics solutions powered using Machine Learning techniques to enable greater commercial effectiveness. Naman’s area of expertise center on statistical modelling, forecasting, bayesian techniques, computer vision, recommender system, and deep learning techniques. Naman has published a few articles in behavioral personalization, computer vision, and Bayesian modeling in leading academic journals as well.
Associate
Professional
Executive
Track: Decision & Risk Analysis
Prioritize Growth Opportunities from Unstructured Consumer Text
Brands are often sitting on a wealth of customer insight in the form of unstructured text that is underutilized in decision making processes because trends are difficult to access at scale in a rapid and inexpensive manner. This session explores examples and an overview of an NLP based analytical approach that helps extract actionable insights. Attendees will leave with an understanding of why we need a word-level approach that can intelligently link concepts based on their meaning, context, and relationship to curate a human-level understanding of customer feedback, and how these trends can help prioritize consumer needs across an entire category and benchmark existing products and services.
