Predicting and Preventing Customer Technical Issues Using Machine Learning and RPA
Toronto Machine Learning Series (TMLS) via YouTube
Python, Prompt Engineering, Data Science — Build the Skills Employers Want Now
Lead AI Strategy with UCSB's Agentic AI Program — Microsoft Certified
Overview
AI, Data Science & Cloud Certificates from Google, IBM & Meta — 40% Off
One plan covers every Professional Certificate on Coursera. 40% off your first 3 months — limited time.
Unlock All Certificates
Discover how to predict and preemptively address customer technical issues in this insightful conference talk from the Toronto Machine Learning Series. Learn from Rogers Communications' senior leaders as they share their journey in developing a machine learning model with over 90% precision to forecast customer problems before they occur. Explore the innovative combination of machine learning, robotic process automation (RPA), and process engineering that enables proactive issue resolution, potentially saving millions in reactive customer support costs. Gain valuable insights into operationalizing predictive models using RPA and understand how this ecosystem can significantly benefit large telecom providers and other industries. Delve into the challenges and solutions of transforming from a reactive to a proactive customer service approach, ultimately enhancing customer experience and operational efficiency.
Syllabus
Predicting which Customers Will Experience a Technical Issue Tomorrow, and Will Call as a Result
Taught by
Toronto Machine Learning Series (TMLS)