About This Whitepaper
Customer retention is an important topic for many reasons, but the most compelling is also the most simple: your existing customers are extremely valuable. According to research by Gartner Group, 80% of your future sales will come from 20% of your customers. Further, a Harvard Business School report states that increasing your customer retention by just 5% increases profits by 25-95%.
This information highlights something we already believe here at ReSci – that it’s crucial for businesses to invest in understanding and retaining their customers. Our data science team spends a lot of time thinking deeply about customer retention for commercial businesses, so we decided to dive deeper on the retention metrics most important to your business.
This whitepaper strives to provide insight on retention metrics, providing definitions for some of our core measurements and predictions. By influencing these metrics, we believe that companies can improve their businesses and keep their customers happy.
These definitions will include both high-level descriptions as well as deeper technical discussions.
About The Authors
Sang Su Lee is a data scientist at Retention Science. He is interested in solving less scientific problems in a scientific way. He received his M.S. and Ph.D. in Computer Science from the University of Southern California and B.S. in Electrical Engineering from Yonsei University.
Vedant Dhandhania is a Machine Learning Engineer at Retention Science. He helps predict customer behavior using advanced machine learning algorithms. His passion lies in the intersection of Signal Processing and Deep Learning.
Eric Doi is a data scientist at Retention Science. His goal is to improve every day, just like gradient boosted learners. He studied Computer Science at UC San Diego and Harvey Mudd College.
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