Quantile Regression: Is the Whole Greater than the Sum of the Parts? - Machine Learning Times - machine learning & data science news
Machine Learning Times
Machine Learning Times

1 year ago
Quantile Regression: Is the Whole Greater than the Sum of the Parts?

 By: Sam Koslowsky, Senior Analytic Consultant, Harte Hanks A key metric that marketers track involves customer life time value. With the proliferation of segment managers, and the availability of ‘BIG’ data, there has been an ever-increasing need to both evaluate and model this all-important measure.  The old 80/20 (or perhaps 90/10) rule maintains that the preponderance of profit emanates from a few valuable customers.  By definition, this implies that the distribution of this profitability yardstick is quite skewed. The graph below better depicts this relationship. Much of the profit emerges from the top quintile. Little emanates from the bottom 20%.

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