Machine Learning Times
Machine Learning Times
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Three Best Practices for Unilever’s Global Analytics Initiatives
    This article from Morgan Vawter, Global Vice...
Getting Machine Learning Projects from Idea to Execution
 Originally published in Harvard Business Review Machine learning might...
Eric Siegel on Bloomberg Businessweek
  Listen to Eric Siegel, former Columbia University Professor,...
Effective Machine Learning Needs Leadership — Not AI Hype
 Originally published in BigThink, Feb 12, 2024.  Excerpted from The...
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5 years 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

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