by Angela Guess
Louis Columbus recently wrote in Forbes, “Unlike advanced analytics techniques that seek out causality first, machine learning techniques are designed to seek out opportunities to optimize decisions based on the predictive value of large-scale data sets. And increasingly data sets are comprised of structured and unstructured data, with the global proliferation of social networks fueling the growth of the latter type of data. Machine learning is proving to be efficient at handling predictive tasks including defining which behaviors have the highest propensity to drive desired sales and marketing outcomes. Businesses eager to compete and win more customers are applying machine learning to sales and marketing challenges first. In the MIT Sloan Management Review article, Sales Gets a Machine-Learning Makeover the Accenture Institute for High Performance shared the results of a recent survey of enterprises with at least $500M in sales that are targeting higher sales growth with machine learning.”
Columbus continues, “Key takeaways from their study results include the following: (1) 76% say they are targeting higher sales growth with machine learning. Gaining greater predictive accuracy by creating and optimizing propensity models to guide up-sell and cross-sell is where machine learning is making contributions to omnichannel selling strategies today. (2) At least 40% of companies surveyed are already using machine learning to improve sales and marketing performance. Two out of five companies have already implemented machine learning in sales and marketing. (3) 38% credited machine learning for improvements in sales performance metrics. Metrics the study tracked include new leads, upsells, and sales cycle times by a factor of 2 or more while another 41% created improvements by a factor of 5 or more.”
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