Data Mining: Machine Learning for Customer Insight

November 15th, 2016 |
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IT Best Practices: Data mining using machine learning enables businesses and organizations to discover fresh insights previously hidden within their data. Whether exploring oil reserves, improving the safety of automobiles, or mapping genomes, machine-learning algorithms are at the heart of these studies.

At Intel, we are quickly moving machine learning from an academic pursuit to a driver of innovation and competitive advantage for our business. To that end, Intel IT developed a machine-learning tool that helps Intel’s sales and marketing organization identify which resellers will best connect with customers in specific vertical industries.

The machine-learning algorithm helps us learn more about our resellers by classifying them and then supplementing this information with another algorithm that mines resellers’ website content. The machine-learning system can also integrate data from an Intel product-recommendation system.

We conducted a proof of concept (PoC) that demonstrated that our tool was effective even when users invested little effort and that it worked across geographies and languages to identify relevant resellers.

Since the PoC, Intel sales and marketing teams have delivered communications to eight vertical industries across four geographies and in eight languages. When we tracked resellers in the engagement chain, we found that, in comparison with the rest of the sales pipeline, twice as many resellers advanced from leads to qualified leads. Their click-through rate for email newsletters is now three times higher, and they complete Intel training at a rate three times higher than the rest of the sales pipeline.

These results reinforce Intel IT’s growing use of machine learning to turn big data into deep insights and to make recommendations in real time for our smart and connected world.

For more information on Intel IT Best Practices, please visit

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Posted in: Big Data, Intel, Intel IT, IT White Papers, IT@Intel