Who are my customers? What the machine can learn on its own

Who are my customers? What the machine can learn on its own
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Sponsored By Melinda Han Williams, VP of data science and analytics, Dstillery In digital marketing, every brand wants to identify the best new customers at the right time on the right screen. But it’s not enough to identify a good versus a bad prospect, nor is it even enough to just understand the characteristics of a good prospect. To truly design an effective brand strategy, you’ll need to understand the variety of stories and reasons that bring customers to your brand, and then identify the different flavors of people behind each of those stories. For example, why do people buy yogurt? The prevailing assumption is that most people buy yogurt for its health benefits. But with one leading yogurt brand, we found that consumers are drawn to yogurt for a variety of reasons, including its appeal to kids as a tasty after-school snack. The good news is, these days brands are overflowing with data to help surface these types of unique stories. And this is true more than ever in the ad tech ecosystem’s lush landscape of observed behavioral data. AI and machine learning give us a way to use that data to surface those customer stories. To utilize machine learning to its fullest potential, you’ll need to understand that there are two main types of the technology: supervised and unsupervised . The difference between supervised and unsupervised machine learning Simply put, a supervised machine learning algorithm learns what you teach it, while an unsupervised algorithm learns on its […]

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