This week, we share three tips to lay the groundwork for machine learning (ML) in your organization. We describe how unified data and data activation takes marketers to a customer-centric focus. We learn how universities are using predictive analytics to improve student outcomes. We consider how algorithms can diversify the startup pool and finally, we highlight how artificial intelligence (AI) can transform digital marketing.
by Mathias Golombek, contributing writer for InformationWeek.com
Machine learning is showing up in our lives in very meaningful ways. Organizations are viewing ML technologies as a necessary investment that will allow their data to do the heavy lifting. And while ML may seem overwhelming and complicated, creating an infrastructure for ML projects is more achievable than many organizations think. Here are three helpful tips for laying the groundwork for smart and successful machine learning execution.
by Chitra Iyer, editor-in-chief for MarTechAdvisor.com
You strive to deliver seamless customer experiences at scale within a multi-channel environment. But you might find yourself constrained to act as a channel-centric marketer instead of customer-centric marketer. Simply because your data sources and activation plans are driven by the primary channels they operate in, rather than individual customer journey events. Learn how to bridge the gap between unified data and activation for customer-centric marketing in practice.
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by Study International Staff for StudyInternational.com
Dropout rates remain high across many universities. As a way to right the ship, universities are using predictive analytics to improve student outcomes. Especially those who are struggling academically. The use of predictive analytics allows universities to intervene and grant support for students at-risk of dropping out—before they take that final step. Learn how this is currently being put into practice, as well as understand the successes and limitations that accompany it.
by Richard Boire, contributing writer for SloanReview.MIT.edu
Men and women tend to have very different experiences when being evaluated for funding. Research shows that men receive questions that are risk-loving in nature, while women receive questions that are risk-averse in nature. One possible explanation for this bias is what’s known as the “cupcake stigma,” which is the perception that women are less serious about their businesses than their male counterparts. Some VC firms are starting to take note of this bias. The full article explains why this is and what’s being done.
by Jason Hall, contributing writer for Forbes.com
AI in marketing can have a tremendous impact. It can be used to improve the customer journey, increase ROI, automate processes, optimize campaigns, and more. This is possible by tapping into big data analytics, machine learning, and other processes to gain insight into your audience. While there are many things that AI cannot do—like feel empathy or compassion—there’s a lot that it can do to add the value needed to help transform your digital marketing mix.
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