Machine Learning Demystified: Applying Predictive Analytics to Optimize Personalization

Market research authored by David Daniels (formerly of Forrester Research and Jupiter Research), and other analysts from The Relevancy Group. Sponsored research can be downloaded with registration. Other titles can be purchased for a fee or save and subscribe to our research. Get access. Ask the analyst; Get Access to Answers.

  • Sponsored by Zeta Global

    Written by David Daniels with Nicholas Einstein Machine Learning, Artifical Intelligence, Personalization, ROI

    About: Published in May 2017, we take an extensive look at machine learning, specifically personalization artificial intelligence. The research looks at the which machine learning personalzation technologies are being utilized.  We examine the finanical impact of of these methods and the role of services in implementing such perosnalziation techniques.

    We address these topics:

    - Machine Learning/Personalization Artificial Intelligence Challenges

    - Data Utilized For Predictive Modeling 

    - Personalization Tactics That Drive Business Results by Curation Type

    - Monthly Email Marketing Revenue – Human- vs. Machine-Curated Content

    Report Excerpt: Marketers are leveraging machine learning to unify and personalize the customer experience across Everychannel, yet personalization tactics dominate email marketing. Email personalization is almost equally split between human and machines. Many marketers plan to adopt Personalization Artificial Intelligence (PAI), have strong budgets to do so. Successful marketers are utilizing PAI in combination with services expertise. Marketers utilizing PAI have a shorter production process and those campaigns are driving more revenue than human-curated personalization.

    The Research: 9 pages, 8 graphics, 2533 words

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