Six case studies of machine-learning powered email marketing – Econsultancy

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Machine learning has changed the game for email marketers. Once hyped as the'next big thing', it is now being put into practice by a wide range of businesses to improve the effectiveness of email. Here are just six case studies that demonstrate its success. Language plays a huge part in why consumers respond to marketing (and why they don't). To figure out why its email engagement rates were declining, Dell partnered with Persado in 2016.


These Startups Are Using AI to "Optimize" Marketing Messages - Cox BLUE

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In a world where artificial intelligence (AI) is gaining traction and being applied in a variety of ways, is it really possible for AI to do intuitive things better than humans can, such as marketing messages? Marketing messaging seems like something that takes human brain power to fully develop, understand, and formulate to optimize return, so could an AI-powered service offer better results?


These startups use AI to "optimize" marketing messages

#artificialintelligence

In a world where artificial intelligence (AI) is gaining traction and being applied in a variety of ways, is it really possible for AI to do intuitive things better than humans can, such as marketing messaging? Marketing messaging seems like something that takes human brain power to fully develop, understand, and formulate to optimize return, so could an AI-powered service offer better results?


How AI & Dynamic Content Are Reinventing Email Marketing

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AI is undoubtedly one of the biggest marketing buzzwords today and, combined with dynamic content, it's helping one longtime brand asset – email – become even more effective.


6 ways AI is making Email Marketing Smarter

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AI and machine learning capabilities are offered by many marketing automation platforms today to help marketers drive better targeting, relevance, and results. In email marketing, AI-powered tools have the potential to change the game, as Andrea Wildt, CMO at Campaign Monitor said in a chat with us at the start of the year - from predicting the best type of content and the right send times to helping with more complex personalization. A/B testing is not new. Email marketers (and marketers in general) have always performed tests to assess which variant of a particular campaign will work better for audiences. This testing relies on user data (behavior), as well as design and technology intuition to form hypotheses that help point marketers toward what would resonate most with their targets.