Whereas traditional A/B testing solutions would force you to pick a winner, machine learning that uses pattern matching algorithms provides real-time Predictive Content. Marketers should use three sets of data to help guide their content selection process and ask the right questions. Customer data from sources like your CRM, web search and purchase history data are critical. Where is your user when they open the message, what time is it, how close are they to your store? What device are they on? What content, image, or offer is getting the best engagement rates from your users, for this campaign? Parsing all this data is not possible in real-time unless you use a powerful machine learning engine, coupled with Smart Rendering Technology. Learn how brands like Marriott have used Machine Learning to improve their email performance and unlock the value of your data and put it to work to help you get better engagement from your users. After attending this session, attendees will be able to: use their CRM data and information about your customers and prospects to predict what content you should include in your messages, in real-time. create testing scenarios that allow you to try different ideas and concepts without having to wait till a post campaign report to learn the valuable lesson of what worked and what did not work. learn what did not work and what groups did not respond well so that you can avoid similar marketing in the future. learn subtle, non-obvious segments of your audience that responded well to your message and use this knowledge to create better campaigns in the future.