The science of producing predictions about what content people want to see next is based on lots of data. For example, things that are particularly interesting to a recommendation engine are items that have been seen in conjunction with other items, things downloaded in the same session, and content browsed before and after a purchase, to name a few. These relationships are known to the engine as interesting, because algorithms have been designed to look for them.
If you’re reading this article, you’re either intrigued or already seriously looking to find the best Recommendation Engine technology that offers predictive personalization for your email marketing program. To properly evaluate this kind of technology for your business, below you’ll find a list of questions to ask as well as more detailed criteria you should keep in mind.
According to research by VentureBeat nearly 70% of marketers will use more email marketing in 2018 than in 2014. The value of email is high, therefore businesses everywhere are working to improve their emails and sending even more. There’s a firehose of content aimed at every inbox and only the best of the best will stand out.
In the digital marketing mix, email has long been the leader in terms of revenue. It’s also the top preferred channel by which customers wish to receive information from brands: 72% of of adults prefer it if brands contact them using email versus any other channel.
