Customers today expect every brand experience to be personalized and seamless across every channel. That’s no easy feat and exactly why AI is crucial to the future of marketing. With AI, marketers have an opportunity to leverage data to deliver predictive, intelligent experiences customers expect and do it at scale.
Marketing Cloud Einstein empowers marketers to predict the optimal timing, channel, content and audience for any marketing message. And today, we’re taking Marketing Cloud Einstein even further by introducing two new innovations – Einstein Segmentation and Einstein Splits. [Click to Tweet]
Einstein Segmentation: Nothing is more important for a marketer than knowing who their audience is, and Einstein Segmentation enables marketers to build the best audience for each campaign. Using machine learning and pattern analysis, Einstein analyzes billions of consumer signals from within the Salesforce data management platform (DMP) to help brands discover the distinct personas that exist within each of their audiences.
This means that companies will be able to reach each key persona with a tailored message that will resonate to them, rather than blasting a one-size-fits-all retargeting message to everyone who has visited their website.
For example, an outdoor gear and apparel retailer could run a summer campaign around hiking. After digging into the personas, they learn that they have several different personas – Family Roadtrippers, Solo Backpackers and Gadget Enthusiasts. This insight allows them to tailor their message and content accordingly. Family Roadtrippers are shown large, roomy tents and backpack carriers for hiking with toddlers, whereas the Solo Backpackers are shown all-in-one, lightweight camp stoves and the Gadget-Minded Hikers are shown the latest GPS device.
Einstein Splits: For years, marketers have been building journeys simply reacting to past customer data. Einstein Splits solves that – it is a new predictive decision split flow control and is embedded directly into Journey Builder. Now, marketers can build journeys based on a customer’s predicted behavior or persona data generated from Einstein by simply dragging and dropping Einstein Splits into the journey. Predictions include likelihood to open, click, unsubscribe or convert. And personas include Win Back/Dormant, Selective Subscriber, Window Shopper or Loyalist. This enables marketers to test different channels, content and tactics using predicted future behavior rather than past behavior.
LIDS is an Indianapolis-based retail store chain that sells officially licensed and branded hats and apparel for collegiate and major professional sports teams. They have more than 1,000 retail businesses in the US, Puerto Rico and Canada. LIDS uses email marketing as one of their main marketing channels. They needed a deeper understanding of their subscribers, but were limited in their reporting capabilities and not able to get the insights needed with a data scientist. Using Einstein Engagement Scoring, they learned that a subset of customers was more engaged with their emails than previously thought. Additionally, they also learned which subscribers were the least engaged and began suppressing that audience from unwanted email campaigns. They achieved a 4x increase in open rate on new product emails and a 2.5x increase in average open rate–and this type of intelligent targeting will now be even easier with Einstein Splits.
Einstein Splits and Einstein Segmentation are powerful new innovations that can help marketers use AI to build smarter, more personalized campaigns and customer journeys. Join us at Connections today or tune in online to see these technologies in action!
We’re publishing a series of articles focused on the future of customer experience in conjunction with Connections, June 12-14 in Chicago. For more insight, check out this 5-point checklist for exceptional customer experience; this article on why customer experience begins with understanding human nature; and this interview with Glen Hartman of Accenture on the power of empathy in creating personalized customer experiences.