As a CMO, your job is to be ready for every marketing development. You’re never allowed to stand still, because the moment you do, something in your industry will change, and you’ll fall behind the competition.
Do you become a different marketer during the holiday season? Until it begins, you spend countless hours researching your audiences, building buyer personas, and executing strategies that put the customer’s experience first. All of your work is rooted in best practice and is conducted with an innovative spirit. I mean, let’s be honest, you’re really good at this.
There are not many new technologies that are truly game-changers. Machine learning is one of those technologies. In a nutshell, machine learning is a form of artificial intelligence in which computers learn to recognize patterns over time and are then able to make complex decisions without human input. Sounds simple enough, right? But it actually has very profound implications for social media.
In the age of smartphones and tablets, home is where your device is. The average consumer spends upwards of three hours a day on their smartphone,so browsing, shopping and satisfying retail needs from wherever they may be is the new norm.
As every email marketer knows, an effective email campaign focuses on relevant content above all else. But there’s a lesson to be learned from print catalogs here, too: product recommendations shouldn’t remind customers where they’ve already been — they should point the way forward to new discoveries, encouraging customers to comfortably branch outward from their core tastes.
Those of us in the tech industry tend to forget that customers frankly don’t want to think about us and don’t want to interact with us. They do want to interact with our products but they don’t want to have anything to do with us. Ultimately, they simply want our products to deliver value to them.
With the help of Oracle Responsys, eHarmony can pinpoint the best time to send an email to each individual. The Oracle AI model leverages customer behavioral data to determine when each customer is most likely to engage with their messaging.