Image source: https://www.bostondynamics.com/
At Criteo, data has always been core to everything we do. We’re a data-driven business and, lately, that means paying attention to the latest developments in machine learning. In our new data hub, we tried to predict what machines would be doing next week, next year, and decades from now.
But we didn’t predict back-flipping robots.
A spinoff from the Massachusetts Institute of Technology, Boston Dynamics recently debuted a video of their humanoid Atlas robot performing perfectly executed (and some not) gymnastic moves, from leaping across the tops of spaced out boxes to – wait for it… a backflip!
Video Source: https://www.bostondynamics.com
From Parkour to Personalization
While performing backflips isn’t exactly necessary for performing everyday tasks, the Atlas’ agility and ability to learn highlights the growing role of data and machine learning in our everyday lives.
(Learn more: Man v. Machine: Is Your Job at Risk?)
We can see in real-time innovations in medical diagnoses and smart cars. We can also see it when it comes to the creative side of marketing. While you probably know that data is important for your business, it’s another thing to actually start using it. Many businesses are saturated with data – far too much for a human to analyze – and that’s where machines have started to help.
When it comes to personalization, machine learning enables retailers and brands to comb through and analyze huge data sets about their shoppers. From that data, the technology can help deliver customized offers to individual shoppers based on their behaviors, purchases, and preferences.
We see this all the time with retargeting. Just as Atlas gets better at performing its stunts with the more it learns, dynamic retargeting gets better at predicting the right products, ads and bids at the right time. With the latest innovations, machine learning is even able to change content in real-time – right as a viewer clicks a video and an ad is displayed, for example.
Machines are learning, optimizing, creating, and acting more and more. It’s up to marketers to think carefully about how to harness these innovations to build better customer experiences. While machine learning can help marketers personalize campaigns, it’s still up to marketers to decide and design what those personalized experiences should be. That’s the human touch that machines, for the time being, just don’t have.
