Picture this: You’re scrolling through Facebook for the tenth time one day when, all of a sudden, you see an ad. It shouldn’t be anything out of the ordinary, but when the ad displays the exact band tee you found yourself googling earlier that morning, you can’t help but wonder, “how does it do that?”
Machine learning is the science of enabling computers to learn without being explicitly programmed. It has been developing for years and in some instances, so subtly, that we didn’t even notice. Social media is a prime example. We want to see ads for new things to buy or do, but we don’t want those ads to be different from our normal habits. More importantly, we certainly don’t want ads to interfere with our scrolling experience. Examples of machine learning created in the past decade can range from something we interact with all the time to things that once seemed unattainable.
Here are four examples of machine learning that you see every day and may not have noticed were even there.
1. Browsing History
Yes, the stories are true: Google always knows what you’re doing. No matter the website or the time of day, everything you browse is seen and remembered. The important thing to remember about Google’s machine learning engine is that it is learning your preferences to better tailor your experience. While the idea that the internet is browsing YOU just as much as you browse IT can be intimidating, Google has determined that users are looking for the most optimized experience possible, and what better way to do so than through machine learning?
Recommendations from retailers you’ve interacted with in the past are just one of the many ways that Google can optimize your experience. Image searches that are combed and classified just for you have been around since Google’s dawn. Every time you open up your YouTube homepage and see a video you may like, it is machine learning at work. Just about everything you do online is a way for companies to get to know you better, and our online interactions are truly all the better because of it.
As marketers, while it may seem obvious, it’s vital to use these search preferences to create better targeted ads. Search data can be one of the best tools in a marketer’s tool belt, and like they always say, “waste not, want not.” Don’t ignore this data, as you may find some of your most interested potential customers have been reading articles about your product or service, just waiting for you to reach out.
2. Siri and Cortana
I live about a half hour away from the Marketo office. Every morning, I stop at the drive-through Starbucks, I grab a bagel from Einstein’s, and then I park my car next-door to the office. The other day, I got in my car, and I noticed that Siri had left a message for me on my home screen. She wanted to let me know that it was going to take me 11 minutes to get to Starbucks and 13 to Einstein’s. Further than that, she was able to tell me how long it would take me to get to the parking lot if I decided to skip breakfast that morning. That might sound terrifying to someone who didn’t know that Siri was learning about them this whole time, but the progress that Siri and Cortana have made in the past few years is incredible.
Siri and Cortana use machine learning to understand how to mimic human interactions. When you say, “Hey Siri,” to your phone, she can identify that phrase under almost any circumstance. As they continue to learn and grow, the two apps will someday be able to understand the simple nuances of just about every language.
Interestingly, Forbes suggests that marketers should be more strategic with how they interact with search engines since the introduction of Siri and Cortana. Brands need to be willing to re-work their keyword strategies more conversationally, adjusting to how someone would communicate with their voice-activated friend. As these programs continue to get “smarter,” marketers need to be more and more creative with their solutions.
3. Facebook and Other Socials
Gone are the days of manually tagging your friends in your social media posts. The tedious task of typing in names to search for the correct friend disappeared when Facebook’s abilities extended into facial recognition. If you go to a baseball game with a group of ten and post a picture, Facebook can scroll through your contacts, match them to the corresponding profile photo, and tag them in the photo without missing a beat. Facial recognition is just one of the amazing ways that social media is using machine learning to improve our experience as users.
Think about even your most simple and basic interactions with social media: memes. Memes sweeping the internet today involves machine learning at its most basic form. When it first began, Botnik studios trained predictive keyboards to learn the typical storyline in a Harry Potter chapter and asked them to write a new one. Since then, the concept has exploded all over social media. The user has a bot watch over 1,000 hours of a movie or a TV show and then write a script of its own, like an episode of Bob Ross’ painting show. While this can be a fun game for us, and something about it feels a bit “off,” it shows you just how powerful machine learning really is and how much smarter computers will get as time goes on.
Marketers should be willing to harness the power of social media, and participating in these fun trends can be a great way to both showcase what your brand does and get people talking. You might not get a whole slew of new customers from participating in meme-ing trends, but you definitely will get some online attention and be labeled as “lit”. That’s internet speak, right?
4. TV and Music
Who hasn’t found themselves aimlessly scrolling through Netflix for a new series to watch? Similar to YouTube, Netflix learns what you enjoy and recommends similar titles, and really knows you better than a lot of companies can claim. If you’re a fan of the popular show The Big Bang Theory, you might find that Netflix would recommend similar sitcoms or even scientific documentaries that you might find interesting. More often than not, the suggestions will be spot-on, and you’ll find yourself immersed in the Netflix binge-watching experience.
Beyond just watching movies, listening to music requires a lot of machine learning to enhance the experience. If I’m listening to the High School Musical soundtrack for the third time in one week, I might find Spotify suggesting other Disney songs that I might like. They might even go as far as creating a playlist for me that includes a daily mix of pop music and musicals. Spotify uses machine learning algorithms to analyze your activity and music taste, curating more specific content, just for you.
Marketers should be aware of what Netflix, Hulu, and Spotify are doing right. Dynamic content suggestions are all about building a “profile” of sorts for the customer. Different versions of a site that change depending on who’s viewing the site at any given time are a great way to keep your customer at the center of everything you do. Getting to know your customer is the best thing you can do for them and they will thank you for it in the long run.
Before you panic, leave the internet forever, and wipe your hard-drive, you should remember what amazing advances in technology machine learning has given us and will give us in the future. We probably will see more precise recommendations online, leading to fewer inaccuracies and a more immersive experience. We definitely will see computers getting better at talking like humans, able to communicate seamlessly with us. Even the most complex and crazy of technologies like self-driving cars are powered by machine learning, so as we move into the future, the experience is only going to get more and more exciting.
How do you feel when you see an advertisement tailored specifically to you? How has machine learning enhanced your online experience? Let us know in the comments!