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What is Machine Learning?

If you’re like most people, “machine learning” probably sounds like another indistinct marketing buzzword. But for those of us in the know, machine learning is one of the most exciting things to happen to digital advertising. We’re here to answer your burning questions about machine learning so you can get excited for the next digital advertising revolution.

The Basics

Simply put, machine learning is a term for a new type of system that gives computers the ability to learn new things, understand data, and draw conclusions. Machine learning systems consist of a special type of artificial intelligence, a series of machine learning algorithms, and the engineers who ensure that everything is working correctly. 

Because machine learning systems combine so many ways to examine a set of data, they’re capable of solving problems and making predictions about future outcomes. Machine learning systems can “teach” themselves to get better in a certain discipline over time (like ad placement), and they get “smarter” as they process more data over time. 

For example, some larger brokerages have started to use machine learning algorithms to run detailed analyses of demographic information, allowing for more accurate CMAs than ever before. Using the mountains of data available, some brokerages will even use these systems to assist in the valuation of a home: Machines may not be able to walkthrough a home, but they can parse through thousands of similar listings in the blink of an eye, selecting an appropriate price based on data-supported insights.

Making machines “smarter” may sound terrifying, but it’s actually leading to breakthroughs in science, medicine, marketing, and pretty much any other field you can dream of. Machine learning systems can process huge amounts of information faster than human beings ever could, allowing breakthroughs to happen with increasing frequency.

So… what does that mean for me?

If you’re reading this, you want to build your digital marketing capabilities. Technology has substantially lowered the barrier to entry when it comes to advertising, and machine learning has already started making waves in the world of digital advertising. If you want to keep up with the industry norms, educating yourself about how different advertising platforms use machine learning can help you decide where to spend your advertising dollars to get the most bang for your buck.

Facebook

Facebook uses machine learning in a huge variety of different ways, but the one that affects you as an agent the most is ad placement.

If you’ve ever run a Facebook ad campaign, you’re familiar with “campaign objectives.” There’s nothing on the page to indicate how your choice of objective will impact your ad placement, but behind the scenes, machine learning systems are figuring out how to present your ads to the right people. As one of the world’s largest advertisers, Facebook has access to a nearly incomprehensible amount of data about ads, ad placements, and ad creative, allowing their systems to take on more and more complex tasks over time.

Facebook’s back-end systems differentiate between “Traffic” and “Brand Awareness” goals. Using the huge amount of data that passes through Facebook’s Ad Manager every single day, your ads are then shown to users who are most qualified based on the selected objective.

For example, if you create a campaign with “Traffic” as the objective, Facebook’s machine learning systems will present your ad(s) to users who are likely to click through to your website. Not only does this help you reach your campaign goal: It helps make Facebook smarter for future campaigns.

On the other hand, if you select the “Brand Awareness” objective, Facebook will focus on users who haven’t been exposed to your brand before. By not showing your ad to people who already know you, Facebook helps your advertising budget go further.

Google

The world’s largest search engine is also one of the world’s largest advertising platforms, and with all that visibility comes a huge amount of pressure to keep pace with the competition. Google is outspoken about its dedication to advertising technology, and has even devoted an entire business unit to the study and development of advanced machine learning systems and applications.

At the highest possible level, Google uses machine learning systems to position search results based on a user’s query. By spending years combing through billions of searches, Google has tailored which results to show you based on your search. These measures of relevancy also apply to text-based ads, with Google adjusting which ads you see based on your behavior.

A screenshot of a Google SERP.
On this Search Engine Results Page (SERP) for “pet insurance”, Google displays 4 search ads and 2 organic results.  Source: https://www.bigfootprintdigital.com/blog/google-serp-changes-search-marketing-game-changer/

Machine learning also controls placement for Google Display Network ads. These visually rich ads appear on countless partnering websites across the internet, but Google’s machine learning systems help make sure that the right people are seeing the right ads, regardless of where they are on the web.

A sample Google Display ad on the right-hand side of a website mockup. Source: https://searchengineland.com/google-debuts-post-ads-lets-brands-turn-google-content-into-ads-on-gdn-179401

Google has also put their technology to work on YouTube. Sure, video ads on YouTube are placed using machine learning, but there are other, more mundane ways in which Google takes advantage of their tech. For example, have you ever stopped and thought about how YouTube “decides” which videos to show you in the “Suggested Videos” sidebar?

A screenshot of the machine learning-assisted "suggested videos" part of YouTube's site.
YouTube will show you suggested videos before, during, and after you watch a piece of content. Source: https://www.404techsupport.com/2014/10/19/how-disable-youtubes-new-autoplay-suggested-videos/

You guessed it. By analyzing millions of hours of watch history from users all over the world, Google’s machine learning systems allow YouTube to serve content that is directly related to the video you’re currently watching.

What now?

So – you’ve learned a little bit more about machine learning. With this exciting new technology, you’re taking the guesswork out of the most complicated part of the advertising process and letting technology make more sophisticated decisions for you.

As the world of advertising moves into the future, it’s important for you to understand how digital marketing platforms use technology. After all, more advanced advertising technology means that your advertising budget goes further, and your ads will reach a more relevant and qualified audience. And with the consistent advances we’ve seen so far, machine learning-assisted advertising will only get more and more efficient. 

Because Facebook and Google are constantly “learning” while they serve ads, running your ads on those platforms will set you up for success (and give you a leg up over your less-savvy competition).

Interested in discovering more about the technical side of machine learning, artificial intelligence, and the ways they can affect you? The internet is rife with in-depth resources that can help you further your understanding.

If you’re a more hands-off type of person, then just sit back, relax, and enjoy the advancement of this incredible technology.

By The Disclosure
Your go-to for all things real estate marketing.

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