How AI and ML Are Changing Digital Marketing

Before we dive into the ways in which Artificial Intelligence (AI) is changing the nature of digital marketing, let's make sure everyone's on the same page about what AI really is.

Here's Yann Lecun, one of the founders of modern AI (who now leads Facebook's AI efforts), providing a simple explanation of AI:

Mint) trying to build a product for reading text and numbers off of receipts:

the Internet of Things.

Marketers are also using AI and machine learning in incredible ways. There are four specific examples already taking place that show just how versatile and powerful these two technological concepts can be when applied properly.

AI Is Helping Businesses Create Better Content

The major way that AI and machine learning are benefiting brands has to do with the insight it provides which enables them to create better content. Major publications are already using this to take existing data and combine it with keywords to create unique content that attracts visitors to a site. News publications like the BBC, CBS and even The New York Times have been doing this for quite a while. You've probably read an AI-powered story from The New York Times in the past without even realizing it - that's how good this can be.

Things haven't reached the point where you can have AI craft a 1,000-word nuanced opinion piece on a complex topic, but we're probably not too far off. Still, organizations use these tools as a way to offload certain basic content creation duties so actual humans are free to focus on bigger and more important things like OTT content or videos that still need that "real" touch.

An Email Marketing Revolution

AI and machine learning are also benefiting organizations in terms of maximizing their email efforts. Marketers of all types use AI to not only personalize campaigns based on preferences and past user behaviors but also to even automate things like A/B testing (testing two different versions of an email to see which one is better).

You can even use AI to determine when the best time of the week is to reach out to someone. If you have an OTT service, for example, the chances are high that all users have wildly different engagement patterns because that's part of what attracted them to your service in the first place. You can use data collected by their past behavior to see when they're most active and reach out to them accordingly to maximize response rates.

The Art of Predictive Customer Behavior

Many brands are using artificial intelligence to not only better understand past user behaviors, but to also take that information and use it to improve future ones, too. If you can predict the behavior of someone based on things they've done or shown interest towards in the past, you can generally predict what they'll do in the future, too. This gives marketers an opportunity to effortlessly eliminate those people unlikely to convert, thus allowing them to focus all of their attention on those profiles that represent higher quality leads.

The Era of AI-Assisted Web Design

Finally, AI and machine learning have grown sophisticated enough that they're being used to help marketers design better websites based on the real experiences of their past and existing customers.

There are tools like Grid, for example, that take user-provided data from various sources to essentially "tell you" where to put things like images, text or calls-to-action on a landing page.

Let's say you had an mLearning platform and weren't sure from a design perspective where certain elements needed to be in order to create the most accessible services possible for your customers. These applications will analyze how people are interacting with your platform and will remove all guesswork from the equation. You get to design a better service that's naturally more engaging, and you get to do so at a fraction of the price. Everybody wins.

Through AI algorithms, it could also be possible to extend the same gains into the realm of UX as well. You can collect and analyze all sorts of information like location, demographics and even devices being used and use AI to offer content that's more relevant for each user in these categories.

In the end, it's important to understand that AI and machine learning aren't "revolutionizing" marketing from the perspective of replacing human employees. Instead, almost the opposite is true. Marketers are able to offload many menial tasks to these types of tools with incredible efficiency, allowing the actual humans to work smarter, not harder. This, in turn, creates a perfect storm of effective campaigns and very satisfied customers, which is a position that every brand wants to be in.