AI Marketing: How to use AI for marketing

Artificial intelligence (AI) isn’t exactly a new idea or even a new technology. Still, it’s come along in leaps and bounds in recent years, and the software and hardware are finally starting to catch up with the theory. Suddenly, all of those science fiction books are starting to look a lot more realistic. That’s one of the reasons why we previously called 2019 the year of AI.

But Isaac Asimov and the like didn’t really look at how AI would affect marketing, and even if they had, they probably wouldn’t have been able to predict it. It turns out that artificial intelligence could well be the next must-have tool for modern marketers, and there’s a good reason for that.

Here are just a few of the main ways that you can take advantage of AI for modern marketing.

AI Marketing: How to use AI for marketing

Before we jump in and take a look at how to use AI for marketing, we should first investigate the different types of AI and understand how they’re typically used. Let’s start with artificial intelligence itself, which refers to any computer algorithm or piece of software designed to mimic human intelligence.

Machine learning is artificial intelligence’s big brother, and the term is used to refer to an algorithm specifically designed to “teach” itself. For example, instead of manually defining what a cat looks like and asking an algorithm to identify pictures of cats based on a set of pre-determined inputs in the form of AI training data , a machine learning algorithm would scan hundreds of thousands of images of cats and determine for itself what a cat looks like.

These two technologies both rely on big data to function, and they’re also at the heart of other emerging new technologies. For example, it’s not uncommon for AI and machine learning to power AR or VR simulations to make them more realistic. They’re also both applied to natural language processing, which is when algorithms are used to understand better the actual language that we speak in.

Let’s take a look at how each of those technologies is being used for marketing.

Artificial Intelligence

AI is mostly used to process huge amounts of data at speeds that no human being could hope to compete with. So when it’s applied to marketing, it does a great job of handling huge client bases and powering CRM systems like Salesforce, which are designed to help you to more accurately understand who your leads are and what they are doing.

It’s also great at powering advanced split tests for highly trafficked websites. Also known as A/B tests and multivariate tests, the idea is to trial small changes to a web page to improve conversion rates and dwell times and to decrease bounce rates and cart abandonments. Instead of requiring a human to design different variants, AI software can automatically create and test hundreds or thousands of different options.

AI is also often used to power automated bidding and programmatic advertising software, again because it can make rapid calculations and manage campaigns effectively on your behalf. It still needs human oversight, of course, as most technology does, and that’s good news for marketers because it means we can keep our jobs. At the moment – and, likely, in the future – the best option is a mixture of both humans and machines.

Machine Learning

Machine learning is arguably the most influential technology that AI has enabled, mostly because if machines can “learn” and to teach themselves to understand better the data that they’ve been provided with. They can then make suggestions for humans that we might not have come across before. They can even act automatically on our behalf, often outperforming humans because of their ability to crunch numbers at a rapid speed and to take action far quicker than a human could.

It’s machine learning that powers Netflix and Free Hotstar. It does this by crunching the big data provided from the viewing patterns of every one of its users and then making super personalized suggestions about what you should watch next based upon what other, similar people have enjoyed. As you can tell from the site’s popularity, it’s an approach that works.

For marketers, a similar concept can be applied within your CRM system. For example, why not serve up content to website visitors who have received a high engagement from other similar visitors? The good news is that you don’t need to be a software analyst or a computer scientist to take advantage of the opportunities afforded by machine learning because it’s increasingly being built into CRM systems by default.

Natural Language Processing

Natural language processing is relevant to modern marketers because it’s the tech that powers Amazon’s Alexa and other virtual assistants. It helps machines to understand full human sentences as opposed to our traditional method of searching, which relied on keywords. Instead of “pizza delivered now” it’s, “Alexa, where’s the nearest open pizza place?”

The good news is that you probably won’t need to interface with natural language processing tech, at least in the foreseeable future. Instead, it sits beneath the metaphorical bonnet, powering the tools that consumers are using to shop and for leisure. Expect to spend more and more time in the future working on the voice equivalent of search engine optimization, ensuring that your products and services are easy to find by people who are interacting with their voice devices.


Augmented reality (AR) and virtual reality (VR) might at first seem as though they have more to offer to gamers than to digital marketers and that they have little to do with artificial intelligence, but hear us out. AI is increasingly being used to power AR and VR software to increase its realism, and these types of games are an untapped goldmine for advertisers.

For example, imagine being able to run advertisements that are shown on billboards in-game and which are based on what we know of those players’ interests. It could open up an entirely new type of advertising that hasn’t been seen since search ads first came along. We might not be quite there yet, but we’re also not far off, and there will be rewards to be had for being an early adopter.

What else?

Because AI and machine learning algorithms get more and more powerful as they’re given access to more and more data, you should make it a priority to start collecting data today even if you have no immediate plans to use AI.

It’s also typically the larger companies that can benefit the most from AI, partly because they’re the ones with all the data and partly because they have bigger budgets for innovation. The good news is that even if you’re an SME, you can start to take advantage of the technologies that we’ve talked about today by looking for SaaS providers who work the technology into the platforms they offer.

The main thing to remember is that artificial intelligence is here to stay. So if you want to remain relevant in our increasingly competitive world, you’ll need to make sure that you’re making it a part of your strategy. Don’t see it as a threat but rather as an opportunity, and if you can see an opportunity to use AI for boosting your marketing team’s performance, don’t hesitate to take it.


Now that you know a few of the ways that modern marketers can take advantage of artificial intelligence, it’s over to you to make sure that you’re in line with best practices and that you’re taking advantage of AI tech where appropriate to help your business to be the best it can possibly be.

It’s also vital for you to remember that AI isn’t some sort of magic bullet. Sure, taking advantage of it can help to give you a leg up on the competition, but it isn’t going to turn your business around overnight. Instead, it’s a long-term ally that you can rely on not just in your marketing department but across your whole business.

Have you used AI for marketing purposes at your business? If so, how have you got on? And if not, will you be trying it out in the future? Be sure to let us know with a comment.

Author Bio:

From 2017 as a CTO at Zfort Group, Andrew concentrates on growing the company into the areas of modern technologies like Artificial Intelligence, BigData, and IoT. Being a CTO Andrew doesn’t give up programming himself because it is critical for some of the projects Andrew curates as a CTO.