Strategy Consulting

9 Applications of Artificial Intelligence in Digital Marketing that will revolutionize your business

We’ve already posted articles on this topic before, like The Most Surprising Applications of Artificial Intelligence That You’ve Never Even Thought Of and 10 Artificial Intelligence Technologies That’ll Rule 2018. So now, the question we’re asking marketers is: How will artificial intelligence (AI) affect digital marketing in 2018?

A few years ago, marketers were somewhat reluctant to incorporate artificial intelligence (AI) in their digital marketing strategies. But this year they’ve gained a lot more confidence in using AI since its ambiguity has been reduced with respect to the results it can provide. These intelligent tools keep evolving more and more and are even reaching a point in which they are able to surpass humans in certain aspects like we’re about to see.

In a survey taken by over 1,600 professionals dedicated to marketing, 61% of those surveyed (without considering the size of their company) mentioned that both artificial intelligence and machine learning will be the most important data initiatives next year (source: MeMSQL).

Another survey by Salesforce indicated that 51% of marketers are already using AI, and 27% more are even planning on incorporating this technology in 2019. This represents the highest expected year-after-year growth of all emerging technologies that marketers are considering adopting next year, surpassing even the Internet of Things (IoT) and marketing automatization.

And, while the amount of information on potential consumers grows, computer sciences related to AI (like machine learning, deep learning and natural language processing [NPL]), will be of utmost importance when making data-based decisions.

We’ve carefully analyzed which AI applications are already revolutionizing the digital market, and you’ll definitely see more than one that probably never even crossed your mind…


What? A machine that writes by itself and creates content from scratch? There’s no way! But, I have news for you…

There is a way! And even though AI still can’t write its own political opinion for a newspaper column or a blog post on the best and most practical advice for a specific industry, there are certain areas in which content created by AI can be useful and help attract visitors to your website. It can help you save lots of time and resources. For example, AI can already write reports and news based on data and information.

Intelligent tools like Wordsmith, Articoolo, and Quill are already being used by the Associated Press and Forbes to create news, which leads to clicks on their websites. Using templates and fill-in-the-blanks to enter data and keywords can create unique content that gives the impression a human wrote it. So, you’ve probably read content that was generated by AI since BBC, CBS, the New York Times and Reuters are also implementing this technology.

In fact, hundreds of articles in the Washington Post are already credited with artificial intelligence technology, Heliograf.


AI is not only able to generate content; it can also curate it. Content curation by artificial intelligence will make it possible to better connect with visitors on certain websites and show them more relevant content.

This technology is commonly used to make personalized content recommendations that the user may find interesting, such as the typical, “people who buy X also buy Y,” like we constantly see on Amazon.

Netflix’s recommendation system can also give you suggestions for movies and TV shows you might find interesting. And it’s pretty accurate!

Now, the question is: How can you benefit from it?

Imagine showing each of your blog’s visitors articles that are more relevant to them, based on posts and topics they’ve already looked at on your blog. They’d definitely spend more time on it.


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Brands are using the power of AI to personalize email marketing campaigns based on preferences and user behaviors. This makes it possible to better connect with them and, with a bit of luck, turn them into clients.

Machine learning or automatic learning can analyze millions of data about the consumer to then determine the best times and days of the week to contact the user, the recommended frequency, the content that catches their attention the most, and which email subjects and titles generate more clicks. Wouldn’t you love to know all about this so you can launch the main metrics of your digital marketing campaigns?

A/B tests take time and can have a certain margin of error. So, in this sense, AI becomes your best friend in personalizing email content for each subscriber.

BoomtrainPhrasee, and Persado are some tools that AI applies to email marketing. And according to Phrasee, its generation of email subject lines surpasses those of a human by over 95%. Persado even says that its cognitive content exceeds what a human could do 100% of the time.


Digital advertising is, without a doubt, the area of digital marketing that’s most successfully adopted artificial intelligence.

For example, Facebook and Google ad platforms already use machine learning and artificial intelligence to find people more prone to making the advertiser’s desired action. To achieve this, they analyze the user’s information, like their interests, demographics, and other aspects to learn and detect the best audience for their brand.

Google AdWords already has an automatic auction-based system that lets advertisers pay the lowest possible cost per conversion.

There’re also already platforms that incorporate AI and the analysis of big data candidates in their processes… but wait until we tell you about Adext.


Adext is an Audience Management as a Service (AMaaS) that uses deep, transfer and machine learning to automate the handling and optimization of your ads on platforms like Google AdWords and Facebook Ads. This means that, in addition to testing different audiences on each ad (up to 480 everyday!) to detect the one most likely to make the desired action or conversion, it’s able to identify and learn which platforms are most profitable and then channel the investment toward them.

Its intelligent algorithms adjust and optimize budgets every hour so that the advertiser can obtain the highest sustained conversion rate (which is guaranteed under contract, or else the software is free) and on average, its increasing ads performance by 83% in just 10 days!

If you want to take advantage of its benefits and enjoy the new era of digital advertising, you can start by reading this step by step guide. Connecting Adext AI to your AdWords and Facebook Ads accounts take around 5 minutes.


The way users perform online searches has changed. So, now we must ask ourselves how this will affect the way in which marketers create and optimize their web content.

There have been two big advances in artificial intelligence that revolutionized Internet searches and search engine optimization (SEO): voice search and Google’s algorithm, RankBrain.

Innovations like Amazon Echo, Google Home, Apple’s Siri, and Microsoft’s Cortana make it easy for people to perform searches by just pressing a button or saying a voice command.

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In its blog, Google revealed that around 70% of the searches Google Assistant receives are in natural, conversational language, and do not use the typical key works that you would type out in a classic Google search.

Google’s machine learning algorithm, RankBrain, was created to get much more relevant search results. It interprets the user’s voice searches and, using the power of AI, provides the user with the best results according to what it interpreted from the user’s language and context.

Voice searches require marketers to adapt their content so that it’s closer to the way a user would verbally express themselves. So, in this sense, those famous long-tail keywords will be replaced with more conversational keywords, based on the way the user would say something or do a voice search. A brand that truly knows how to benefit from voice searches will be able to considerably increase their organic traffic.


If you thought a good website couldn’t exist without the help of a programmer and designer… well, that’s a thing of the past.

Today, there are already applications, like Grid, that use artificial intelligence to design a website based on user-provided information (like images, text, calls-to-action, etc.). They can make the website look professional in much less time and at an unbeatable price.


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Through intelligent algorithms, it’s possible to personalize an experience on a website. After analyzing thousands of data on a single user (including location, demographics, devices, interaction with the site, etc.), AI can display offers and content that are more appropriate for each user type.

A 2017 Evergage survey on personalization in real time showed that 33% of the marketers surveyed used AI to provide personalized web experiences. And, when they were asked about the benefits of personalization driven by AI, 63% responded that it increased conversion rates and improved the consumer’s experience.

It’s true: a good user experience is what keeps an audience browsing a site and, the more time they spend on it, the higher the probability of a conversion.

In this sense, one of the many possibilities that AI offers to make the user experience more user-friendly are chatbots, which we’ll talk about now.


Many brands have started to communicate with their prospects through messenger applications like WhatsApp, Facebook Messenger, and Slack. They’re fast since consumers are already using these tools to chat with friends and colleagues and, let’s get real, no one likes to wait for a response on the phone.

Chatbots are making the process of automating responses to potential buyers’ frequently asked questions even easier by providing them with a way to search for the product or service they’re looking for.

A good indicator of a chatbot powered by AI is its ability to answer open questions. These bots use natural learning processing and machine learning to find the correct response.

Chatbots also have many other advantages. They can serve clients 24/7 and retain their data. They’re friendly and never lose their patience. Customers may get angry, but the bot always treats them well. Chatbots can respond to several requests from different customers at the same time, so waiting times will no longer be a problem.

Sephora, for example, is a brand that uses a chatbot to give beauty advice to its users and offer them the best cosmetic products according to their needs. Through its application or website, Sephora Visual Artist lets its potential clients “test” cosmetic products like lipsticks, eyeshadows, and highlighting pallets. Visual Artist is able to identify facial features and then use augmented reality to apply the selected product to the user’s photograph. It can even automatically apply an eyeshadow suggestion based on the skin tone of the consumer!

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Don’t you want a chatbot to become your best sales rep?

The good news is that you don’t need to have a huge budget to create a chatbot. You can use Facebook bot tools, like bot, to train bots in example conversations and make them continually learn from their user interactions.


Predictive analysis is just the use of data, statistical algorithms, and machine learning techniques to identify the probability of future conclusions based on data history.

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Predictive models can be applied in several areas, and marketing is no exception. These models make it possible to predict the probability of a specific prospect becoming a client. They can also predict other aspects, like the quoted price necessary to make a conversion, or which clients are more prone to making more than one purchase.

The key here is to remember that predictive models will only be as good as the data you provide while creating them. So, if there are mistakes in your data, or there’s a high level of randomness, it won’t be able to make correct or accurate predictions.

This AI application will transform marketers from reactive to proactive planners, thanks to the data that serves as a forward-thinking element or guide to make the correct decisions.

An example of how this discipline is applied in digital marketing is the ranking of prospects or lead scoring. Models generated by machine learning can be trained to rank prospects or leads based on certain criteria that the sales team defines as “qualified purchasers.” This way, the sales team won’t lose any more time on leads that will never convert and can focus on those that will. This, in addition to contributing to increasing sales, means saving considerable time and resources.