Gartner predicts AI software will reach $62 billion in 2022. Artificial intelligence can be used in many different contexts, and that’s part of what makes it so difficult to define. Is it just a buzzword? Is it a technology that can be harnessed for practical purposes? 🚧

In this article, we’ll focus on artificial intelligence as used in digital marketing. What does it mean? How can it help you achieve your business goals? Let’s find out.


What Is Artificial Intelligence?

According to Investopedia, “artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.”

Therefore, AI allows machines to learn different tasks just like a human would do, and improve their responses due to external factors and feedback.

AI has been used almost anywhere, from medical applications to design, from heavy machinery to cars. It is not surprising that marketing benefits from AI too. But what does AI marketing mean?


What Is AI Marketing?

Artificial intelligence marketing takes automation to the next level. These applications bring in a lot of value and can improve relevant KPIs (key performance indicators) such as return on investment, monthly recurring revenue, lifetime value… By using artificial intelligence, these apps learn from each interaction with a customer and each action taken. 💸

This is therefore a branch of digital marketing that is growing and becoming more prevalent. These are some common applications of AI in marketing.


Components of AI In Marketing

A few components make up the AI marketing toolset. These include different types of technology that allow artificial intelligence to evolve constantly and learn new “tricks” as a human would do. Let’s go through a few.

1. Machine Learning

One of the pillars of machine learning is machine learning. Algorithms created to perform certain tasks gather information from past successes and failures in order to improve future results. The algorithm, therefore, learns and applies what it has learned in new contexts.

machine learning

2. Big Data and Analytics

Other than machine learning, another great advantage of AI marketing is its capability to gather and analyze large amounts of data very quickly. These analytics can be used for machine learning but also to guide decision-making from marketers and other employees that work with sales and support.

3. AI Platform Solutions

Applications fueled by artificial intelligence give marketers a platform to focus their efforts on, that analyzes their data for learning purposes and can command different operations on its own.

These platforms are like a control center for all current tasks that are being automated. Every adjustment is done automatically so the platform user has nothing to worry about.


Common Applications

1. Data Insights

Analysing data from your business and collecting insights from it, is at the same time essential and difficult. Artificial intelligence allows you to save time and money by detecting behavioral patterns in customers. 🧑 These patterns can then be used to automatically create user clusters (same as segments and tags on Platformly). Segments of users are then used to create tailored messages that match behavior, engagement, purchase record, and other factors.

2. Personalization

Personalization goes hand in hand with segmenting your audience, but is not limited to that. Common use cases include chatbots that respond to customer messages, dynamic websites, product recommendations that adapt to the user, marketing campaigns that learn from previous engagement and behavior…

3. Campaign Recommendations

Marketers can benefit a lot from AI marketing. Particularly with campaign recommendations. When creating an ad campaign on a platform like Meta or Twitter, the platform bases itself on previous campaigns from you and other advertisers from your niche to give you content suggestions, segmentation recommendations such as specific demographics, audience size, and much more.

This goes as far as to even recommend images from your library that are more likely to perform well. Also, you can get suggestions on how to improve results, such as switching off low-performance ad groups, and investing more in high-performance ads. 🗒️

4. Scheduling

Sometimes, marketers are not sure of the best time of day or day of the week to publish new content and to engage with customers and leads. AI marketing records the times and dates with the best performance so that you are able to schedule your blog posts, Facebook posts, or even tweets, at the right day and the right time.

This is made possible by artificial intelligence in your publishing software. By recording performance and engagement metrics on each post and detecting patterns, AI allows you to tap into this data in order to time your content publication perfectly. ⏲️


So, it is clear that artificial intelligence is a goldmine for marketing professionals with its capabilities and its applications. But it isn’t always smooth sailing on these platforms. 🌊

With such powerful tools, there come great challenges. And that’s what we’ll talk about in the next section.

deepmind artificial intelligence


AI Marketing Challenges


As with every tool, your team members need the training to work with an AI-powered platform.

The issue with AI Marketing tools is that they can reach a high level of complexity that makes them difficult to manage. Adequate training is therefore essential if you want to harness the power of artificial intelligence for your marketing strategy and tasks.

Data Quality

How can you make sure the recommendations of your AI tool are accurate? You make sure of data quality. This ties together with the need for training. Feed your AI tool with accurate data, and the results should follow. Ensure data quality, and you’ll be able to trust the recommendations your AI helper pushes out. 💻


This has always been a common issue online, and artificial intelligence is another branch of marketing that is affected by privacy concerns.

Data safety can be a big problem if you have a data leak of any kind, especially regarding sensitive customer information. When choosing an AI platform for marketing, make sure that platform has data protection measures in place.

Also, make sure employees know how to act in order to avoid privacy mishaps, by training them to direct these concerns with practical measures and good communication with customers. 🛒

Measuring Performance

When it comes to performance, ROI (return on investment), MRR (monthly recurring revenue) and similar metrics are easy to measure and justify. But when it comes to measuring customer satisfaction and experience, it’s not as simple to say that the results came from this or that.

This makes it quite difficult to justify using AI in marketing, especially when it comes to companies with small budgets.

However, happy customers are returning customers. Not all KPIs are simple to measure and a lot of factors can contribute to increasing sales and profit.

Deployment Best Practices

Setting up a new SaaS tool for your business is a very important task. The way you set up your user profiles, company accounts, features to include, and so on will help shape the way your business performs.

Deployment needs to follow an evaluation process on your part: what are your needs and requirements for an artificial intelligence tool? How can this technology benefit you?

Asking yourself these questions will help you set up your AI marketing strategy for better results. 💰

deepmind artificial intelligence

Constant Changes

Another common issue that affects digital marketing is the constantly changing nature of this business and the technologies that evolve with it.

This requires you to stay up to date. Look for training and webinars from your software vendor, talk to experts on Twitter, and never start learning no matter what.


Two Final Pieces Of Advice

Establish Goals

In order to know how your campaigns are performing, you need to know how to measure results. Know what you want to improve, what your key weaknesses are, and where you need to work a bit harder.

Have set goals before you choose your elected AI app. These goals, as mentioned, will help you decide on the best tool and how to proceed further. 🎯

Data Science Talent

Depending on the size of your marketing team, you might have considered acquiring talent for data science and analytics.

However, here’s the thing: data is priceless, but not using it to its full potential is very costly. If you have the chance to hire someone that will decipher your data for you, by all means, go for it. 📈

Wrapping Up

There’s a lot to be said about artificial intelligence in marketing, how it can be used and why you should embrace this trend. But here’s what you need to know: AI is not a fad and is not going to go away.

We covered mostly the main topics for artificial intelligence marketing here, but stay tuned for more in-depth guides about marketing automation!

About Author

Deeply passionate about writing, copy, and social media. Digital Marketing Assistant at Platformly.


Engage and lead your audience through every step of the customer lifecycle - the next-gen marketing automation platform

Learn More