6 simple steps to making AI part of your marketing strategy today

Artificial intelligence has reached its tipping point for marketing. The technology has progressed to a point of offering businesses a distinct competitive advantage and is improving so rapidly that we can see a future where AI adoption is critical to a company’s success. 

Think of it like this, the forward-thinking retailers who jumped on the ecommerce boom early benefited from testing, learning, and generating data that helped shape their online offering before Amazon, and then COVID-19, transformed the way we shop forever.

Artificial Intelligence is no different. It is being adopted by forward-thinking marketers today and with every data point acquired, the AI is getting smarter and making more accurate predictions while the employees at your business are learning how to make the most of this incredible technology. We can’t stress this enough — the businesses that don’t focus on AI now will, best case, be playing catch-up when the adoption rate starts to soar. Worst case, they will be outrun by competitors and will cease to exist.

In this ultimate guide, we’ll explain what artificial intelligence marketing actually is, how it is being applied to marketing today, what we can expect as the technology evolves, and some simple ways you can jump in and start embracing AI today. 

AI marketing definition

AI marketing uses artificial intelligence technologies to analyze data, predict an audience’s behavior based on observing actions or societal and economic trends, and automate marketing campaigns, customer support responses, digital ad buying, lead scoring, and more.

Many marketers may be using AI without even realizing it, using common tools like programmatic ad buying or social media monitoring.  This is really just the beginning, the world of marketing AI is expanding rapidly and the future is bright. 

AI marketing statistics

If AI still feels like the stuff of Blade Runner and The Jetsons, these statistics around adoption, global market growth, and the benefits businesses are already seeing will prove otherwise. 

1. Private investment in AI totaled $93.5 billion in 2021, more than double the total private investment in 2020 (Stanford HAI AI Index Report 2021) 

2. The global AI market is predicted to reach $126 billion by 2025 (Statista) 

3. By 2030, AI could contribute up to $15.7 trillion to the global economy (PwC) 

   1. $6.6 trillion of this is likely to come from increased productivity

   2. $9.1 trillion is likely to come from consumption-side effects 

4. 52% of companies accelerated their AI adoption plans because of the COVID-19 pandemic (PwC) 

5. 25% of companies have processes fully enabled by AI with widespread adoption (PwC)

6. 21% of companies have a few promising proofs of concept and are looking to scale AI (PwC)

7. 33% have started implementing limited AI use cases (PwC) 

8. Between 2018 and 2025, the Asia-Pacific region will experience the highest compound annual growth rate (Mordor Intelligence) 

9. In 2022, companies are expected to have an average of 35 AI projects in place (Gartner)

10. 86% of CEOs say AI is mainstream technology in their office in 2021 (PwC) 

11. 72% of business leaders feel positive about the role AI will play in the future (The AI Journal) 

12. 74% of business leaders believe AI will make business processes more efficient (The AI Journal)

13. 55% of business leaders believe AI will help create new business models

14. 54% believe AI will enable the creation of new products and services

15. 75% of organizations could be out of business if they fail to scale artificial intelligence (Accenture) 

16. 84% of C-Level executives believe they won’t achieve their business strategy without scaling AI, yet only 16% have made the shift from mere experimentation to creating an organization powered by robust AI capabilities (Accenture) 

17. 64% of executives say that implementing AI has increased productivity (PwC) 

18. 86% of executives say that creating better customer experiences is a direct benefit of implementing AI (PwC) 

19. 75% of executives say implementing AI improves decision making (PwC)

The four types of AI and how they are applied 

There are four types of artificial intelligence, and they range from the very basic to the very sophisticated. Some are in use right now, and it’s likely you interact with them every single day (especially if you’re an Ortto customer). Others are not yet available, but they’re on the way. 

Here, we’ll break down the four main types of AI and how they are applied in programs today so that you can start to get a sense of where we are, and where we’re headed. 

Reactive AI

This is the most basic type of artificial intelligence and has applications in many of the programs we use each and every day. Reactive AI responds to an input of data, but does not have a memory. This means reactive AI is not able to learn actions or conceive of the past or the future.

Reactive AI is used in many of the applications we use in our day-to-day lives, including spam filters for our email inboxes, recommendation engines like Spotify and Netflix, and IBM’s Deep Blue machine which famously beat chess Grandmaster Garry Kasparov in 1997.

While it is a limited form of AI, it represents a great stride forward in the history of AI development and provided a stepping stone for every form that follows.

Limited memory AI

Building on reactive AI, limited memory AI has, as the name suggests, a limited memory. This means it can build on experiential knowledge by observing actions or data and use this historical information in combination with pre-programmed information to make predictions.

Many chatbots rely on limited memory AI, using the data gained from conversations with customers alongside pre-programmed responses to have more productive conversations with customers. Autonomous vehicles, or self-driving cars, use limited memory AI to observe their environment, other vehicles, people, or objects in their line of vision. They use this information to detect changes and adjust as necessary.

Limited memory AI is the most widely-used kind of AI today, with the next step in intelligence still hovering on the horizon.

Theory of mind AI

Let’s take Chatbots as an example. While limited memory AI provides customers with a good experience, the bot lacks the emotional intelligence required to make a customer experience great.

Theory of mind AI will change all that, allowing us to hold a meaningful conversation with a machine that can understand emotions and adjust its behavior according to those emotions. Theory of mind AI will have a longer memory and decision-making capabilities, meaning it can act more independently, requiring less human intervention.

Already we have seen some elements of theory of mind AI in existence. The robot Kismet, developed by Professor Cynthia Breazeal in 2010, could recognize and even replicate facial expressions, a crucial part of how humans read emotions.

Sophia, a humanoid robot created by Hanson Robotics in 2016, took this one step further with the ability to not just replicate facial expressions, but actually respond to interactions with humans with appropriate facial expressions.

Both bots represent great strides towards theory of mind AI which will see robots becoming a part of human society.

Self-aware AI

Now we’ve reached the most advanced form of artificial intelligence, and one that we have not developed any kind of hardware or algorithms to support. Self-aware AI is when machines will have their own emotions and will therefore have desires and needs just like any human.

Machines with this AI will have a level of consciousness and intelligence similar to human beings. Experts predict that AI could progress to this point and pass a consciousness test in 2060.

While 40 years may seem far away, there are many smaller strides that could happen between theory-of-mind AI and self-aware AI, each of which will change the way we work and open the door to new ways of marketing and doing business. 

How to get started with AI marketing 

In case we haven’t stressed this enough yet — the time is now to jump on board with AI marketing. The technology is evolving rapidly and the businesses that thrive in the future will be those that have embraced this new technology early on. There are two key reasons embracing AI should be a priority for your marketing department: 

1. Unifying and organizing data
   In a customer data platform that is underpinned with AI, like Ortto, data is crucial. That’s just part of why the first thing you do in the platform is unify all of your data sources — customer, behavioral, transactional, and activity-based — to get a single view of the customer journey. With data unified, the AI has a full picture and can do its job.
   

2. Learning to work with AI
   Like anything new, learning to make the most of AI can take some time, and companies that start learning now will be lightyears ahead of their competitors five years down the track when the technology has improved. In a platform like Ortto, you’ll get immediate benefits from features like the subject line recommendation engine, and long-term benefits from the insights Ortto AI pulls from your data and your marketing team’s ability to ask the AI the right questions. 
   With each new piece of data, test, and experience, the AI will become more embedded in your business, giving you a huge leg-up on the competition. 

But… how?! Here we’ll outline the four types of marketing-specific AI that exist today, and how they can be applied. 

The four kinds of marketing AI

Harvard Business Review categorized the four kinds of marketing AI according to their intelligence level and structure. If you’re just getting started with AI, this simple categorization can help your business take a crawl, walk, run approach, allowing you and your team to acquire AI skills and amass the necessary data in a sustainable way. 

Each of these four types is being used in various marketing tools today, including: 

• Stand-alone task automation apps

  • Chatbots like Facebook Messenger bots

  • Social media automation 

• Integrated task-automation apps

  • Inbound customer call routing

  • CDP-linked marketing automation systems 

• Integrated machine-learning apps

  • Data analysis tools 

  • Predictive sales-lead scoring 

  • Personalization including product and content recommendations or special offers

  • Programmatic digital ad buying

• Stand-alone machine learning apps

  • Branded apps like Olay Skin Advisor and Vee24 chatbot

6 simple steps to making AI part of your marketing strategy today 

If you want to start using AI in your marketing, but don’t know where to start, these six steps will help you utilize the AI that is available today, and prepare for what’s to come in the future. 

Step One: Connect your apps, channels and platforms 

When it comes to unlocking AI's real potential in a world of channel-agnostic customer journeys, APIs are essential.

APIs open the gates between software systems, apps, channels, and platforms. With these "gates" open, online channels and data sets become a nervous system for AI to crawl through — analyzing and collecting information from every customer.

This neural network of apps is key to consolidating data across every available data silo. It's something that humans could never manage alone — there's just too much information to process.

When AI can seamlessly access data from API-connected channels, it can organize it, streamline it, and present it in a way that reduces the cognitive load on marketing teams. The result?

The management of high-volume, multi-channel messaging at scale is not only humanly possible, it's better than ever before. And the best framework to facilitate this is a CDP that can unify data, segment audiences, measure success and automate marketing across the entire customer journey. This is exactly what Ortto was built to do. 

Software like this allows AI to:

• Use API technology more freely

• Connect data silos across modern and legacy applications and systems

• Democratize data availability

• Provide actionable insights into next-best actions

• Create automated, consumer-facing processes (such as product ordering via virtual assistant)

• Enhance the customer journey with dynamic, personalized variables on a 1:1 level

• Identify customers on any channel, device, or app

Instead of focusing on managing enormous datasets, human marketers can shift their focus to making good business decisions.

Step two: Begin automated marketing across the customer journey 

As the world becomes more and more connected, customers are continuing to be influenced by marketing on multiple channels.  

To keep up with the modern digital marketplace, marketing teams need to understand how customer experiences are converging across multi-channel journeys. This kind of attribution is ridiculously complicated for a regular human, but for an API-connected AI system, things are different.

With an AI-powered platform like Ortto, you can get a single view of your customer’s journey, attribute revenue to specific campaigns or messages, and automate marketing across the entire customer journey. With smart audience segmentation and activity-based marketing, you can personalize messages to land in the right inbox, at the right time, with the right message.

This would be impossible without the assistance of AI. Autonomous marketing systems are capable of crawling, analyzing and organizing billions of data points and automating tasks at a volume that no human would have the time to do.

Step three: Build and target lookalike audiences

Find audiences that 'look' like your customers.

Lookalike (LAL) modeling uses your existing customer data to find people that have similar traits to your customers. Companies such as Google and Facebook use AI algorithms to identify lookalike audiences that share behaviors, interests or demographics with your customers. For this reason, lookalike audiences are very likely to be interested in your brand.

Capturing your customer data is the first step to creating a lookalike audience. To capture data, marketers integrate web forms on their website, landing pages and social channels. There are many dos and don’t of designing web forms, but it’s important to get it right to ensure you capture the right data.

Once you are capturing your customer data, you can use Ortto to segment that audience to show your most loyal customers, biggest spenders, or even customers who have performed a specific action. Once you have this segment, you can use the Facebook integration to automatically upload your data to Facebook. Facebook’s AI can then match your customers with active users to create a 'custom' audience, which is then used to create and target lookalikes.

Leads captured through this activity will be directly imported to your Ortto CDP, allowing you to enter them into a relevant playbook and send marketing messages to them without wasting a moment. 

Step four: Experiment with real-time behavioral modeling

Real-time behavioral modeling uses current data to estimate user behaviors online. Thanks to advancements in artificial intelligence, you can track behaviors like spending habits, website visits and content interactions.

Behavioral AI algorithms analyze real-time data to determine what people are interested in, what they’re buying, and when they’re making a purchase. This is particularly powerful in online shopping experiences where you can show customers context-sensitive offers, messaging and deals that nudge them towards making a decision.

What behavioral modeling AI can do:

• Anticipate what your customers are interested in

• Predict future behaviors to help creates a more efficient customer journey

• Cross-reference with additional data sources like lookalike audiences

Most top-performing companies use behavioral modeling to create more personalized experiences for their customers. Within Ortto, you can use a number of integrations in your customer journey, and start taking advantage of behavioral modeling. One example is Recurly, a platform that optimizes subscription-based business models. Recurly uses behavioral modeling to discover when customers are most likely to make an invoice payment and, when a customer payment fails, Recurly retries the invoice payment at a time that it is most likely to be successful.

Step five: Use AI’s content recommendations

It wasn’t too long ago that AI content recommendations sounded, well, a little off. But the technology has improved significantly. One of the best ways to get started with AI content is through email subject lines.

Here’s how it works: You’re sending an email or an SMS and you really want your audience to take action. You start typing, and the AI will make recommendations. In this scenario, the AI has sifted through millions of data points about the type of subject lines or SMS messages an audience is more likely to engage with. It is then able to make recommendations based on these learnings. 

Once you’re used to working with the AI in this capacity, start experimenting with larger pieces. Have the AI read a blog post and translate it into an email. Or try feeding the AI a bunch of information and watching as it writes a basic blog post on its own. Your content team can think of the AI like another team member — it helps craft content that can be edited and perfected by a human.

Step six: Utilize chatbots or voice assistance 

Now that you understand how AI speaks, try setting up a Chatbot through a third-party provider. Chatbots, like the example from Incu below, and voice assistants use AI to simulate human conversation, interpreting and processing the customer’s questions, answers, and comments to give an answer based on the knowledge database it has available. When it reaches a point of conversation that it cannot respond to, it is prompted to pass the communication to a human operator.

The more interactions your AI has, the more that knowledge base grows, and the less your human team has to get involved. 

Using a chatbot is a great way to get used to teaching and working with AI, plus it can help with lead generation, lead qualification, upselling, and more. 

The final word 

Artificial intelligence is here to stay and it’s only become a more integral part of marketing strategies over time. Not too long ago, handing your customer service over to a robot was unheard of, but now it’s commonplace, and many of the biggest companies in the world embrace chatbots and voice assistants for their customer service.

If you want to get started unifying your data and using AI to your advantage, Ortto is a simple way to do so. In fact, giving brands access to AI is a big part of our ‘why’ — we know that many companies simply do not have the human or financial resources to implement complex platforms and architecture, so we built a unified customer journey platform for online business that is underpinned by AI. 

Get started with Ortto today. Visit our pricing page to find the right solution for your business and take advantage of our Ortto-branded free plan or a 14-day free trial of our paid features.