How is AI being used in Marketing Technology

Gartner argues that AI technology will be in almost every new software product by 2020.

“Software is eating the world, but AI is going to eat software.” Jensen Huang, NVIDIA CEO.

We’ve seen what the experts have to say.

Now let’s take a trip back in time and see just how AI came to be and how it has turned into what it is today.

In the summer of 1956 a group of scientists and academics met at the Dartmouth Conference to undertake a joint research project.

The question they asked themselves was: “How can we get machines to behave like humans?”

From that day on, the field of AI has been constantly evolving and today we can see three distinct phases in its evolution:

• Artificial Intelligence. (1950s). Defined as a program that can sense, reason, act and adapt.
• Machine Learning. (1980s). Computers begin to learn without being programmed. A single algorithm learns from past experiences and data fed to it by humans.
• Deep Learning. (2010). Machines start to mimic the way in which the human brain works. AI systems that can be trained to predict outputs given a set of inputs.

As we can see on Nvidia’s blog, we’ve gone from a purely sensory-based concept to a predictive one with original idea and content generation.

So… when did Marketing Technology start using AI?

The key to all forms of AI is data. And every business has big chunks of data from all their customers and all the metrics they keep track of along the year.

As soon as Marketing Technology companies realized the potential of AI to analyze and interpret all that data to improve conversions and customer relations, a new era had begun.

According to Statista the global market growth of AI is going to be close to double each year from here on out.

Right now, voice search and machine learning are the most widely used AI applications. Deep learning is the next step but it’s still early days for this branch of the field.

The applications of AI in Marketing Technology can be divided into two large spectrums:

Media

Audience analysis, conversion contexts, bid/cost management and investment guidance go in this category.

Google, social networks like Facebook or Twitter… you name it. They all use AI algorithms to determine variables that will impact user experience.

For Google that means search ranking position and for social media it translates to the reach of a user’s content and the relevance it’s going to have on the platform.

How about if we want information on the context of a conversion or a drop off from a sales funnel? Google Analytics has the answer thanks to the tons of metrics it keeps track of for every customer on your website.

AI is even being used to help us with our paid marketing efforts. Have you used Google Adwords lately? Well, every option that says “automatic” is giving control to an AI to help us determine how much to bid for a specific keyword.

How about this? You get home from work to have Alexa greet you and ask about your day. You answer her and then ask her for business updates for the day.

She knows the exact status of your finances and what investments you have. She goes ahead and tells you that she saw a big drop in Bitcoin and that she pulled all your cash out before it could drop any further.

That’s only a glimpse of what a future governed by AI may look like.

Experiences

Personalization, responsiveness, content curation/recommendation, chatbots and predictive customer service belong under experiences.

The simple fact that practically everything we do online is tracked in one way or another leads to corporations having access to more information about us and our interests than our own family or friends have.

If you do a search now for “flat screen TV” on Amazon or Google you’re probably going to see adverts of these products on the side of every page you visit for the next few hours. That’s just an example of how every action you do has a reaction on the Internet.

Chatbots are a great option for businesses to provide timely customer service to their users

They aren’t going to completely substitute humans for every consultation as some cases may require a more complex analysis or approach.

But nothing stops companies from using chatbots to answer frequently asked questions or providing product information.

The best part is that bots don’t have an hourly wage and they don’t sleep.

And what about cold calls? The annoying sales pitches that disturb you while you’re taking a nap.

Those days may be close to over.

AI can now be used to automatically send out initial emails to new leads and determine when and if they are ready to talk to a human representative.

This saves hundreds of working hours for actual employees and improves the quality of every lead acquired.

These are just some of the ways AI is being used to leverage a competitive advantage by Marketing Technology companies.

Tomorrow we may need to add 10 more to the list because the moment for AI is now and this industry is ever changing.

Here are some great real-life examples of how companies are using AI to stay at the top of their industries:

• Netflix only needs you to pick your first series or movie to be able to recommend what you should watch next.

Its high success rate and the fact that it keeps viewers hooked have made it worth $1 Billion.

• TurnItIn helps professors and teachers detect plagiarism in their students’ work. It compares the input paper and scans the Internet for similar content.

• Amazon’s Alexa, Siri and Cortana are virtual personal assistant ready to serve you. Just tell them what you want to do or what you need and they will find it for you.

And that’s not all. The more you use them, the more personalized their services will become as they get to know you.

• WayMo is an autonomous driving cars initiative that strives to improve road safety and mobility for everyone.

• IBM Watson helps companies to dynamically price their goods based on customer loyalty and behavior.

Each and every one of these examples involves processing data (input) to get a result (output).

Voice, sensors, text, user navigation and experience… all different ways to input data… but data nonetheless.

Now what if in a not-so-far-away future AI became less dependent on data to the point that it could create new and original outputs based on the situation?

Google’s new “Duplex” technology presented at their developer conference marks a new milestone in machine intelligence.

A completely AI-powered virtual assistant that can have a natural conversation over the phone with a human and reply accordingly independently of the answer it’s given

During the conference the robot phoned an actual hair salon and a restaurant and booked appointments at each of them!

The technology behind this breakthrough brings together natural language processing (NLP), deep learning and text-to-speech technology.

As you can see, the future waits for no one and for good or for bad AI will play a big part in it.

On a final note, let’s take in these wise words from Max Tegmark, President of the Future of Life Institute:

“Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial.”

In summary

AI is here to stay and as seen in this article it already plays a bigger part in our lives than we care to admit.

It’s the early adopters that are going to have a competitive advantage in the world of tomorrow so if you’re a company owner or thinking of starting one, now may be the right time to consider AI as the core of your business.

Changing the foundations of your company in 5 years to adapt it to the new technological advances may lead to unwanted expenditure.

Plus the AI boom will not wait for anybody so when it does hit, you had better be ready.

Take a look at five big challenges business that want to adopt and succeed with AI may face in order to help you make a decision.

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