Artificial Intelligence Marketing
By: Federico Gobbi
Tags: Machine Learning, Artificial Intelligence, Marketing, Deep Learning, Digital Marketing

AI Marketing

Nowadays, we are hearing experts and professionals talking about the good sides of innovation. Robots helping humans rehabilitate from fatal diseases or machines predicting future consumers’ behaviors.

On the other hand, many are also talking about job replacement. For these ones, the robots will take everything and destroy the planet once and for all. No more jobs, the human destiny is to die burdened under the weight of the machines.

Thanks God, the future is better than many expect it to be ;-)

A couple of years ago, I was working in a robotic company based in Italy called @TelerobotLabs — later acquired by the larger group “Danieli Automation” as a new and stronger robotic department — and the idea of working with robots for the future of the humanity was extremely exciting.

Of course, the very preeminent mystery was: Is there a chance robots will take over the planet and destroy everything like in the movie “Terminator”?

There wasn’t a better answer than the one CEO, David Corsini, gave me at that time.

“Until the robots are plugged into the wall, we’ll simply unplug them.”

So, after this assumption, please sit down on your sofa and enjoy the article because no one is gonna take over your couch.

What is Artificial Intelligence?

In order to give you a better idea of what we are talking about, I’d love to start from the very scratch and clarify — once and for all — the doubts anyone might have by reading this article from the youngest to the oldest.

Since I am also still learning about this fascinating world I want to use other people’s experience to describe what artificial intelligence is and how it has developed in the previous years.

Bernard Marr, a Forbes writer, defined temporarily and etymologically: “Artificial Intelligence has been around for a long time — the Greek myths contain stories of mechanical men designed to mimic our own behavior. Very early European computers were conceived as “logical machines” and by reproducing capabilities such as basic arithmetic and memory, engineers saw their job, fundamentally, as attempting to create mechanical brains.

As technology, and, most importantly, our understanding of how our minds work, has progressed, our concept of what constitutes AI has changed. Rather than increasingly complex calculations, work in the field of AI concentrated on mimicking human decision-making processes and carrying out tasks in ever more human ways.”

John McCarthy, Professor Emeritus of Computer Science at Stanford University, described Artificial Intelligence in a research as “the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable. Intelligence is the computational part of the ability to achieve goals in the world. Varying kinds and degrees of intelligence occur in people, many animals, and some machines.”

After an in-depth research, I came up with an easy definition of what Artificial Intelligence means. AI is the ability of a machine (computer) to perform tasks in a way that will end up with meaningful solutions to the initial assignments, compared to the typical decisional process of a human.

Did you hear about Machine Learning and Deep Learning?

Easily, these are two applications of AI. Actually, machine learning incorporates deep learning to some extent. Somebody could also say the opposite, we will analyze the differences in a second.

What is Machine Learning? and Deep Learning?

To make it easier and faster for me ;-) I like to share the NVIDIA definition of Machine Learning:

Machine Learning at its most basic is the practice of using algorithms to parse data, learn from it, and then make a determination or prediction about something in the world. So rather than hand-coding software routines with a specific set of instructions to accomplish a particular task, the machine is “trained” using large amounts of data and algorithms that give it the ability to learn how to perform the task.

Deep Learning involves feeding a computer system a lot of data, which it can use to make decisions about other data which is fed through neural networks, as is the case in machine learning. These networks — logical constructions which ask a series of binary true/false questions, or extract a numerical value, of every bit of data which pass through them, and classify it according to the answers received.

As our teacher, Francesco Mosconi said: “Deep Learning is a Machine Learning that works really well with large amounts of unstructured data like images or text”.

Francesco is founder @DataWeekends, a Machine Learning and Deep Learning workshop program to teach basically anyone (I made it ;-) how to code an AI machine.

“Today, image recognition by machines trained via deep learning in some scenarios is better than humans, and that ranges from cats to identifying indicators for cancer in blood and tumors in MRI scans” — NVIDIA says.

So, why explaining in a such “deep” way how AI works and is composed?

The answer is that in order to fully understand how Artificial Intelligence Marketing works is also imperative to understand how AI itself operates. Then, understanding the AIM application is easier — nonetheless, I helped you to balance your knowledge with the topic.

Now, another important step.

What do we mean when we say Marketing?

I need you to understand what marketing means. I am giving you an easy definition. Marketing is the process and the action of promoting and selling products to consumers (a deeper analysis could be made on this definition but we will stick with an easy one since our objective isn’t based on this study).

..and we come to AIM — Artificial Intelligence Marketing !

I consider it obvious, but it couldn’t be, how these two — very different, apparently — fields are coming together.

The connection between Artificial Intelligence and Marketing is based on finding the perfect way of promoting and selling the perfect product to the right person at the right time.

You see how the definition is turning into something extremely specific and defined.

The perfect way…

The perfect product…

The right person…

The right time…

These “RIGHTs” remind me of the “Just-in-time” Japanese process, also known as TPS- Toyota Production System — as a “methodology aimed primarily at reducing flow times within production system as well as response times from suppliers and to customers” (Wikipedia, 2016).

Many believe that marketing will be one of the first disciplines disrupted by AI. But marketing and business relationships are human relationships, how will these ‘machines’ actually be sentient? Personal relationships … even if not reciprocated, that will feel very real to us. “

And where will AI affect day-to-day consumers the most? According to PHD, it will be with “information-access, entertainment-centric and social-connection platforms accessed across multiple devices”.

I personally decided to categorize these processes under what I called Artificial Intelligence Marketing. Meaning all the systems are using Artificial Intelligence in a way that can influence the marketing activities as we’ve never seen before, from the perfect customization of everything the customer will need to predicting his behavior and desires.

In this way, we will track and lead this conversation by suggesting and exposing the new trends/startups to the marketers community (and not just them) and deeply analyzing how this ecosystem will disrupt the previous scenario.

So what is Artificial Intelligence Marketing going to be? For me is going to be the perfect strategy. The word perfect is going to impact every product and service. We will have what we want right there.

There are some areas which will be more exposed and others less so.

I posted this question to the guys that are currently active on the Growth Hackers -GrowthHackes.com — platform (founded by Sean Ellis) and I got some very interesting answers, especially the one my friend Arsene gave me:

“It’s still in its infancy (see Persado for the copywriting aspect of it), we can envision an interesting wave of AI content creation apps since curation is just a limited first step. It’s very time consuming for marketers to develop content, and even more stay up to par with the latest in SEO algorithm (Hummingbird and what next?) to develop topical depth that favors SERP ranking. […]

There definitely is a clear trend in AI chatbot. A number of platforms make it extremely easy even for the nontech savvy marketer to create new AI-persona chatbots, content-aware chatbots and more. We are also going to see that AI permeates new forms of media in these new “channels” such as real-time video content analysis to create brand-new forms of must-have users engagement in both the B2C and B2B spaces. […]”

There is a phrase I believe is traveling behind all these big question marks and AI influencing marketing:

“If a Tesla can drive itself on autopilot at 70mph on the highway taking in all the surrounding environment inputs, we can help marketers do the same with all the data inputs they are analyzing.”

What are the Artificial Intelligence applications in the Marketing Activities?

I was just reading a few days ago an interesting article written by DemandBase saying that 80% of all Marketing Executives Predict Artificial Intelligence Will Revolutionize Marketing by 2020.

But actually, AI is already revolutionizing Marketing. There are dozens of applications already set up.

Here you have a breakdown I made from a personal research into what I thought were the main applications (I’ll try to put them in decreasing order of relevance):

Analytics. It’s extremely incredible how much data big companies have nowadays. What’s interesting? The point is that right now this data is not used in any way. AI will help to organize, select, prioritize and come up with the right data at the right moment for the right task. (Noodle.ai) Preventing fraud. Today one of the biggest challenges where AI already helped a lot is internet fraud detection. The relevance of AI is not just for card issuers, though. Data breaches is something retailers have been exposed to for a long time. AI will help to prevent fraud analyzing not just structured data but also unstructured data. (PayPal) Predictive Customer Service. Imagine you can give to your customer the right product at the right moment at the right price. With AI you can. (Intel, Saffron, Digital Genius, Assist.ai etc.). Product pricing. I have always been excited thinking that I could find a certain product at the price I was expecting. AI allows companies to predict the perfect price and generate a custom fare for the specific expectations of the different customers — it is a sort of dynamic price optimization based on the prospects. Forecasting. Clearly one of the biggest potentials that AI has is predicting, almost whatever we need for each business market. AI helps companies to foretell — almost perfectly optimized — how the sales will look like in 6 months/1 year from now. Of course, it is something businesses are already used to do, but today these forecasts are not very accurate and easy to do. AI will take the numbers directly from the companies’ financial statements, CRMs and all the useful documents a firm is producing.

These are the main applications where AI is influencing and will influence marketing. Here many others:

6. Image Recognition

7. Voice Recognition

8. Language Recognition

9. Virtual Assistants/Agents (Waston, IBM; Domino; Coca-Cola)

10. Website Designing Optimization (The Grid; etc.)

11. Recommendations — products, food, social platforms (Facebook; Amazon; Uber; Netflix; LinkedIn; Google Plus; etc.)

12. Content curation

13. Search engines (Rankbrain; Boomtrain; etc.)

14. Social semantic (Tay, Microsoft etc.)

15. Localization (Facebook drones; etc.)

16. Sentimental Analysis + location recommendation (Facebook; etc.) [Happy person in a fun place]

17. Customer segmentation

18. Color adaptation — websites changing color based on the customer preferences.

19. Content generation

20. Refine marketing.

Of course, the major number of AI applications in marketing are online-based processes. It is also considerable the offline world. AI will physically help people in the everyday things. Customer experience would be the very first application that comes up to my mind. Talking about something more important than marketing, Microsoft announced in 2016 its ambition to defeat cancer using Natural Language Processing (NLP) to analyze research papers in close to real time.

However, we will start considering the online environment since at the moment it’s the most affected one.

NB you can be part of our Meetup group and start meeting with other professional discussing this topic. Here is the link to subscribe to the group

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Please leave any comment you might have below, you will be considered part of the next wave of the Artificial Intelligence Marketing 😎

Originally posted on LinkedIn: https://www.linkedin.com/pulse/artificial-intelligence-marketing-association-manifesto-gobbi