AI for marketing: how AI will skyrocket your digital performance
Marketing is an algorithm and nobody can repeat the success of the AI when it comes to managing them
AI is now changing the whole world and the marketing sphere is not an exception. The creation of the powerful marketing strategy that resonates requires a good understanding of human psychology and some empathy.
However, primitive marketing that we are used to pretty well is just a set of algorithms. And no human can repeat the success of the AI when it comes to managing algorithms. So, let’s dive deeper into the perspectives of AI for marketing.
But first, let’s look at what AI is.
Some time ago, developers have been building algorithms they could explain, using conditions “if this → then that”.
However, some problems are too difficult for people to process and understand. The more data humanity has been accumulating, the more difficult it was to cope with all this data. Time has come to create neural networks!
How do these networks function? Nobody knows that. Even people who create them.
But here is a very approximate mechanism of a neural network creation, which can give kinda some understanding of why AI is so powerful.
Let’s imagine that you want to build an ANI (artificial narrow intelligence) that will distinguish different images. Say, pics of a table, and those of Trump.
Creating such a neural network, you build a bot that builds bots that will distinguish between images. Also, a builder-bot constructs a bot that will teach learner-bots to do that. Neither a builder-bot nor a teacher-bot can differentiate between images of furniture and the president of the US.
The builder-bot builds bots-learners, but it is not even skillful even in its trade and creates bots with some random connections.
These randomly-built bots then go to the teacher-bot. How it teaches small learners-bot if it can’t understand what is depicted in the photo?
Well, it doesn’t teach, it tests. A human being gives the teacher-bot a bunch of labeled photos, like test questions and answers to them. The special feature of a neural network is that it needs a real lot of information to learn.
If a human child can understand that it is dangerous to stick a hand into the fire, having done it a couple of times, neural networks are much dumber when learning.
If the neural network was a child, to get an understanding of such a simple thing, it would have to touch a hot thing like 10 thousand times or even more.
That’s why AI creation was impossible before the era of Big Data. But, wait! We now have much data yet how to label such an amount?
Though there are some tools to make the labeling process easier. this process is still manual. Thousands of teams around the world label data to enable, for instance, autonomous vehicles’ existence.
And by the way, you help with this matter too, while choosing the pictures where traffic lights or crossroads are depicted offered you instead of captchas by Google.
So, this labeled data goes to the teacher-bot and gives it the information on what is depicted in the pictures. Learner-bots try to determine where a table and where Trump is.
Actually, they rather guess, than determine.
After the teacher-bot checked the results, the builder-bot separates the ones with the best results and recycles the others. Then a builder-bot creates new learner-bots similar to the most excellent learner-bots with some changes and sends them back to school again. Rinse and repeat.
So, it’s kinda natural selection in action. After every round of testing, the best bots survive and improve, while others are destroyed. The loop is repeated until the results of the best learner-bot are close to perfection.
This excellent learner-bot exceeds all expectations of its creator, it distinguishes between a table and Trump even when a human being fail to do that and acts in a way his creator can’t understand (if you’ve ever watched recorded chess parties with Alpha Zero, you know that humans don’t play chess like that). This is how AI is born.
And if it acts better than people in every possible way, let’s see what can do AI for marketing.
1. Enhance your content
People often say that content creation is purely human skill, and AI can’t generate great content as it lacks the understanding of aesthetics and psychology.
I don’t see any problem with it and, though I am a writer and it saddens me, I believe AI will do better than humans both when it comes to literature/journalism and content/copywriting
A famous American writer Kurt Vonnegut wrote in “The Sunday Herald” newspaper a year before his death:
“If I should ever die, God forbid, let this be my epitaph: THE ONLY PROOF HE NEEDED FOR THE EXISTENCE OF GOD WAS MUSIC”.
He was an author but still believed that music, unlike literature, is divine.
When I’ve been telling my dad, who is a big music lover, about the power of the AI, he told me: I will believe in its power only when it can create music like the one of Chopin.
Later, I’ve persuaded my dad to listen to a long-forgotten Chopin’s musical composition, and he was fascinated. What a genius Chopin was! - he exclaimed.
The thing is this “long-forgotten Chopin’s piece” was written not by Chopin but a musical intelligence Emmy created by a composer and scientist David Cope. It just used algorithms it determined in Chopin’s style to make a composition similar to Chopin’s one.
David Cope doesn’t consider that Emmy will threaten the work of human composers. It will just help them to create better music.
Yet, maybe one day Emmy will win an Emmy award, who knows.
Why I am telling you this story?
Because if marvelous music can be of a non-divine origin like Vonnegut thought, but of an algorithmic one, everything else definitely can be too. Including content.
I will elaborate more on AI-generated content in one of my following posts. In any case, Ai will optimize content delivery through SEO.
2. Optimize content delivery
Every day we interact with such an SEO-AI that tries to organize the existing content effectively. I am talking about Google with its RankBrain algorithm, which allows bloggers not to stuff their articles with keywords, as they did before.
RankBrain independently decides what results should be ranked in the organic search where exactly, based on the natural language processing.
To make this decision, the RankBrain algorithm analyzes a bunch of data and creates a ton of different criteria that matter to a higher or lower extent. Of course, Google now gives some tips to rank your materials higher such as “be an authoritative trustworthy expert”, but, as you can see, this advice is pretty vague.
That’s because RankBrain is a classical AI, and nobody has the ultimate knowledge about how it works. However, an outstanding SEO specialist Brian Dean figured out quite successfully how to rank for the algorithm to boost your SEO results.
In any case, if you want your content to rank high in Google, you have to spend a bunch of time making this happen. Even more time, than you spend creating the content. And nobody can guarantee that your efforts will pay off.
Here are just a few operations that you have to do for the on-page SEO.
- To analyze market trends and popular content
- To analyze top-performing articles and to get insights from them
- To create the semantic core of your site
- To brainstorm keywords which align well with your semantic core to optimize your post for them
- To find keywords your competitors rank for and you don’t
- To analyze the search volume and the SEO difficulty and to choose the most appropriate keywords among generated ones
- To create an outline of the post, preferably including related queries people are looking for
- To optimize your article for the chosen long-tail keywords and to make your article as relevant as possible to the main one
- To analyze regularly what keywords your article ranks for and to update the article adding those keywords to it
And there is also off-page SEO which is more important and difficult than the on-page one.
As you can see, SEO includes A LOT of manual work. Now, imagine that all this work is done by a neural network, and you can concentrate just on writing and be sure that your positioning will be alright.
Let’s take an example of the Alli AI SEO tool and see what it can do for you already now. It creates an SEO strategy for you, based on all the Google algorithm updates, so you won’t have to read a lot of articles on SEO, take many courses, such as the Ahrefs very expensive one, and figure out how to change your strategy to keep up. It also offers you code and content optimizations to generate more organic traffic. Besides, you can track your progress in the same tool.
Given that SEO takes, at least, a half of your time, distracting you from content creation, when you’re growing your blog, using such an AI-based SEO tool seems to be a great deal.
3. Help generate a bigger volume of higher quality leads
When we’re talking about leads, we mean prospects that can potentially become customers. So, leads are people who will likely be interested in your product or service.
How do you define potential customers among mere people who, say, visited your site or read your company’s blog? First, you have to identify your target audience, manually create your target personas and reach them out at the right time with the right offer. And, of course, you can make a mistake with your targeting and all your efforts won’t give a tangible ROI.
61% of marketers say generating traffic and leads is their top challenge. And sales reps spend as much as 80% of their working time calling and emailing potential customers, and, hence, only 20% of time closing deals.
Probably, this is the reason why everybody hates generating leads.
But in the nearest future, instead of handling all of these repetitive and routine tasks, you will be able to concentrate on a more important activity, assigning lead-generation to a neural network.
It will be able to create more specific target personas, based on the problem your company solves, analyze your client database detecting the clients that are ready to make a purchase or will be ready to do it soon, and nurture them the right way.
Let’s take Leadberry - one of the best modern lead generation tools, which is the best rated Google technology partner app in the world. What it can do for you already now?
Not only can Leadberry unveil what executives of the exact companies visited what pages of your site, but it also provides you with their contact information across various channels, from phone numbers to Twitter accounts (Google has the biggest database, so you can imagine the power this app hands out to you).
The app also evaluates how serious a visitor's interest is regarding your services/products based on a set of algorithms, so all the spammers are filtered out automatically.
Besides, the soft offers you the leads similar to the ones you’ve already generated.
And finally, when you’ve gathered your list of prospects in Leadberry, you can connect it with your favorite CRM systems or email automatization tools.
4. Expand your audience in social media
So, social media marketing is a great form of customer service as well as a very effective way to spread awareness about your company using a carefully crafted content strategy.
AI can help you craft it based on the insights from big data. Not only will it help you to define what content in your niche gets the most likes, comments, and shares but also analyze the performance of your posts. This will help you to define messages your target personas resonate with and to build your social media strategy around these messages. Hence, you will receive a massive competitive advantage.
You’re used to gathering data and get such insights from the results of your top-performing competitors manually. No need to say that uncertainty is great in this case. So, why not assign these boring tasks to somebody who won’t be bored and will be much more accurate than you are, and spend your time more wisely?
For instance, using the SocialBakers platform, you can easily uncover interests and content preferences of your target audience, as well as the most authoritative influencers that they follow.
Also, the platform allows you to manage your publications across various social media in one calendar, using just your smartphone. And after your content is published, the platform gives you quite a detailed analytics on how it performs.
5. Create influencers of your own
I’ve already been telling you about CGI influencers in this article.
And AI can help you create own influencers. They can be not just photos, but even popular video bloggers. Remember that video generates more engagement than any other content type on Instagram
To create your influencer-character and its videos, you can make use of computer-generated graphics with AI. NVIDIA has already been working for several years to make AI capable to do the heavy work in the complex graphics creation instead of human artists.
So, why not suppose that in future Deep Fake will be able to generate not only fakes but brand new characters based on the criteria you prescribe?
For instance, China has already created an AI presenter.
Yes, maybe, he is not very emotional but it still delivers news pretty comprehensively. I am sure that in a couple of years we’ll witness a CGI revolution and a lot of influencers will appear.
6. Personalize your campaigns
In 2019, members of the Association of National Advertisers selected “Personalization” as the Word of the Year.
There are quite serious reasons for that. 74% of marketers consider targeted personalization the reason for increased customer engagement. And they are right, as half of Millennials and Gen Zers ignore communications from companies that don’t personalize their content.
Research from McKinsey even shows that brands that are good at personalization deliver 5 to 10 times the marketing ROI & boost their sales by as much as 10% as compared to companies that don’t personalize.
To my mind, personalization has several dimensions, and all of them can be optimized with the help of AI.
The first dimension is the segmentation. Today, most of the marketers when targeting, define several segments and ideally create a targeted sales funnel for every category of users.
This kind of personalization, as you can see from the stats above, can make these efforts worth every penny. But what if the segmentation was much more precise (because a larger dataset is considered) and there were 1000 segments of the same audience, instead of 10? How many more results would it bring!
Now, you probably think that it would be quite difficult and expensive to process all these segments and create email sequences for all of them. But here, we have another dimension of personalization - natural language processing (NLP).
With time, Ai constantly becomes better at writing in a natural language. So, it can analyze the patterns of email campaigns that once converted amazingly, and create the one for your company based on the analyzed data.
Fortunately, texts of some legendary email sequences can be easily found online, so you will be able to gather a great collection for your NLP neural network.
Besides, you can use NLP to localize your content. Probably, localization is not so popular topic to discuss, but it can still make or break your game. For instance, 60% of local consumers in non-English speaking countries will unlikely to buy from English-only websites.
Will you click to read the article “How to buy a bindaas Porsche for just 755152 rupees”? I mean, even if you’re a fan of Porsche and are currently going to buy a car.
That’s because you’ll just lack a desire to google what means “bindaas” in Hindi slang and to convert rupees into dollars. Nobody wants to read the article to understand the title of which he had to google twice.
So, the article about how to buy a luxury Porsche for just $10000 that had a viral potential will remain of-the-radar.
When you localize your marketing campaigns, i.e. their language, including the local slang, use correct date and currency formats, take into account local behavioral patterns, you show respect to your audience. And your prospects will return a thousandfold in gratitude.
You will even be able to move one step further and create personalized digital sales representatives that will engage your clients in dialogue using both conversational tone and respect to every little detail you know about your customers.
They will also send emails at the right time, craft awesome subject lines to stimulate clients’ curiosity and be there for your clients 24/7. This will result in closing a great number of deals. And this is our nearest future!
7. Enhance your clients’ user experience with chatbots
All the points about personalization correlate with AI-based chatbots even better than with email sequences.
The thing is that everybody is tired of getting limitless personalized or “personalized” emails from different companies. So, at best, just 20% of your audience will open your email, no matter how much time you’ve spent to make it perfect.
Now, compare this with 88% open rates you can achieve messaging your prospects via a chatbot.
Not only can chatbots have high open rates and communicate with your prospects in a personalized way but also they can answer very quickly up to 80% of clients’ routine questions, which is important to 55% of the Internet users.
If usual rule-based chatbots can respond 80% of obvious questions with answers prepared in advance, they can’t, however, answer any questions outside of the defined rules.
And can not learn to do that through interactions. They only perform scenarios you train them for, and this can reduce the extent of personalization and turn off some of your clients.
On the other hand, AI chatbots understand the context and intent of a question before formulating a response. Due to this understanding, they can generate answers to more complex questions and can continuously improve.
Besides, they understand many languages and can truly work miracles of personalization.
AI chatbots demand much more data and time to train, but in the long run, an AI chatbot will become an awesome tool for your business. You can base your sales funnel on a chatbot, nurture your client base through it and even turn it into a professional digital sales rep.
To do that you can use a tool just like the Conversica system which is an already accessible sales AI assistant. So, what such a sales rep can do for your business?
It follows-up leads who showed some interest in your product or service and engages unresponsive leads with natural language, doing it either via email or text exchanges.
Also, Conversica sends invitations to both online and live events to your clients and can do that in multiple languages. After having several interactions with your clients, the system identifies the hot leads, whose contacts are then given to your sales team, and updates your CRM system with new data obtained from the interaction.
Besides, all the insights on where leads are getting stuck, Conversica AI stores on its dashboards and in the reports so that you can understand pretty quickly what aspects of your sales funnel should be improved.
So, using the soft of such a kind, you allow your sales team to focus on closing the deals, and not to be overwhelmed with necessary, but not so efficient for your business tasks.
Quantum computers will change the AI game completely
Quantum computers may be soon enough used for scientific and commercial advantage, possibly, even in 2020. And quantum computers pull up the Quantum machine learning development.
What’s the cool thing about it?
From the technical point of view, in classical computing, data is stored in physical binary bits. This means that a bit is either in a 0 state or a 1 state and it cannot be both at the same time.
Quantum computing uses properties of subatomic particles that can be in two states at the same time, and the quantum bits (called “qubits” for short) can be a combination of both a classical 0 and 1 state. This property allows much more data to be stored in qubit than in a regular bit.
How will quantum computers revolutionize AI? Remember at the beginning of this article, I’ve described the process of machine learning? It takes a bunch of data (the more, the better) and, hence, A LOT of time to process it.
Qubits features will allow us to speed up the machine learning process to a high extent, and to allow AI to solve VERY COMPLEX problems with a tiny or none inaccuracy.
For instance, now Google has a quantum computer they claim is 100 million times faster than any of today’s systems. Just imagine the opportunities it creates for machine learning!
So, even though the use of AI in marketing can now seem a luxury, in the nearest future it will be the necessity for you if you want to beat your competitors or, at least, be competitive enough. So, it’s time to think in this direction to keep up.
What do you think about the AI perspectives for marketing? Have I mentioned all the cases? Or you have anything to add? If you do, share your thoughts in the comments.
Jane is a B2B marketing blogger and content marketer, sales funnels architect, digital marketing consultant. She is fond of in-depth analytics and good coffee. You can read more of her articles on Medium: https://firstname.lastname@example.org