Marketing, they say, is the process of getting people interested in what you have to offer (product or service). It’s that simple (a no-brainer).
Throughout history, marketing has been revolutionized over and over, and it’s no surprise (people change).
With more advanced technology coming into play decade after decade, determining how people relate to the world around them (their behaviors, what they like and dislike), the process of marketing keeps getting complicated (or rather advanced).
Fortunately, for smart marketers, the same technological advancements that change people’s behavior can also be leveraged for better marketing.
When radios came into play, people’s behavior changed. There was that instant shift, but smart marketers adapted and leveraged radios to strengthen their marketing.
The same with the television and the internet.
Today, there is a new king in town, artificial intelligence, and it’s already having the same impact as TVs, radios, and the internet.
But, there is something different this time, it’s no longer business as usual with artificial intelligence.
What we saw with the radio, television, and internet was what I would call ‘a platform change’.
It was more about ‘the where’ with radios, TVs, and the internet; where people spend their time.
Radio marketing, TV marketing, and internet marketing are all digital marketing that is differentiated by their respectful platform.
You do radio marketing on radio, TV on TV, internet on the internet, and even print on print; but that’s not the case with Artificial Intelligence.
AI = Game Changer.
What is Artificial Intelligence (AI) Marketing?
Artificial intelligence marketing is the process of getting people interested in your product or service using/leveraging artificial intelligence technologies/tools.
It is the automation of modern marketing processes in one sense.
Modern marketing has been characterized by social media marketing, internet ads, SEOs, and their likes.
Artificial intelligence marketing is all about making all these existing marketing practices more effective, efficient, and faster.
In today’s world, there are so much consumer data flying around and what AI does chiefly, is to make sense of this consumer data and make smart marketing decisions autonomously.
AI is no new to consumers.
According to Pega, 77% of consumers are already using AI platforms in 2019. Not only are there a lot of consumer data around for marketers to leverage, but most consumers are also already using AI platforms (having AI in their lives).
Oracle found out that 78% of brands have already or are planning to implement AI in 2020.
It’s coming together, isn’t it?
The point is that AI marketing is not a new thing waiting to penetrate the market. It is already in the market, and businesses are already implementing it, while other businesses are still sleeping.
AI marketing is the future of marketing. And it’s not just the future of marketing, it’s marketing today.
Maybe to some, it has not gained mainstream attention but the reality is, it’s here.
Artificial intelligence marketing is AI running online ad campaigns, communicating with customers as bots, and generating leads for businesses.
Why does AI matter? Importance of AI Marketing
Technologically, the direction AIs domination of going into the future is upward and forward.
I spend more time on my phone than I spend on any other device every day. 70 – 90% of the time is spent on my phone all I do is consume content (videos, audio, or written content).
Most of the contents I consume (if not all) are directly or indirectly recommended to me by an AI system. Google Search, Google Discover, and YouTube are all powered by AI.
And as such, there is no hiding that AI has a great influence on my everyday life. I’m used to AI recommending things for me, I trust its recommendations to a great extent.
But am not alone. Most people with smartphones are seeing AI in their everyday use of their phones. Whether they are gaming, Facebooking, Googling, TikToking, Twitting, Instagramming, Snapchat, YouTubing, Gmailling, or anything ‘ing’ with their phones.
We have arrived in an age where AI systems are influencing people every day, and the number is growing.
AI has and is proving to be a force of influence in today’s world. It has been deployed heavily to influence political elections as exposed by the Cambridge Analytical Scandal.
Marketing on one hand is all about influence; influencing people to pay for products and services.
And AI on the other hand is one of the most (if not the most) effective tools of influence in today’s world.
As such, AI marketing is a no-brainer.
For the bookman, here is some importance of AI marketing:
Importance of Artificial Intelligence
- It is very effective:
This is probably down to the fact that AI marketing is built on the back of real consumer data. One of the things that make AI stand out in marketing, is, its leveraging and making sense of the vast amount of important consumer data available in this era of big data.
No more random ads, ads are shown to people who are most likely to buy your product or pay for your service. They are shown to people who have demonstrated interest in the product or other closely related products.
- It makes marketing super-easy:
Plug and play marketing, that’s the promise of AI marketing. Everybody can be an expert marketer because AI in marketing works. After all, most AI marketing efforts work autonomously.
All you need is to click the install button and bingo! You have an AI chatbot running on your website, generating leads over and over.
AI marketing makes every marketer better. There is no need to go through consumers’ data and have sleepless nights when AI systems can do the hard work better and hand you over the result.
- It is cost effective:
Looking from the outside, one would have thought that AI marketing is expensive. But, that is not the case. AI marketing saves businesses money, by cutting down their marketing budget significantly.
AI marketing is so cheap, like crazy cheap. And it’s one of the reasons why smart marketers should immediately jump on the ‘AI for Marketing’ bandwagon.
Compare the cost of AI marketing tools to hiring full-time marketers and you will understand why AI marketing is so cheap.
The reality is that AI marketing is going to reduce the need for manpower in the marketing department.
A marketing team of 10 can be slashed down to 2 or with AI augmenting them.
2 – 3 marketers plus AI will deliver better marketing results as a team than 10 – 20 marketers without AI; in today’s world, no doubt.
- It is easily scalable:
You don’t have to worry about growth and the need to scale up marketing efforts with AI marketing.
Everything just works automatically and autonomously, maintaining the same degree of effectiveness at scale.
Much of this is really because AI systems can cover more marketing grounds faster. Scaling from 100 to 1,000,000 with AI happens in a flash.
Artificial Intelligence (AI) Advertising
Artificial intelligence (AI) advertising is the use or deployment of AI tools/technologies in the process of creating and delivering persuasive messages that cause someone to take the desired action.
One important thing to note is that, in the same way, we have different levels of self-driving cars, there are different levels of AI advertising.
The levels of AI advertising are dependent on the degree of AI’s involvement in the advertising process.
Traditionally, running ad campaigns involves audience research and analysis, ad creation, and deploying ads based on budgets to an audience.
This process of online advertisement is painstaking and requires a lot of experience and expertise to get campaigns right (to create successful campaigns consistently).
AI advertising today (maybe revolutionized in the future) is not about replacing humans completely in the advertising process, it’s about augmenting humans, aiding them to be better.
Break advertising into different stages (Audience research/analysis, ad creation, or ad buying) and you will find an AI tool that could be used to make smarter decisions or choices in each stage.
- Audience Research/Analysis:
With so much data on consumers available in today’s world, audience research and analysis becomes majorly a thing of mining (collecting) and making sense of these data to establish target audiences.
The process of ‘making sense of these data’ traditionally, is a pain in the a**, even for experienced data scientists.
These are the stages where AI (machine learning algorithms) come into play. Machine learning algorithms are currently being deployed by top ad platforms (Facebook, Google, and their likes) to collect (mine) and analyze these data for advertisement purposes.
This is one of the reasons why Facebook ads are incredibly attractive (beyond the fact that they are cheap, for now).
- Ads Creation:
This is all about creating a compelling message that can be presented in plain text, graphically, or as video content.
And ad creation in a sense is no big deal.
Everybody can create an ad, but, not everybody can create an ‘effective ad’.
Creating an effective ad consistently is no beginner’s feat. It requires a great deal of experience (trials and errors) and insight to create a compelling message that will resonate with a targeted audience.
Gaining such valuable experience from a human perspective takes months (sometimes years) of trials and errors but not for AI systems.
AI systems can learn very fast, and gain sufficient experience to create compelling ads.
A popular case study is the use of IBM’s Watson (an AI system) to script an ad for the Lexus ES.
Watson identified elements common to award-worthy commercials that were both emotionally intelligent and entertaining, according to IBM.
There are so many other AI tools that follow similar principles and are used to create compelling ads, some are video editors such as Magisto and smart cameras such as Adobe Photoshop.
- Audience Targeting:
This is closely tied to audience research/analysis. Where audience research/analysis is in the planning stage of advertising, audience targeting is at the execution stage.
Audience targeting is a way marketers get their ads to reach their desired consumers with a great deal of accuracy, based on the consumers’ online and offline activities.
Think of audience targeting as a system for getting your ads to reach the kind of people you want your ads to reach.
Usually, after researching and analyzing an audience, an advertiser says ‘this is the kind of people I want to reach out to’.
Audience targeting is ensuring that the advertiser’s ads get to his desired (targeted) audience.
This is a feat that for a long could not be achieved with a high degree of accuracy until AI rolled in.
AI systems can ensure that only your targeted audience gets your ads.
If I run an ad on Facebook targeting only Indian males aged 21 – 30, that live in Delhi and are interested in Machine Learning. My ads will certainly (99.9%) get to only Indian males aged 21 – 30, that live in Delhi and are interested in Machine Learning.
That’s the power of AI in audience targeting and thus increases to a great extent, the likelihood that my ads will perform better than usual.
- Ads Performance and Spend Optimization:
On the 8th of November 2020, Facebook introduced campaign budget optimization (CBO). This is a feature that helps to automatically redistribute ad budget to the best-performing audience.
That’s a practical example of Ad spend optimization; an effort to ensure you get the best results for your cents.
AI systems are capable of carrying out such feat as they have shown in their use for Facebook CBO.
The other part of the equation, ad performance, is in a reasonable way tied to spend optimization.
Ad performance is really about how well your ads achieved their desired result based on your budget.
AI systems are begin deployed to ensure that ads get to their targeted audience, and increase ad performance by experimenting with audience segments, identifying the best performing audience, and hola! It automatically redistributes the ads to that audience.
AIs are game changers in ensuring that ads perform at the utmost best and that ad budgets are well spent.
A study conducted by Xueming et al, suggests that “undisclosed chatbots are as effective as proficient workers and four times more effective than inexperienced workers in engendering customer purchases”.
Now, that’s a game changer happening in the world of direct online marketing.
Direct marketing is a business effort to get a potential customer interested in their product or service through direct means without using any form of the middleman (such as advertising media).
An example of direct marketing can be mail, email, phone call, or in-person pitch. Direct marketing is a highly effective form of marketing when executed properly, but the problem traditionally seems to reside in its scalability.
You’d need 10 persons or 10 different communications to market to 10 customers.
Imagine a business whose potential customer runs in the 10s of thousands or 100s of thousands or even millions: You will be needing a lot of direct marketers.
Online direct marketing happens in the form of direct communication with potential customers through a private online messaging platform (Facebook Messenger and WhatsApp), emails, and the revolutionary chatbots among others.
Chatbots are where AI is influencing direct marketing the most. Think of Alexa, Siri, or Google Assistant and you have an example of what an AI chatbot can be.
AI chatbots can carry out communications via auditory or textual means, they are being deployed in marketing/sales by smart businesses on their websites and off their site, like being used by businesses on Facebook Messenger.
AI-based chatbots can generate leads and make sales by communicating with a customer directly, they are becoming more effective at that come each morning.
Most businesses deploy AI chatbots for customer service purposes, and interestingly, great customer service is a great marketing strategy.
Examples of Businesses that uses/used AI Chatbots:
Yes, that Starbucks, the multibillion dollar coffee company. Starbucks up-ed its marketing efforts to another level in 2017, when it unveiled a chatbot that takes orders via messaging or voice.
The chatbot was introduced as a feature in its mobile app (My Starbuck Barista). And they didn’t stop there, they went on to integrate the feature with Google Assistant and Alexa, two of the most popular Virtual Assistants developed by Google and Amazon respectively.
Facebook unveiled ‘chatbot extensions’ at its developers’ conference, F8, in 2017. And smart businesses like Spotify took advantage of it.
Facebook’s ‘chatbot extensions let bots provide interactions, social features that users can invoke into their conversations’.
Spotify launched a Facebook Messenger chatbot that allows customers to discover and share music recommendations based on mood, activity, or genres. Spotify is not the only ‘smart’ business taking advantage of the Facebook chatbot extensions anyways.
Fandango’s messenger bots allow its customers to watch movie trailers, find local theatres, and see what’s trending. And Lyft also enables users to request rides via Facebook messenger chat. MasterCard, Staples, Pizza Hut, and The Wall Street Journal are also deploying Facebook chatbots as part of their marketing strategy.
They are also leveraging the Facebook chatbot extension, albeit, in a way worthy of elaboration.
National Geographic as of the time of writing this article has over 46 million likes on Facebook (46,110,933 likes to be precise) and over 45 million followers; that’s a lot of likes and followers.
And National Geographic is not shy about using chatbots as a marketing strategy to leverage its huge Facebook audience.
In 2017, National Geographic leveraged ‘Einstein Messenger Chatbot’ to promote the launch of its original series ‘Genius’.
Facebook messenger users were given the chance to chat with ‘Einstein’, while the boot attempts to educate users about physics, it also ‘educate’ them on the release of the original series ‘Genius’.
That’s what I would love to call ‘Genius Marketing’. In 2018, they also tried a similar marketing strategy when they wanted to promote their 2019 Almanac.
They created a daily trivia chatbot that’s powered by content from the Almanac, with the obvious (not so obvious) goal of promoting and selling the book to their fanbase on Facebook.
An AI recommendation system is a system that predicts users’ preference of a given item(s) over others, using diverse machine learning algorithms.
AI-powered recommendation systems are at the heart of major tech companies that operate online businesses and offer online products.
Netflix, Google, Amazon, Apple, Tesla, and Alibaba all rely on recommender systems for building a major product or service.
This system is at the core of their marketing strategy.
Take Amazon, for instance, they use recommendation systems to recommend products to their users in a personalized manner.
YouTube itself is a video recommendation system powered by AI and Facebook uses recommendation systems to get users engaged as long as possible.
I go to YouTube almost every day, love the platform generally, and this is not because I saw a great ad urging me to return every day. I think personally, it’s down to their amazing recommendation system.
Anytime I go to YouTube, I know there is some personalized video waiting for me to consume. I am compelled to watch some ads at times; some I skip after a few seconds and others are short and am compelled to watch to the end.
By going to YouTube and watching videos there every day, YouTube is making money off my activities on daily basis. And the only visible marketing they did that’s making me come back was just their recommendation system.
That’s how powerful recommendation systems can be.
Here are two major ways recommendations systems are used in marketing:
These are mostly adopted by eCommerce sites, where physical products are recommended to users based on different metrics that suggests user will be interested in the product.
Product recommendation is not new in marketing, it has existed long before the internet. Years back when I was a salesperson for a local boutique.
I remember that when a customer buys some clothes, I do tell the customer something like ‘these shoes will match those clothes, you know’ and that’s product recommendation 101.
In most cases, after further persuasive talks, the customer ends up buying the clothes and the recommended shoes. You can call that ‘sales’, but ‘sales’ and ‘marketing’ are intertwined, though, there is a distinct difference between the two.
AI product recommendations can be seen applied on Amazon.com and BestBuy.
Instead of recommending products, content is being recommended; that’s content recommendation. They involve the algorithmic recommendation of video, textual, or graphical contents.
Examples of online content recommendation systems are YouTube, Google Discover, and even Spotify. Content recommendation systems can be applied to up content marketing strategies and efforts.
Advantages of Recommendation Systems in Marketing
Improved customer engagement and satisfaction: Recommendation Systems gets customers engaged with a business’s product or service, by offering a personalized experience to users. In turn, well-engaged users end up satisfied.
This is true either for product or content recommendation systems.
- Leads to More Conversions: More engaged and satisfied users (customers) leads to more conversion for businesses. And that’s a no-brainer.
- Increases the rate of Returning Customers: These things work hand in hand. When customers make purchases as a result of high engagement and satisfaction, they are most likely to return to make other purchases in the future. And that’s one of the reasons why people keep coming back to buy from Amazon and renew their subscriptions on Netflix and Spotify.
- Increases Cart Value: Maybe the customer came around to buy clothes, but as a result of an AI-powered recommendation system, they end up buying the clothes + shoes. Boom! Increase in cart value ($$$).
- The System gets better: As old wines get better with age, so do AI recommendation systems. The more user activity goes on, the more recommendation systems get better. And the ‘circle of better’ continues; better recommendation systems, better engaged and satisfied customers, better conversions for businesses, better (increased) cart value, and better (more) returning customers/users.
Artificial intelligence marketing is just getting started and so is this article. Expect more updates to the article as there will be more advancements in Artificial intelligence marketing.
I’d be looking forward to touching on AI email marketing, how AI is affecting SEO and VSO, and Social media marketing.
For now, browse around, subscribe to stay tuned, and leave a comment down below if you have any questions, contributions, or observations.
I’m a Technology Stock Analyst, with focus on companies developing cutting-edge techs. Keeping track of cutting-edge techs, companies and stocks is what I do almost everyday. And I love it. Whether it’s artificial intelligence, 5g, or autonomous vehicles; I’m all in.