Today, AI is everywhere. It powers voice assistants, email service providers, financial processes, medical diagnostic technology, and self-driving cars.
But this is just the tip of the iceberg. The market—currently valued at $119.78BN—will increase almost tenfold in the next seven years.
And in case you hadn’t noticed, it’s taking over marketing too.
Let’s take a deep dive into how AI is transforming marketing, explaining its top use cases and providing actionable tips to help you become an AI-powered marketer.
So grab a coffee, sit back, and take it all in.
Table of Contents
- Why AI is taking over the marketing function
- Why marketers can’t afford to ignore AI
- How can marketers use AI?
- 5 reasons to be positive about marketing AI
- The 5-step process to becoming an AI-driven marketer
- Final thoughts
Why AI is taking over the marketing function
AI will fundamentally transform how companies market themselves. It has already started to have an impact—you probably already rely on a few AI-based tools.
However, we’re only just entering the beginning of the AI era in marketing.
McKinsey suggests companies will gain the most revenue benefits from AI by using it to boost their marketing and sales functions. Harvard Business Review states, “Of all a company’s functions, marketing has perhaps the most to gain from artificial intelligence.”
And it’s easy to understand why.
AI can process, analyze, and utilize vast swathes of data exponentially quicker than people can. It’s even becoming increasingly creative—just ask Dall-E to produce an image of Donald Duck playing ping pong.
As we reach the hockey stick growth phase of AI adoption, marketers have three choices:
- To bury their heads in the sand and ignore AI’s inevitable rise
- To adopt a lukewarm approach, using the occasional AI-based tool but not developing any rich personal expertise
- To go all in, making AI their greatest ally
If you’re reading this, you’re likely in category C. Or perhaps you’re not quite there yet. If that’s the case, this guide will hopefully explain why you must be.
As the old adage goes, “If you can’t beat them, join them”. Unfortunately, you won’t be able to beat AI—at least not at its own game. The goal, therefore, must be to identify how you can use it to your advantage.
That’s where we can help.
Why marketers can’t afford to ignore AI
Ignoring AI is perhaps the worst thing marketers can do, both for their short-term success and long-term career prospects.
Disruptive technology shatters the status quo. Just ask Kodak or Blockbuster. If you fail to keep up with the rise of AI, you’ll soon become obsolete.
Here’s why.
- Your company will be at a competitive disadvantage
Companies that don’t adopt AI will inevitably fall behind their competitors. They’ll be slower, less accurate, and will require more resources to get the job done. Over time their more agile and AI-enabled competitors will carve out an unsurpassable competitive advantage.
- You’ll provide a subpar customer experience
AI tools help marketers create highly personalized marketing campaigns, generating higher engagement and conversion rates. Ignoring AI will hamper your personalization efforts. In turn, you’ll miss out on a key opportunity to connect with customers.
- You’ll miss key insights from ever-increasing datasets
We’re producing more data than at any stage in human history. This is both an opportunity and a challenge. Companies that harness, analyze, and utilize customer data will unearth precious gemstones to fuel their marketing success. However, doing this at speed requires AI—there are no two ways about it.
- Your career will take a hit
Marketing is evolving at an exponential rate. If you ignore the trends that will define the industry’s future, such as AI, your days are numbered.
No company wants to hire a marketer stuck using yesterday’s techniques and tools. They want someone who can keep up with (and even lead) the pace of change.
How can marketers use AI?
Before we dig into the potential marketing AI use cases, let’s first provide a framework for assessing marketing AI tools, courtesy of Harvard Business Review.
As you already know, not all AI tools are the same. Duh. They each have their own strengths and weaknesses, use cases and price points.
That’s why Harvard Business Review has split them up into four quadrants: stand-alone machine-learning apps, integrated machine-learning apps, stand-alone task-automation apps, and integrated task-automation apps.
Once you understand which quadrant applications fall into, you can more effectively plan and sequence the introduction of new tools into your marketing mix.
For example, it might be worth starting small, integrating stand-alone task-automation apps as a first step. These don’t require complex set-up processes, and they’re pretty easy to use.
If you just want to test the waters of marketing AI, or convince senior leadership that it’s worth investing in, consider starting with one of these types of tools. You can then look to integrate increasingly complex and interconnected tools moving forward.
Right, enough top-level theory—let’s dive into the most effective use cases for AI in marketing.
Audience segmentation
Before marketers can serve personalized experiences, they first need to segment their audiences. You already know this—but you might not know how AI can help.
AI-based tools power segmentation by identifying key patterns and trends in customer behavior. There are four main ways they do this: clustering, supervised learning, unsupervised learning, and natural language processing (NLP).
- Clustering
AI uses customer data to group prospects and customers by their demographics and preferences. For example, it might create segments according to a customer’s income, location, job title, or more.
- Supervised learning
Supervised learning is when AI-powered algorithms learn from labeled data, such as past customer behavior and purchases. It can then use this to identify customers with the highest lifetime value, showing where you should focus your efforts.
- Unsupervised learning
Unsupervised learning, on the other hand, is when AI discovers segments without predefined labels. Algorithms do this by identifying patterns and correlations within the data.
- Natural language processing (NLP)
NLP refers to the process of analyzing unstructured customer data, such as customer feedback or social media posts, to identify customer segments based on their interests, opinions, or attitudes.
An example of AI-powered audience segmentation
Deloitte provides the following example:
‘A travel clothing retailer who divides its customers into avid camping holiday lovers and hikers can use AI segmentation to identify many specific types of customers.
AI can help him identify a group of “lux-campers” looking for comfortable tents and a high level of comfort, or “trail enthusiasts” who buy the most technically advanced equipment.
Once identified, it can apply individualized campaigns to them, emphasizing the advantages of a travel coffee maker useful to “lux-campers”, or a new watch with GPS, which will find recognition among “trail enthusiasts”.’
Personalization
AI allows marketers to personalize their messaging and recommendations based on customers’ behaviors, preferences, and demographics.
It’s particularly adept at helping marketers identify the appropriate strategy, tweak their messaging, and determine pricing.
Strategy
AI-powered predictive modeling uses historical customer data to generate predictions about how customers will behave in the future.
It provides key insights into which customers are most likely to make a purchase, which leads are most likely to convert, or which customers are most likely to churn.
You can then use these insights to tailor your approach to each group. For example, if a customer is about to churn, consider offering them a special discount as one of your valued customers.
But that’s not all.
AI can also analyze customer data and browsing history to provide consumers with personalized product recommendations.
You’ve probably seen this before. One second, you’re browsing through Star Wars-themed socks on your phone’s Instagram app (because you’re a cool marketer, right?).
After 10 minutes, you close Instagram and return to work. Only, the second you fire up your browser, what do you see? Banner ads about Star Wars-themed socks.
Messaging
We naturally alter our communication depending on who we speak to. It’s human nature to reflect people’s own styles of communication back to them.
Of course, communication preferences vary greatly. Gen Z and Millennials might love slang and emojis, but older consumers generally prefer more business-like tones.
This is where NLP can help. Marketers can use AI to identify which tone of voice works best for which customer segment before personalizing your messaging accordingly.
Pricing
AI can even help marketers identify the right pricing strategies to use. For example, one automotive company uses AI to personalize the offers it sends prospects and the prices it charges them.
Wow. Imagine paying more for a product because an AI model has determined you’re a sucker. Ouch.
An example of AI-powered personalization
Intellimize helps Tableau turn “static, one-size-fits-all websites into adaptive learning websites that optimize and personalize the experience for every single visitor in the moment.”
As Bryan Law, SVP Marketing and GM of Ecommerce, Tableau, explains, “What Intellimize brings to the table is the understanding that not every visitor to our site is the same… Intellimize can recognize and capitalize on this opportunity to show each web visitor a personalized experience that is best for them. Further, the platform can run many simultaneous tests, and will perpetually optimize the site experience as our visitors change over time.”
The results are staggering. Since implementing Intellimize, Tableau has generated a 2X increase in conversion rate and 9:1 ROI.
A/B testing
A/B testing is like crack for marketers. There, we said it.
As soon as you’ve completed one A/B test, you’re onto the next one. “Oh but can we just test this one last thing,” you say, promising it’ll be the last for at least a week. Lies.
We don’t blame you—A/B testing is amazing. And it’s even better using AI.
AI-powered tools help with every stage of the process. They analyze customer data from multiple sources to inform what you should be testing and why.
Imagine your AI-powered analytics shows that your landing page copy performs more poorly than expected for certain demographics. It’s great at convincing millennials to convert, but boomers aren’t so keen.
Damn boomers.
With this in mind, you go back to the drawing board, leveraging AI tools to create a few different boomer-friendly alternatives. Armed with these new iterations, you use AI to specifically show this copy only to boomers who visit the landing page.
The AI will then collect the results and demonstrate which is more effective. In fact, if it uses the multi-armed bandit (MAB) algorithm, then it will automatically prioritize the most effective version.
An example of AI-powered A/B testing
Optimizely users can take advantage of the tool’s MAB capabilities to “intelligently change the traffic allocation across variations to achieve a goal.” This means the algorithm will automatically prioritize statistically significant variations—in other words, that perform the strongest.
Imagine you’re launching a new newsletter signup landing page, but you don’t know which copy to use. You’ve heard that long copy sells, but your instinct is to keep the text short and sweet. Should you include images? How about Gifs?
You create multiple options, launch them, and let the MAB algorithm do its thing. Automatically, it will begin to prioritize the version that works best, meaning you can sit back, relax, and watch the results pour in.
Customer service
AI first made its marketing chops with chatbots. While chatbots aren’t perfect, they’re pretty damn effective. If your company’s serious about its customer service, then you’ve probably already got chatbots on your site.
It’s easy to understand why.
Using NLP, chatbots understand and respond to customers’ requests. Even if they can’t answer their questions directly, chatbots can signpost customers to helpful resources or allow them to raise the query with a human agent.
Best of all, they never take a day off, can operate in multiple languages simultaneously, and can handle a torrent of vitriolic customer abuse without any apparent deterioration in performance.
What’s not to love?
But chatbots aren’t the only way AI powers top-tier customer service. AI also automates repetitive tasks such as data entry and ticket routing, meaning human agents can focus on more complex interactions.
AI can even provide real-time suggestions and information while a human agent chats with a customer. And, AI transcription tools can record customer interactions before using NLP to classify the call: customer sentiment, what the call was about, agent performance, and so on.
An example of AI-powered customer service
Global pizza chain Domino’s uses AI to give customers real-time predictions about when their order will be ready. Their load-time model factors in labor variables, order complexity, and any other relevant operational factors to produce 75 – 95% accurate predictions.
But that’s not all.
Domino’s also uses AI chatbots to interact with consumers via Facebook Messenger, making it as easy as possible for customers to order a pizza, leave a review, and more.
Content creation
Source: Cheezburger, ‘Funny Tweets About ChatGPT, the New and Advanced AI Chatbot’
Unless you’ve been living under a rock for the past few months, you’ll know all about AI content creation. Chat GPT has taken the industry (and our LinkedIn timelines) by storm—but it’s far from the only tool out there.
Marketers can now use NLP-driven AI to create pretty much any type of content: blogs, guides, email lists, diss tracks (in case the sales team needs to be put back in its place), landing pages, etc. It’s worth also highlighting that AI doesn’t just create text-based content—you can also use tools like Dall-E to generate images in seconds.
Is it perfect? Not always, but it’s getting better every single day. It’s only a matter of time until AI tools are marketers’ very own Hemingways. Well, without the crippling alcoholism.
As things stand, AI content creation is a great way to cut down the time to a first draft or to spark ideas. You might not be able to use the content it spits out verbatim/without tweaks, but it’s a fantastic way to generate quick ideas, create outlines, and do the boring pre-work before you can start messing around with your syntax.
An example of AI-powered content creation
For this example, we decided to take things in-house. I asked ChatGPT3 to “Write me a poem about why marketers should embrace AI”.
Here’s what it came up with.
“Marketers must embrace AI with open arms,
For it can bring them many new charms,
Data that was once hard to find,
AI can now analyze and grind.
Gone are the days of guesswork and trends,
AI can now deliver precise results and bends,
Customer insights and behavior so clear,
Marketing strategies can now be well tailored.
It saves time and increases efficiency,
Helping you reach your goals with clarity,
Making informed decisions, no more delay,
Embracing AI, watch your brand grow day by day.
So let us embrace this technology bright,
And use it to make our marketing shine bright,
For the future belongs to those who adapt,
And AI is the key to a marketer’s success script.”
Not perfect, but not bad. It’s about as lyrical as most of today’s rappers tbh.
Market research
Using AI for data collection and analysis transforms market research.
AI-powered social media listening and web scraping tools rapidly gather vast quantities of data from a range of sources. Then, AI-powered data analysis processes large quantities of data to identify patterns and trends that would be difficult for humans to spot.
AI tools are far quicker and more effective at data analysis than people are. Duh. But AI isn’t just great with numbers—it’s also surprisingly effective at picking up how consumers feel.
AI-powered NLP understands and interprets customer feedback and sentiment, providing richer insights into customer needs and preferences. Meanwhile, AI-powered machine learning analyzes swathes of data to make predictions about customer behavior, which can inform future marketing strategies and improve decision-making.
Oh, and it can do so in multiple languages, simultaneously. Showoff.
An example of AI-powered market research
Zappi uses AI to help some of the world’s biggest brands—from PepsiCo, to McDonald’s, to Heineken—with their market research. It works as follows.
First, a client comes to Zappi with an idea, such as for a new advert. They have a few different variations but aren’t sure which one will resonate the best with their target audience.
Zappi then brings that concept to consumer-panel organizations, loads the panel data into the Zappi system, and uses AI to validate that the panel respondents match a pre-specific set of criteria. In other words, ensuring they accurately represent the organization’s target audience.
The Zappi system then analyzes the data the panel produces using AI. What’s more, the system also integrates market data AI models to more effectively predict new products’ potential market success.
Advertising
‘Half the money I spend on advertising is wasted; the trouble is I don’t know which half,’ said John Wanamaker. Shame he didn’t stick around til the AI era.
AI optimizes every step of the advertising journey. AI-based algorithms analyze massive amounts of data to better understand consumer behavior and preferences. Advertisers can then create more personalized and relevant advertising experiences, unlocking higher conversion rates and greater ROI.
Additionally, AI technologies like Ml and NLP also enable real-time bidding. Companies can therefore optimize ad placement and delivery in response to how their target audience behaves.
An example of AI-powered advertising
Consider the example of Accenture, which joined forces with an American retailer to design a custom AI-powered solution.
The goals were simple: to enable quicker and more accurate data collection, and to power enhanced modeling to optimize media spend.
It set to work speeding up the data flow process before aggregating and processing data from all media channels, sales, and spend figures.
The results were astounding:
- Unlocked $300 million in media buying opportunities;
- Cut data aggregation processes by 80%;
- Slashed the lag between the measurement period and performance insights from five months to five weeks;
- Opened up a 10-and-a-half-month planning runway for the same period the following year;
- Provided more nuanced insights, allowing teams to measure how channels’ performance varied throughout the year.
AI tools can even gently nudge consumers along the funnel based on their previous behavior.
That’s why Wayfair targets users in the ‘consideration’ stage of the buying journey. It uses AI to “determine which customers are most likely to be persuadable and, on the basis of their browsing histories, choose products to show them.”
5 reasons to be positive about marketing AI
AI will revolutionize marketing.
That said, not all marketers will generate the same value from AI. Those who welcome it with open arms, accept it’s here to stay for the long run, and commit to learning all about it will thrive.
However, those who ignore it will lose their companies’ market share, competitive advantage, and maybe even their jobs.
We can’t force you to be positive, but we can try to convince you why AI is a good thing for marketers… So here goes.
- You can do more with less effort
Here at AI Marketing School, we’re massive fans of the Pareto Principle (aka the 80/20 rule). Simply put, it means roughly 80% of your results will come from 20% of your efforts.
Think about it for a second. Your company probably generates 80% of its revenues from 20% of its customer base. 20% of your team/company is probably responsible for 80% of all productivity. You probably get 80% of your life’s fulfillment from 20% of your time (living for the weekend amirite?).
AI is the ultimate 80/20 tool. It can segment customers, identifying the 20% who contribute 80% of revenue. Or it can analyze completely new customers/existing prospects to determine which will generate the greatest LTV. It can also assess existing strategies to show which are worth continuing, and which you should scrap.
Quit wasting time and effort on low-performing efforts. Focus on what moves the needle, not on what you think you should do. Do you find that your accounting practice generates significantly more leads via TikTok than from direct mail? If so, go all in on TikTok.
AI can also tackle the time-consuming tasks that take 80% of your time but only produce 20% of your results: data analysis, social listening, and so on. The 80/20 rule is only an approximate ratio. However, the crux of this point is that AI helps you identify ways to achieve more with less.
Focus on doing things that have the highest ROI, and automate the rest.
- By learning about AI early, you’ll give yourself a competitive advantage
Get ahead of the game. AI is coming—there’s no point ignoring it.
Commit to learning everything under the sun about AI in marketing. Get to grips with new tools, read interviews with leading figures, and make your AI knowledge your competitive advantage.
If you do, the results will be transformative. You’ll create better strategies in less time, leading to better results. You’ll get recognized by senior leadership and promoted—meaning you’ll grow your career at a rate of knots.
AI will never replace you because you’ll always be one step ahead of the game.
- AI is transforming every other industry for good
AI has permeated almost every industry over the past few decades. Consider the following examples:
- Healthcare: Improve diagnostic accuracy, streamline administrative tasks, and accelerate drug development.
- Finance: Identify fraud, predict stock prices, and provide personalized financial advice to customers.
- Manufacturing: Optimize production processes, enhance quality control, and reduce costs.
- Energy: Boosting the efficiency and performance of power generation and distribution systems, predicting equipment failures, and optimizing homes’ energy consumption.
This is just the tip of the iceberg. AI tools have made countless industries better—so why not marketing? Why would marketers not want to unlock greater efficiency, accuracy, and performance?
- It’ll only automate sh***y jobs
AI can do some pretty cool stuff. That said, its main use cases are for tasks that humans don’t want to do/can’t do nearly as quickly or effectively. For example, like:
- Analyzing thousands of data points
- Creating first drafts
- Responding to routine customer queries
- Content moderation
And so on.
You’ll notice that many of these tasks are quite, how should we put this, dull. They’re data-heavy and routine. Even the process of creating first drafts relies more on ensuring you hit the right points rather than adding any sort of finesse.
So, the fact that AI thrives at these dull jobs is a lifesaver.
People aren’t machines. We like novelty and to be challenged—we don’t like tedium. Doing the same tasks daily bores us out of our minds. We become unhappy, frustrated, and make mistakes. We lose our passion.
But AI doesn’t.
It’s happy doing the same sh** again and again. It doesn’t feel like it’s wasting away its life—it doesn’t have a life. Or sentience. Well, yet…
Use AI to handle tasks you hate and spend more time doing what you enjoy. Use your brainpower wisely, reserving it for making important decisions.
As HBR puts it, “As companies become more sophisticated in their use of marketing AI, many fully automate certain types of decisions, taking humans out of the loop entirely. With repetitive, high-speed decisions, such as those required for programmatic ad buying (where digital ads are served up almost instantaneously to users), this approach is essential.”
- While giving you more time to be creative…
Generally speaking, marketers are pretty creative folks. We appreciate snappy slogans, attention-grabbing ads, sleek branding, and the like.
But marketing today is as much art as it is science. Creativity’s great, but what do the numbers say? You’ve only got so much budget to spend—meaning ROI matters more than artistic expression. When there are only 8 hours in the working day, data analysis will take up more of your time and energy than playing around on Canva.
With AI, however, you can flip the script.
Use AI tools to automate repetitive tasks: data entry, analysis, report generation, etc. Spend less time getting to the insights and more time using them to inform your creativity.
We’re not saying AI is some sort of magic wand—you’ll probably still have to look at datasets from time to time. However, by using AI tools correctly, you can direct most of your attention towards creative tasks that you genuinely enjoy.
The 5-step process to becoming an AI-driven marketer
Right, enough of the theory—let’s explain how you can use AI to build your dream career in marketing.
- Be an early enthusiast. Love AI like it’s your first child/puppy/car
It’s hard to get behind something you don’t care about. That’s why it’s vital you learn to LOVE AI.
See it as your pathway to a better future. It’s the assistant you always wished you had, your right-hand robot buddy who’ll do all the horrendous jobs you can’t be bothered to do. It will never take a day off, will happily work overnight if you let it, and is always ready to take orders.
Imagine having someone on your team who was like that in real life. You’d cherish them like they were your first child/puppy/car. You’d do anything possible to help them, knowing they’re always there for you when you need them.
Think of AI in these terms. It’s not coming to take your job—it’s coming to make you better at your job.
- Rinse free trials
You need to know which tools are right for YOUR BUSINESS, YOUR TEAM, and YOU AS AN INDIVIDUAL.
There’s no single best tool for everyone. Each software has its advantages and limitations, so you need to work out what’s right for your needs.
This requires testing. Lots of it.
Almost every single decent AI tool offers a free trial period. Use it and document your progress, such as:
- What you did
- How easy it was to use
- Whether it lived up to expectations
- How much it usually costs
Do this for every single trial.
At the end, you’ll be able to map out which tools are right for your business and team. Consider creating an all-in-one spreadsheet-based metric to track and rank the different tools.
Then, invest your company’s money wisely in tools you love, and that you know work. It’s that simple.
- Do the work (and always keep on learning)
You might be thinking; “Wait—I thought AI was going to do all the work? You’re saying I can’t just lie around watching The Office for the 3,489th time?”
No, not exactly.
AI will do the bulk of the work, but it still needs direction. Think of it like a sheepdog. They’re far better at rounding up sheep than you’ll ever be, but you need to tell them which sheep to round up and where to put them.
Weird analogy, I know, but I grew up on a farm. Can’t you tell?
All this means one thing: you need to do the work. You have to put in the hours. Try different tools, learn what they can and can’t do, and work out which ones are best suited to your needs. Then, figure out how to use AI to drive the greatest efficiencies within your existing processes.
This is where you can create a genuine competitive advantage over other marketers.
While they’ll be slow to adopt the tools or use them in basic ways, you’ll know the precise ins and outs of each tool. You won’t give it tasks that it’s not great at, but you’ll only use it for tasks that it can handle better than your colleagues. You’ll understand its immense value while bearing in mind its intrinsic limitations.
But we have a warning—don’t ever think you’ve ‘made it’. Complacency could well be your downfall.
The rate at which AI will improve will only increase from here on out. If you sit back, relax, and ignore the landscape for even a few months, you might quickly fall behind.
Stay humble and keep learning.
- Get senior leadership on board
You must get senior leadership on your side. We certainly don’t recommend brown-nosing (ew), but we do recommend gently reminding upper management that AI will help your team do more with less effort.
Start by scraping together as many case studies or real-life examples to show how AI boosts ROI. If you can show how spending $10 on a tool leads to $100 of revenue, senior leadership will hand you the company card then and there.
This is even more prescient given the state of the economy.
Most companies are pausing hiring or downsizing—but they want to maintain (or increase) profits. Is that too much to ask for? Not necessarily.
If you clearly show how AI will allow you to do more with less, then senior leadership will support your AI endeavors to the moon. You don’t have to explain how the tools work—you just need to state how they help.
- Remember its limitations
AI isn’t a panacea. It’s not the answer to everything. Instead, it’s just a tool.
The best marketers will be those who understand the best results come from AI AND people working together. Calculators didn’t spell the end of mathematicians. Implementing autonomous taxi and take-off capabilities definitely improved the aviation industry—but pilots still exist for a reason.
For the time being, at least, people will still need to control AI—to push the buttons, set the tools’ directions, and make sense of the answers. Don’t think AI can do everything. At least, not yet.
It’s incredibly valuable, provided people use it correctly. It’s far from a complete cure-all.
Final thoughts
Congrats, you’ve made it to the end. We hope this guide has informed and perhaps even entertained you. Most importantly, we hope it’s imbued you with a passion for using AI to take your career to the next level.
AI is both an opportunity and a crisis, depending on your viewpoint. Marketers that jump on board and commit to creating an AI-powered future will thrive. Those that ignore it entirely, or can’t be bothered to take the plunge, will soon become irrelevant.
The choice is yours. We certainly know which direction we’re heading in.
So good luck, keep experimenting and have fun. Let’s see what the future holds in store.