AI in Marketing: Strategies, Examples, and Everything You Need to Know

Back in 2018, Lexus released what is known as the first ad ever scripted by AI in marketing. It used IBM Watson to analyze 15-years of “luxury brands and cars campaigns that have won Cannes Lions creativity awards and ranges of several other external data (1).” Yes, for those wondering, Watson did find elements that best resonate with the audience from the dataset.

Since then, there has been a colossal surge in the use of AI for marketing purposes. Businesses are building more effective marketing strategies and changing how they attract, engage, and convert their target audience with advancements in AI concepts like machine learning (2).

AI, Artificial Intelligence enables marketers to leverage customer data to anticipate their next move and help improve the overall customer journey.

AI in Marketing — Source: Smart Insights

According to Salesforce (3), there has been a 186% Y-O-Y growth in using artificial intelligence for marketing, with the total number of marketers using AI surging to 84% in 2020 from a mere 29% in 2018.

In addition, a forecast from IDC suggests that by the end of 2021, the global spending on AI software, hardware, and services may have increased to over 340 billion USD (4).

And all of these point to a more important and deeper story, AI is the future of marketing.

AI has the potential to transform the advertising world at every level, from audience targeting to ad creation to final purchase. Notably, today, almost every online ad firm uses machine learning, a core AI tech, to determine whether users will click on an ad. It is only one of the many use cases.

There are dozens of AI use cases in the marketing industry with brands using the technology to find and segment target audiences, build creative ads, improve the overall performance, and speed optimization, at scale, in real-time, with minimal to no human involvement.

In other words, AI has a profound impact on your brand’s competitive advantage.

How is AI Transforming the Digital Ad Industry?

First, let’s get clear that artificial intelligence is not just a phrase for one technology. Instead, it is an umbrella term used for a wide range of machines that learn (either with the help of us humans or on their own). It allows AI technologies to perform certain cognitive tasks similarly or even better.

“AI is the science of making machines smart,” said Demis Hassabis from Google DeepMind. And we believe it to be one of the best definitions of explaining AI (5).

Some AI technologies you may have already heard about include:

Machine Learning
Computer Vision
Natural Language Generation
NLP; Natural Language Processing
Neural Networks
Speech Recognition
Deep Learning

None of these technologies are futurist; in fact, you are already using them in your everyday lives without even realizing it.

For instance, we use Google Docs to write our articles at TimesNext. It uses AI to read what we type, understand it enough, and recommend what to type next using Smart Compose. Google also uses similar technology on its Gmail (6).

Meta’s Facebook also uses AI to detect people in your photos and recommends who to tag. Autonomous cars use AI to detect obstacles and help us drive effectively and safely with (hopefully soon!) no human errors.

Google Assistant or Siri in phones uses AI to understand our voice commands and offer sensible responses in return.

There are also smart home products like Ring (cameras) and Nest (thermostats) that use AI to sense changes in their observable environments to take action based on what makes sense.

Long story short, AI is transforming every industry, from finance to healthcare, retail to entertainment, at a dramatic pace. And the story for the marketing and advertising industry is no different.

Along the way, it offers unprecedented revenue opportunities and helps businesses save costs significantly. In short, AI plays an important role; in taking our digital marketing revolution to the next level.

Today, customers expect brands to deliver ad communications on their terms, which requires businesses to depart from their usual strategies.

“A well-done advertising is no longer a game of volume per unit price. It has now evolved into a targeted and intelligent offering that serves customers’ needs. It also offers customers the control they have been asking for and has increased the effectiveness of the ad in a way that traditional ads have only dreamed of until now,” noted Adweek (7).

AI in Marketing MakeThings Better

We, humans, are excellent at communication, and we do not doubt your ability to send personalized messages in one-on-one context with people. Or we may also include tens of people like your friends, family members, coworkers, etc., in communicating with them in a way that allows them to respond to it most effectively.

Could you set those messages at scale for thousands or millions of people? Maybe, but we humans don’t have the time or resources to do it. However, an AI system can.

It even has several advantages over our traditional software. Of course, it can process a huge amount of data and offers excellent clarity to marketers. However, when it comes to offering context about the data, they disappoint.

On the other hand, AI technologies are “smart.” They can analyze data and even make predictions about that data’s meanings.

For instance, a CRM system with all your contacts powered by an AI would have the same data as traditional software. Except, it would also recommend which leads you can more likely close, who you should contact next, and how to score leads.

Below are some great use cases for AI that marketers can use for their campaigns.

Writing and Testing Ad Copy: eBay, Chase Bank

Since 2016, the global ecommerce marketplace, eBay, has been working with an AI-powered customer experience platform named Phrasee to enhance its email marketing copies (8).

AI in advertising — How Phrasee approaches AI content creation and optimization, Source: Phrasee

Optimizing their email marketing performance is a relatively simple task for an average brand.

It primarily includes A/B testing of different subject lines and CTA. However, things are trickier for a company with eBay’s scale.

Phrasee built language models for eBay, which allowed the company to make custom copies that align with its brand voice and customers’ needs, and specific promotions at a click of a button.

Since they have teamed up with Phrasee, eBay has witnessed several improvements in its email marketing campaigns, including (as per the data published in 2020):

↑ 15.8% average open uplift
↑ 31.2% average click uplift
700k+ incremental opens per campaign
56k+ incremental clicks per campaign

Another example we found was Chase Bank using AI to achieve more humanity in its copywriting.

In 2019, Chase Bank signed a five-year deal with a New York-based company, Persado, that applies AI to marketing creative (9, 10). And after testing its solutions, Chase found that using ML in copywriting helped them achieve more humanity in their copywriting and overall marketing campaigns.

For instance, one digital ad written by a human read: “Access cash from the equity in your home.” Whereas the version from Persado read: “It is true – You can unlock cash from the equity in your home.” The latter performed better with people.

AI in Marketing to Find Trends: Ben & Jerry

When it comes to finding trends using AI, the best example that comes to our mind is how Unilever helped Ben & Jerry to find the trend for “Ice Cream for Breakfast.”

While using its AI data centers which helps Unilever gain insights from various sources like CRM, social listening, and marketing research, it found a link between breakfast and ice cream (11).

The consumer goods company capitalized on this insight by creating a line of cereal-flavored ice creams for the Ben & Jerry’s brand, including Fruit Loop and Frozen Flakes.

Personalized Product Recommendation: Amazon

AI for marketers — Amazon Personalize Process Illustration, Source: Amazon, Venture Beat)

While talking about AI, how can we not mention Amazon, a pioneer in using machine learning to offer personalized product recommendations? However, it has been a challenge for the ecommerce giant to extend its services to businesses that run their sites on AWS, Amazon Web Services.

In 2019, Amazon availed Amazon Personalized, which brought Amazon’s same ML tech to its AWS customers to use in their applications. Since its initial rollout Amazon team has enhanced its functionality to the extent that Personalize now delivers over 50% better recommendations across a range of product types (12, 13).

Notably, brands like Subway, Yamaha, and Domino are already using Personalize to highlight in-store catalogs, musical instruments, flavor recommendations, and other style combinations.

Chatbots: Sephora

According to reports (14), chatbots are witnessing the highest growth of any other brand communication channel. Notably, its usage has increased by over 92% between 2019 and 2020 alone.

Sephora is an early adopter of AI who started using a chatbot to give beauty advice on Kik in 2017.

It helped customers narrow down their choices, starting with a quiz on their product preferences. It is especially helpful in the cosmetic industry since options can be overwhelming, and products often need in-person testing.

Sephora also gained valuable insights and higher engagement with its initial chatbot experiment, leading the beauty brand to launch several more chatbots across social media.

Organic traffic: Tomorrow Sleep

Alright, we understand. So far, we have only offered examples of massive, multinational companies adopting AI. It may lead you to think that only big household names like eBay, Amazon, and Unilever, with multi-billion-dollar revenues alone, can leverage AI benefits in marketing.

However, it is not true at all, as demonstrated by Tomorrow Sleep, a mattress startup (15).

Incepted in 2017, Tomorrow Sleep started its journey with content marketing after a year of its launch. While the company knew that driving organic traffic was crucial for its long-term success, it also realized how its long-standing rivals already had a pretty tight organic search market.

Being a startup, it didn’t have enough scale and budget to build limitless content volumes. Hence it started experimenting with intent-driven terms.

Tomorrow Sleep turned to AI-powered content research, intelligence, and writing firm, MarketMuse, to find the primary and related topics Tomorrow Sleep needed (16). Then, it analyzed the top 20 search results from each primary topic to track any gaps and opportunities.

The results were excellent. Tomorrow Sleep managed to outrange its much bigger competitors like Casper for its key topics and witnessed a massive surge in organic traffic from 4k a month to 400k a month within a year.