The Application of AI in Marketing, Advertising and Media Buying
Chat GPT. Bard. ERNIE Bot.
While AI has recently made headlines for its potential to transform marketing and advertising, AI technology is far from new to the industry. In many ways, it already has transformed marketing, playing an influential role in the field since the early 2000s.
By 2020, 50% of companies used AI in at least one business function, but especially for service operations, marketing, and sales. Two-thirds of companies using AI said its use increased revenue, and companies with greater AI adoption also reported better leadership and stronger business results.
But in the last few years, the use cases for AI have exploded as technology has advanced and companies have grown more familiar with its capabilities. Today, AI-based tools are used to improve outcomes and speed up processes across countless marketing activities, from ad targeting to personalized content creation.
Technology starts recommending your next purchase.
In 2003, Amazon published a paper on “collaborative filtering.” The company had begun recommending books to customers based on clusters of behavioral data. Technology reviewed and organized past customers’ actions. This data was then interpreted and used to predict future behavior.
As consumers, receiving product or content recommendations through technology is now almost unremarkable. Netflix suggests the next show you may be interested in—a comedy by the same producer who created your favorite comfort watch. An ecommerce retailer shows you a scarf that perfectly matches the jacket you just added to your virtual cart.
Personalized suggestions based on an individual’s preferences and interests, often gathered from websites and social media, ensure users access relevant content. Ideally, this creates a better customer experience.
Basic automation tools gain popularity for email marketing.
In the early 2010s, businesses were already experimenting with automation for email marketing campaigns. Technology could help schedule when emails were sent and identify deliverability issues.
Since then, the artificial intelligence behind these early tools has developed significantly and is now commonly used within many companies’ sales and marketing departments. Today, AI can write email subject lines personalized to individuals, identify the best contacts, and even craft sales messages.
AI becomes everyone's favorite content creator.
In 2011, IBM’s Watson computer competed on Jeopardy against two previous show winners. Watson won, and while the show was fascinating, it was also evidence of a technological breakthrough. AI could now process complex requests and draw answers from unorganized information.
Over a decade later, the implications of this breakthrough are impressive for content marketers, graphic designers, and even software engineers. By typing a request into a tool like Chat GPT, copywriters can receive a first draft of their next blog post. After providing a prompt, designers can quickly generate visuals for testing different creative concepts. Software engineers can gain lines of code.
However, as many have noted, AI doesn’t seem ready to take over content creation entirely. It still requires a human to guide strategy, ensure accuracy, and monitor quality. (Even Chat GPT admits it’s still evolving).
AI chatbots improve the customer experience.
An early example of a chatbot is SmarterChild, a digital assistant included on the desktop version of AOL Instant Messenger. It could find information on topics ranging from the weather to movie showtimes.
As time passed, the questions chatbots could answer became more complex. And after incorporating AI into chatbots, their value skyrocketed. Businesses began using chatbots to answer questions usually fielded by customer service representatives. This not only freed up people to focus on complex issues but allowed customers to receive help more quickly.
And that’s just scratching the surface of chatbot use cases. Our own chatbot, Abbot, has provided personalized, interactive experiences for businesses across multiple industries to help remove purchase barriers.
Digital advertising gets smarter and faster.
It's been years since Google introduced using AI to improve digital ad targeting. By analyzing consumer demographics, interests, and behaviors AI could help brands show the right ads to the right people. Advertisers found themselves saving significant time researching their target audiences and where to reach them.
But by 2014, programmatic ad buying was streamlining processes even more for digital advertising. AI eventually began managing advertiser budgets, automating bids, and monitoring results. Its decisions were based on the goals for each specific campaign. Now it can even help run A/B tests more efficiently. And predict which ads will resonate most with different audiences.
AI automates TV media buying.
Programmatic buying isn’t just for online advertising. AI can also be used to identify high-value TV media buys. This starts with analyzing massive amounts of data gathered from multiple sources. This can include a brand’s own first-party customer data, historical performance results, media marketplace trends, and more.
For a human, that’s an essentially impossible amount of data to process, especially within a timeframe that would allow for speedy and effective decision-making. Because even if a human did calculate all that data to identify a valuable buy, the opportunity could be gone by the time a conclusion was reached.
With AI, marketers can rely on technology to identify and recommend buys with the greatest opportunities for advertisers. However, like in other areas of marketing, humans have remained important for guiding strategy. People can account for less tangible objectives that AI might overlook, like the prestige that comes with showing up on a particularly well-known network, even if it is a more expensive way to reach an advertiser’s target audience.
Meet the TV media-buying AI, Annika.
With access to an exclusive rate class, Annika has bought and optimized media for TV advertisers for nearly five years. She’s grown smarter every year (and technically, with every buy).
Programmed with each advertiser’s unique performance criteria and target audience, Annika analyzes billions of data points to find the best buys across linear and streaming TV for that individual brand.
In 2022, she recommended 55,000 media buys and two million airings for Marketing Architects’ clients. Based on performance, she made 90,000 optimizations over the year. And she saves our media team around 4,700 hours in manual labor annually.
But most importantly, Annika dramatically improves campaign performance for TV advertisers. So between Annika and Chat GPT, our favorite AI is Annika... but we are a little biased!
Want to learn more about using AI for TV campaigns?
Listen to this podcast episode to learn how our media-buying AI, Annika, makes sense of an incredibly complex media landscape. (Plus hear a cameo from Annika herself.)