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, artificial intelligence 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.

In the last few years, the use cases for AI in marketing 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.

The History of Artificial Intelligence and Marketing

2003: 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. However, the implementation of this technology revolutionized ecommerce and was one of the first applications of AI-based website personalization.

Late 2000s: AI chatbots improve the customer experience.

While people have been researching chatbots since the 1960s (ELIZA was the first chatbot ever published), only in the past few years has their use and application become mainstream.

Today, businesses are rapidly adopting chatbots as their abilities, skills, and value have skyrocketed. Since 2008, businesses have used chatbots to answer questions usually fielded by customer service representatives. This not only frees up people to focus on complex issues but allows 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.

Early 2010s: 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 marketing 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 ideal contacts, and even craft sales messages.

2014: Digital advertising gets smart and fast.

In 2014, AI was introduced to programmatic ad buying which streamlined 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.

2018: Digital advertising gets even smarter and faster.

In 2018, Google introduced machine learning 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.

2022: 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 (released by OpenAI in 2022), 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 in Marketing and Advertising Today

AI has become ubiquitous in digital marketing and is a pivotal tool for businesses to enhance their marketing strategies. Using AI in marketing enables a data-driven approach, personalization, and efficient advertising campaigns. Some examples of how AI is being used in marketing include:

Programmatic Advertising: AI is used in programmatic advertising to analyze vast amounts of data. With its analysis, it can optimize ad buying and placement which increases advertising effectiveness while lowering costs.
Search Engine Optimization: AI is used in SEO by analyzing user search patterns and website data. Not only can AI help webmasters create new content, but it helps Google and other search engines to understand content and surface relevant results to users.
Website Personalization: AI is used in website personalization by tailoring marketing messages to customers based on their past behavior and preferences.
TV Advertising: AI is used within TV advertising to enable audience targeting, automate ad buying, customize content, predict viewer behavior, and measure performance for future optimizations.

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. AI-driven media buying 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.

With AI, marketers can rely on technology to identify and recommend media buys with the greatest opportunities for advertisers. However, like in other areas of marketing, humans have remained important in 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 TV media buys using AI 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 media 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 or contact us to learn how our media-buying AI, Annika, makes sense of an incredibly complex media landscape. (Plus hear a cameo from Annika herself.)