The Science Behind AI in Advertising

Today, the advertising industry is changing at a rapid pace. It can be difficult to keep up with technology that seems to be changing exponentially every fiscal quarter. 

Artificial Intelligence (AI) is one class of technology that is changing the world very rapidly. What is now grouped under the umbrella “AI” term includes the algorithms and machine learning that have been a part of the advertising industry in some way, shape, or form for years. Of course, today, things are a little different.

Many rapidly advancing AI tools are now centered on data science and audience intelligence, analyzing vast data sets and signals much more efficiently than a human can, while providing anonymization for personal information. This power can be harnessed to understand your audience, reach them, and create more personalized experiences.

Here, we’ll expand on the science that drives this advancing technology. We’ll explore:

  • The scientific principles that make AI in advertising possible
  • How predictive analytics work
  • The science behind natural language processing and how it helps advertisers reach their goal
  • And much more

The Growing Presence of AI in the Advertising Industry

Today, consumer behavior has become increasingly complex and difficult to measure, with many fragmented channels providing a vast number of data points that are nearly impossible for humans to parse. Unsurprisingly, AI tools have become more advanced and widespread in response as the technology that powers them advances to address the need for rapid, in-depth analysis. In fact, AI in marketing (i.e., AI advertising) is projected to be a $40.09 billion market in 2025, according to a study by MarketsandMarkets. 

As alluded to above, AI can analyze large amounts of data very efficiently. This allows it to provide invaluable insights that can dramatically improve advertising strategies. It can rapidly analyze:

  • Consumer behavior
  • Consumer preferences
  • Consumer buying habits
  • Ad placements
  • Ad targeting
  • Ad messaging

It also dramatically impacts the industry through:

  • Machine learning
  • Predictive analytics
  • Personalization algorithms

Though there are a few potential challenges, the benefits of this technology are clear. The results include:

  • More efficient ad spending
  • Optimized decision-making
  • Better customer experiences

Why Does the Science Behind AI Advertising Matter?

Personalized advertising is on the rise in today’s digital marketing age. A majority of consumers expect to receive recommendations concerning what they need while casually browsing the internet. 

It’s common to hear commentary on how advertising seems to be “listening,” recommending products consumers were discussing or considering. But this type of anticipated need drives conversions, and understanding the science behind this sort of technology can help you create highly personalized campaigns that target specific demographics or behaviors accurately. 

Understanding AI in Advertising

In this section, we’ll explore some of the fundamentals of AI. We’ll also explore ways your company can use AI in its marketing strategies. 

Fundamentals of Artificial Intelligence

The concept of AI has been around since computers were first invented in the 1940s. Science fiction tales of AI obtaining a mind of its own or even taking over the human race have been circulating for many years.

In its current state, AI is a branch of computer science that attempts to teach a computer to emulate how humans think and act. It uses complex algorithms to:

  • Learn
  • Reason
  • Make decisions
  • Analyze data
  • Identify patterns
  • Make predictions

It’s a multidisciplinary field. Mathematics, computer science, and cognitive science all come together to mimic human intelligence. Today, you’ll find AI being used in almost every facet of society from healthcare to finance to transportation and (obviously) robotics. 

The term “artificial intelligence” was coined by John McCarthy in 1955, who described it as “the science and engineering of making intelligent machines.”

AI can range widely in capabilities. It can be a static algorithm that does the same thing every time. It can also use deep learning and machine learning algorithms to change its behavior. These algorithms can alter how an AI operates dramatically based on feedback from data. 

  • Machine learning involves feeding large amounts of data into a system and learning from it.
  • Deep learning is a type of machine learning. It uses artificial neural networks that operate similarly to the human brain. The system can then change its behavior based on similarities between different subsets of data.

Applications of AI in Advertising

Let’s look at ways you can apply AI in your marketing campaigns.

Predictive Analytics

This is one of the critical applications of AI for advertising. Predictive analytics can forecast trends using:

  • Data mining
  • Machine learning
  • Statistics algorithms

You can use this data to understand consumer behavior and create personalized ad experiences.

This application can help you make informed decisions about:

  • Who to target
  • What messaging to use
  • Which advertising channels to use

It can also make your advertising budget significantly more efficient, boosting the ROI on your marketing efforts.

Specifically, this practice also helps you better reach your objectives by:

  • Understanding your target audience
  • Personalizing their ad content
  • Optimizing your advertising strategies

Don’t just take our word for it, though. Some of the biggest brands in the world have already seen significant benefits from using predictive analytics.

One of the greatest AI advertising examples is Coca-Cola, who have been early adopters of the technology. Coca-Cola saw a massive jump in customer engagement after implementing a machine-learning algorithm, using image recognition technology to analyze social media photos featuring Coca-Cola products as well as to provide a more seamless proof of purchase process. And as far back as 2009, they’ve been using simple AI to analyze vending machine data on customer behavior and preferences to inform product development.

AI’s power lies in the ability to analyze large amounts of data quickly, allowing you to make informed decisions that drive tangible results. As AI in advertising evolves even further, predictive analytics will become more and more essential to stay ahead of the curve and remain competitive.

Personalized Ad Targeting

Personalized ad targeting is another very promising application of advertising AI. It leverages machine learning algorithms to determine consumers’ interests, preferences, and behaviors. That way, you can deliver AI-targeted advertising that your audience will want to engage with.

One of the main advantages of personalized ad targeting is its ability to increase an ad’s effectiveness. By tailoring ads to your specific audience’s interests and needs, you can gain the following:

  • Higher click-through rates
  • Higher conversion rates
  • Higher returns on investment

It can also better serve the online ecosystem by reducing irrelevant ads. This helps everyone by improving consumers’ chances of seeing ads they care about. It can also create a more positive perception of your brand and lead to increased loyalty and repeat business.

Of course, some concerns can arise with privacy and data protection regarding personalized ad targeting. Staying informed on developments and approaching your strategies with transparency will play a massive part in ensuring you stay compliant with GDPR and other regulations.

Image and Video Recognition in Visual Advertising

In today’s world, images and videos have become powerful mediums for AI digital advertising. Brands consistently try to find ways to optimize visual advertising efforts to reach their target audience more effectively.

With the advent of AI, it’s possible to scan visual elements, such as:

  • Colors
  • Objects
  • Faces
  • Logos
  • Emotions

You can then use these elements to determine what combination will work best for your audience. AI can rapidly generate many combinations of elements on the fly to see which will convert audiences most successfully.

Moreover, taking things a step further, AI can also recognize these elements in consumers’ images and videos uploaded to social media. You can then use AI to inform ad creatives that emulate the vibe of user-generated content (UGC) to precisely target your consumers.

This technology also has vast potential in brand safety and suitability, rapidly analyzing images and video to help you understand the context in which your advertising may appear. This can ensure that your brand does not become associated with unfavorable or inappropriate content.

Natural Language Processing

NLP focuses on understanding and interpreting human language. It enables machines to comprehend speech and text by interpreting phrases and phonemes. Phonemes are distinct units of sound that make up different parts of words. This can help analyze contextual content for brand safety as well, and also provide insight into consumer sentiment.

With NLP, AI can interpret what consumers say via:

  • Customer feedback
  • Social media interactions
  • Customer support inquiries
  • Voice assistant commands

When combined with sentiment analysis, NLP can be potent. Sentiment analysis analyzes digital text to determine whether what is said is positive, negative, or neutral. This can help you better understand the needs and preferences of your consumers. Then, you can tailor your marketing messages accordingly.

NLP can also power chatbots and voice assistants. This makes it easier for people to interact with your brand throughout the customer journey. Conversational AI tools can:

  • Recognize voice commands
  • Answer questions
  • Provide product recommendations
  • Provide insight and tips to improve the customer experience

Evaluating AI-Powered Advertising Campaigns

Now, we’ll look at how you can assess your AI-powered campaign. You can use the described metrics to optimize the performance of your ads over time.

Metrics and Key Performance Indicators (KPIs)

Evaluating AI-powered advertising campaigns requires a comprehensive understanding of metrics and key performance indicators (KPIs). These metrics help you measure how effective your campaign is. KPIs also help you determine how close you are to your goals.

Make sure, then, that you define your metrics and KPIs early on in your campaign. That way, AI will be much more effective when it comes into the picture. You’ll already be equipped with specific data to feed into the algorithm.

Basic metrics to consider include:

  • Click-through rates (CTR)
  • Conversion rates 
  • Cost per click (CPC) 
  • Return on investment (ROI)

You’re probably already familiar with these metrics, but you won’t want to leave them unattended when running an AI-powered campaign. You’ll want to hone in on these metrics for at least the first few cycles of advertisement. With AI analyzing and changing your campaign rapidly, you’ll want to ensure it moves things in the right direction.

That’s why it’s crucial to have your KPIs defined and concrete. They will help you evaluate how to optimize each milestone in your campaign.

You’ll then be able to see if your campaign is delivering results or if other areas need improvement. Monitoring and adjusting these aspects will be critical to the overall success of your campaign, and having an expert involved who understands both the digital advertising landscape and AI tools is vital.

A/B Testing and Campaign Optimization

As a key component of many AI-powered advertising campaigns, A/B testing is just as important, if not more influential, as running any human-planned campaign. Of course, while it’s easy to think you can turn on the AI and watch the money roll in, it will always perform better with more data and input.

While AI-powered tools are incredibly effective at performing the operations we mentioned above, A/B testing can help you spot any blindspots in the algorithm and tweak it to perform at its best.

This will be an ongoing process, and you’ll want to review your results and make changes as needed. This could involve:

  • Tweaking the messaging
  • Adjusting targets
  • Adjusting the ad format
  • Switching up a creative entirely

This campaign optimization will be an ongoing process. AI, at its current stage, is an invaluable tool to augment marketing skills which should be monitored and guided by strategic experts as needed. You’ll still want to have someone involved in testing and planning, while AI provides the rapid analysis and adjustments needed where human reaction times fall short.

Monitoring and Adjusting AI Algorithms

AI can deliver incredibly detailed reports on your campaign almost instantaneously. You won’t have to wait for manual analysis to learn how last week’s ads performed. 

You’ll see which creatives are performing well in real time, and advanced AI tools can adjust your spend to focus on these high-performing ads, optimizing for budget and performance. You can also utilize machine learning techniques to train your algorithm. If some aspects of your ad are proven to work with a certain demographic, your AI can automatically serve those types of ad creatives to others in similar demographics.

Advanced AI Models and Algorithms in Advertising

Advanced models are really moving the needle for both AI and advertising. These advanced technologies are able to analyze massive amounts of data and learn from it to make intelligent decisions. 

Deep learning is a method that we touched on briefly earlier. These types of algorithms mimic the neural networks in your brain. They can identify relationships between different types of data and their characteristics, so they can understand complex patterns. This enables you to get deeper insights into consumer behavior.

Something we haven’t talked about yet, meanwhile, is reinforcement learning. This allows an algorithm to learn through trial and error. It can then constantly improve its performance based on feedback it is receiving from data sets. These types of algorithms can be good for optimizing bidding strategies and ad placements.

Collaborative filtering algorithms can be used to provide personalized recommendations. These types of algorithms analyze user data to better understand individual preferences. Then, an algorithm can make relevant product and content suggestions. 

There are also generative AI tools revolutionizing the way you create advertising content. These generative adversarial networks (GANs) can create realistic images, videos, and text. This lets you create personalized and visually appealing ads, tailored to suit the tastes of your consumer. This can help you deliver more impactful ad content by making relatable creatives that speak directly to your target audience.

Ethical Considerations for Data Collection and Usage in AI Advertising

Ethical concerns arise with any new type of technology. If handled inappropriately, AI can quickly make consumers feel like they’re being watched instead of helped. It’s essential to make sure you’re being transparent about:

  • What data is being collected 
  • How data is being used
  • Who data is being shared with 
  • Ways to opt out of data collection

Also, it’s very important to consider the potential for bias. AI is only as objective as the data it’s being trained with. This data will be reflected in the campaigns they generate. You’ll want to be vigilant about addressing any biases reflected in AI-powered campaigns.

You will constantly find new ways to leverage AI as technology continues to evolve. Here are some emerging trends to look out for:

1. Voice-Activated Ads: These interactive voice experiences engage consumers more conversationally.

2. Augmented Reality (AR) Ads: Allows consumers to virtually test products by trying on clothing, visualizing furniture in their homes, touring venues, and more.

3. Personalized Video Ads: Use insights to fuel personalization and dynamically create videos optimized for specific audiences.

4. Time of Day Advertising: Optimize your strategy by analyzing large amounts of data to deliver personalized ads at specific times of the day when your target audience is active.

5. Influencer Marketing Powered by AI: You can serve specific content from an influencer based on your audience’s interests. For example, if an influencer is creating skincare content for your brand, AI can serve specific ads to consumers that are interested in different types of products, such as makeup and face wash.

The Benefits and Challenges of Using AI in Advertising

Let’s review some of the benefits and challenges of AI that we have discussed throughout this article. 

  • You can analyze large amounts of data more efficiently using AI. This data can provide valuable insights into consumer behavior, preferences, and trends. 
  • You can create highly targeted campaigns based on audience data and predictive analytics using AI. 
  • You can automate ad placements, targeting, and optimization using AI. 
  • You can make adjustments to your campaign on the fly using AI. 
  • You can personalize ad messaging using AI, building trust with your audience quickly. 

However, using AI-powered advertising can present challenges. 

  • One of the main challenges is ensuring that AI is collecting your audience’s data in an ethical way. It’s essential to be transparent about how you collect and use data.
  • AI algorithms are not infallible. They depend on quality data to perform to their full potential. 

Consider working with a digital advertising partner that can help you access the latest in AI tech and maximize the benefits while minimizing the potential drawbacks.

Reap the Benefits of AI-Powered Advertising With AUDIENCEX

You can easily take full advantage of AI tools in your campaigns by working with a digital advertising partner such as AUDIENCEX. Our suite of privacy-safe AI-powered solutions, AUDIENCEX Intelligence (AXi), provides advanced capabilities to help you understand your audience, expand it efficiently, and scale performance rapidly throughout digital channels. Built from the ground up to provide innovative performance capabilities while safeguarding user data, our solutions include:

  • First-party data analysis
  • Behavioral data science
  • Access to fully consented third-party data sets
  • Predictive audience modeling
  • Custom bidding algorithms
  • Continuous campaign optimization
  • Real-time analytics and actionable insights
  • Omnichannel programmatic access
  • Tech-enabled creative capabilities

All of our innovative technical capabilities are overseen by industry-leading strategic experts, dedicated data scientists, and analytics & insights teams monitoring and enhancing the performance of these tools throughout the entire lifecycle of your campaign to ensure you’re taking full advantage of their benefits. 

We work to ensure that our solutions, no matter how advanced, are rapidly and effectively leveraged for our clients, with easily understood results and performance. If you’re ready to start taking advantage of AI-powered advertising technology to help your campaigns engage the right audience, reach out to our team today. We would love to connect and explore how our solutions can work best for you.

Get more Insights on AI in Advertising

If you’d like to learn more about AI in digital advertising, check out our recent on-demand webinar, aX Roundtable: AI in Programmatic Advertising. During this event, AUDIENCEX leadership discussed the background of AI in advertising, its impact on the industry, how these solutions can be leveraged today, and what they expect to see as these technologies continue to rapidly advance.