A Marketer’s Guide to AI Advertising [Understanding the Future]

The popularity of generative AI tools like ChatGPT has increased the attention towards using artificial intelligence in advertising. These tools are everywhere and have drastically changed how marketers accomplish their tasks. However, generative AI is not the only application of AI in advertising.

AI is a rapidly advancing technology transforming many industries, including marketing. It analyzes and recognizes patterns in vast amounts of data and makes predictions at every stage of ad creation and management. From spot-on personalized targeting to high-converting ad copies, AI plays a role.

According to Salesforce research, 68% of marketers have a fully-defined AI strategy. Marketers across the globe are already leveraging AI tools to automate customer interactions and data integration and to personalize customer journeys across multiple channels.

A Marketer's Guide to AI Advertising [Understanding the Future]:

A Quick Definition of AI

Many marketers mistake AI for marketing automation because they have similar outcomes. Both tools simplify a marketer’s life by automating daily tasks and increasing efficiency. However, the two are starkly different.

Marketing automation relies on pre-defined rules-based algorithms to train a robot or software to perform tasks without human intervention. It eliminates manual, repetitive tasks such as data entry and classification.

On the other hand, AI tools don’t just automate tasks; they learn how to do things better. They don’t rely on pre-defined rules to decide; they know how to make decisions independently.

Demis Hassabis, the CEO of the AI startup DeepMind (acquired by Google), famously defined AI as the “science of making machines smart.”

AI technology can perform tasks that typically require human intelligence, such as speech recognition, decision-making, and natural language processing. It uses machine-learning algorithms, statistical models, and deep-learning neural networks to analyze large amounts of data, learn from it, and improve performance over time.

You can unlock new opportunities and capabilities using AI since the machine constantly learns and improves, creating better output each time.

Use Cases of AI in Advertising

Advertising is one of the many fields where there have been many successful AI use cases.

Use Cases of AI in Advertising

Personalized Advertising

With the surge of data privacy laws, the traditional way of collecting third-party data and relying on cookies has limited the ability of advertisers to offer targeted ads. Furthermore, digital ads are known to be intrusive and annoying, often detracting audiences from the brands hoping to capture their interest.

With AI, businesses can deliver the most suitable ads at the right time and in the correct format to maximize their impact. AI generates highly personalized and relevant ads by analyzing tons of data, such as search queries, social media activities, and first-party data, while remaining compliant with data privacy laws.

Furthermore, AI continuously optimizes personalized ads to improve performance by analyzing data on ad engagement and conversion rates. AI can adjust ad content and targeting, enhancing its effectiveness and helping brands remain competitive in a rapidly changing advertising landscape.

Optimized Ad Budgeting and Ad Spending

Managing a marketing ads budget has always proven challenging as advertisers struggle to create profitable ads that consistently generate huge returns. The process involves a lot of A/B testing and trial and error that usually proves costly and risky.

AI helps you select the best advertising channels where your ads will have the highest reach and allocate the appropriate budget to make enough dent without wasting resources. It can also automate the entire media buying process and intelligently adjust your marketing costs. AI tools can determine which channels generate the highest ROI, then reallocate resources toward those better-performing channels.

Google’s Smart Bidding platform is a prime example. It uses machine learning to understand bids and impressions and optimize ads for the most revenue per dollar. An independent musical equipment store that used the platform reported a 66% improvement in ROAS (return on ad spend) and a 14% reduction in CPA (cost per acquisition).

AI also improves your retargeting campaigns beyond showing ads to people who abandoned carts or, worse, already bought the same item. AI tools can identify a similar product or a better deal that shoppers will likely buy, increasing conversion.

Ad Creation and Management

AI-powered tools are accelerating the pace where companies generate ad copies and creatives. You only need to provide these tools with your goals, audience, and messaging, and it will create multiple versions of an ad within seconds. This saves time, effort, and costs from the entire creative process.

A mobile game developer experienced a 252% uplift in ROAS and a 92% increase in conversion after utilizing the Meta AI platform to generate multiple variants of an ad. They supplied the elements and text messages and let the AI platform do the rest.

Aside from creating the ads, AI can also handle ad scheduling and targeting, as mentioned above. It will also measure the ad campaign's impact by analyzing multiple metrics like ad engagement, conversions, social media mentions, purchase intent, and more.

Challenges of AI in Advertising

Despite AI software having extensive uses and benefits in advertising, there are also several challenges and criticisms.

Challenges of AI in Advertising

Lack of transparency

Agencies like the FCC and FTC regulate traditional ads, which ensures they follow specific guidelines like having full disclosure statements that they are sponsored content. Ideally, AI-generated ads should follow the same rules, but realistically, more than half of AI-generated programmatic ads analyzed in a study didn’t carry disclosure labels.

This lack of transparency can result in consumer deception and lead to false beliefs, confusion, and dissatisfaction. AI-generated ads should learn to offer content that matches users’ preferences while containing clear disclosure labels.

Algorithmic bias

AI algorithms may be biased since people who programmed them may possess unconscious biases. This can cause discriminatory outcomes that exclude certain groups and negatively impact ROI. Further, an AI model trained in biased data can perpetuate and amplify its existing biases.

For example, suppose an ad platform shows ads only to users in a particular location. In that case, it may exclude users who live in low-income areas, leading to systemic discrimination against certain groups. Regularly testing AI models and using machine learning can help mitigate AI bias.

Data quality and privacy

AI relies on vast amounts of data to operate effectively, but the data quality can vary widely. Low-quality data can lead to inaccurate predictions and suboptimal performance. Furthermore, advertisers must ensure data is compliant with data privacy standards or risk facing heavy penalties.

Observing specific guidelines may prove challenging for AI tools, as they tend to overstep acceptable terms.

Budget Constraints

Developing and implementing AI systems require significant time and financial resources. For small businesses, the cost of developing and implementing AI systems can be prohibitive, making it difficult to compete with larger enterprises with more significant resources.

For most businesses, the solution is using AI marketing tools, which come with paid or free limited versions.

Ethical concerns

Using AI raises several ethical concerns critical to implementing AI in advertising. For one, there’s the criticism that AI algorithms can become potentially manipulative and use highly personalized, persuasive advertising. For example, an AI-powered advertising system may target vulnerable users with messages designed to exploit their fears or insecurities.

Another glaring concern is the impact of AI on employment as AI algorithms continue to automate many of the tasks traditionally held by employees. AI could displace humans and cause economic disruption.

Guidelines for Using AI in Advertising

As AI becomes ubiquitous, advertisers must learn how to adopt AI in their advertising strategies. Here are several guidelines to help you get started and ensure you can harness the power of AI efficiently and effectively.

Guidelines for Using AI in Advertising

1. Define your business goals.

Before investing in AI for advertising, develop a clear understanding of your advertising goals and identify areas where AI can be helpful. AI is constantly changing, but you don’t need the latest algorithms if they don’t align with your advertising needs.

2. Choose the right AI solution.

AI-powered tools are not created equal. Even if they use the same training language, they don’t deliver the same results. When looking for an AI solution, consider factors like cost, ease of implementation, and scalability. Take advantage of trial periods to learn how these tools work and fit within the organization.

3. Feed AI with quality data and smart prompts.

High-quality data is crucial for effective AI in advertising. Make sure the data you’re using is clean, accurate, and free from bias. Remember that AI tools rely on your initial input to generate the desired outcome.

To get the best results, you also need to provide smart prompts. These short text inputs instruct AI on what to do and what results to generate. The better your prompts are, the better the responses will be.

4. Monitor and optimize performance.

Regularly review metrics such as click-through and conversion rates to identify areas for improvement. The beauty of AI tools is that it lets you quickly iterate what’s working so you can come up with multiple versions in seconds.

For instance, if you’re using generative AI to write copy and find out that a particular template is working well, you can ask the AI model to create multiple versions that you can use for A/B tests.

5. Prioritize ethical considerations.

Be transparent about the use of AI in advertising and ensure user privacy is protected. Always check the output AI generates and filter it to see if they remain relevant and truthful. When left unchecked, AI can produce misleading or overstated claims.

AI automation also replaces a lot of jobs but also creates new ones. As you embrace AI, train your team on the unique challenges and opportunities the technology presents.

Transforming Advertising With AI

AI allows performance marketers to create more effective campaigns that reach the intended audience and generates profitable results. It analyzes vast volumes of data helping you understand customer behavior better.

However, it’s not perfect and has its challenges. Understanding these limitations will help you have a realistic perspective on AI’s role in advertising so you can use this cutting-edge tool responsibly.

AI will inevitably continue to evolve and improve as our world becomes more connected and digital. Adapting them today and learning how to harness their power properly will position your company at the forefront of your industry.

Frequently Asked Questions

Why is AI important in advertising?

The primary role of AI in advertising is to deliver highly targeted and personalized ads. Cookies are disappearing due to privacy concerns and browser changes, forcing many advertisers to rely on machine learning to analyze vast amounts of customer data so they can tailor their marketing campaigns to specific audiences.

Furthermore, developments in generative AI are helping marketers develop multiple versions of high-converting creatives that they can deploy quickly. AI also collects data that can be used to refine these creatives further.

What is an example of the use of AI in digital advertising?

Google’s Performance Max is a primary example of using AI to run better ads. The tool automates ad placement, targeting, and optimization, allowing you to manage campaigns across the entire Google Network from a single source. The more you use Performance Max, the better it gets at delivering relevant ads since it uses machine learning to learn about your audience and refine campaigns.

Another example is dynamic search ads (DSA), another AI-powered advertising tool from Google. It generates headlines and ad descriptions automatically based on relevant search terms.

How will AI change advertising?

AI has the potential to transform the advertising industry in several ways:

  • Creating highly personalized experiences for audiences by generating customized content relevant to each user
  • Automating advertising processes like ad creation, targeting, and optimization
  • Uncovering insights and patterns that may not be apparent to humans by analyzing vast volumes of data
  • Predicting consumer behavior and preferences to increase the effectiveness of ads further
  • Creating more precise targeting that leads to higher engagement and conversions
  • Quickly generating creative ideas and content that can open up new possibilities for advertising campaigns