AI in advertising: What should you know about it?
Big data and artificial intelligence are changing the digital advertising market at a rapid pace. Not only marketers and advertisers are seeing this, but also consumers, who are shown personalized ads based on their current interests and search history. Chatbots answer questions and help audiences make decisions. So, what exactly is AI advertising?
AI-based advertising is a technology that models human behavior by studying large data sets. It is followed by predicting patterns, creating accurate and effective context, and building strategies for relevant ad impressions to target audiences.
To do this, historical data is used to help AI make better decisions in the future. With AI, advertisers can create more personalized ads, target the right audience, and make faster choices. In this article, we will discuss how AI is changing the advertising market and 5 challenges of AI in advertising.
What does AI advertising consist of?
AI-powered advertising can include the following technologies.
Machine learning
Cognitive advertising algorithms use artificial intelligence and computer algorithms to analyze information and automatically improve the experience. Devices that apply machine learning technology can analyze new information based on relevant historical data. This can then inform decision-making — what has or hasn’t worked in the past.
Big data and analytics
With the emergence of digital media channels, experts from marketing and cybersecurity have brought Big Data to the forefront of technology. Thanks to it, it is possible to evaluate which strategies used in advertising and sales funnels are most effective.
Efficient AI platforms
Specialized AI platforms can be used to manage large data sets effectively. They can extract valuable marketing information about the target audience and make the right decisions.
For example, do you know the difference between SSP and DSP? In AI-driven advertising, they serve distinct roles within the programmatic ecosystem. Publishers use an SSP to manage and sell their ad inventory. It utilizes AI to optimize the selling process, ensuring that ad spaces are sold at the highest possible price by analyzing real-time data and predicting which ads will perform best. This helps publishers maximize their revenue by intelligently managing and auctioning their ad spaces to advertisers.
On the other hand, advertisers employ a DSP to purchase ad space across multiple digital platforms. AI within DSPs is critical in targeting the right audience, optimizing bid prices, and selecting the best ad placements to achieve specific campaign objectives. By analyzing user data and predicting behavior, DSPs help advertisers run efficient and effective campaigns, ensuring their ads reach the right people at the right time.
What’s in store for AI?
Advertisers who aren’t already using artificial intelligence to optimize ads should look closer at the technology. Researchers predict significant growth in AI’s presence in the advertising market over the next decade.
Artificial intelligence helps companies better segment audiences to launch advertising campaigns. It also enables the creation of targeted ads while measuring results.
Experts at US marketing company HubSpot report that today’s marketers are creating content for many different audiences, not just one. Three is the bare minimum but it’s often many more as brands are speaking to their existing audiences and those determined through consumer growth targeting. Creating ads for only one audience and hoping for the best is now pointless.
To get better results, companies are using AI in business. This allows for more precise targeting of niche groups of potential buyers. With the help of artificial intelligence, ads are shown to the right people.
Measuring the success of advertising campaigns and strategies is easier with artificial intelligence. The transparency and accuracy of the data analyzed make it easier for advertisers to understand what is worth investing in.
The advertising industry that applies artificial intelligence will continue to evolve with the digitalization of the modern world. Advertisers already have the opportunity to take advantage of the many benefits of this technology.
Let’s look closer at how artificial intelligence is changing the digital advertising ecosystem and how companies can use these insights to create more cohesive ad strategies.
How is AI changing the advertising market?
Artificial intelligence technology is rapidly changing the advertising market landscape because of its ability to self-learn and get smarter. Here are some ways it can be used to optimize advertising.
Personalized leads for a better user experience
Marketers and advertisers use data to personalize ads to improve user experience and reach targeted audiences. This data includes demographic information, interests, purchase intent, and behavior patterns.
Improving ad relevance and personalization is becoming a top priority for marketers. 80% of users who believe they shop frequently say they do so from companies offering personalized deals based on their interests and user experience.
AI solutions like conversational marketing help advertisers build personalized communications with consumers and provide potential buyers with the best offers. Conversational marketing is personalized real-time communication with current and potential company customers using multilingual chatbots, live chats, voice assistants, and other forms of AI.
In fact, 71% of shoppers prefer to communicate in real-time with brand representatives. That’s why marketers and business owners have started using conversational AI marketing more frequently to interact with customers.
Audience segmentation before ads are shown
Using machine learning, advertisers can learn the behavioral patterns of target audiences and create offers that interest them at the moment. Carefully segmented audiences and the right ad content can guarantee higher conversion rates.
To do this, ML analyzes all available information about a particular user, such as demographics and online behavior. The data obtained will influence the type of content the user wants to see at a specific moment.
Transforming booking systems
AI technology is making waves in industries beyond advertising. Take, for example, a clinic appointment system. By leveraging AI, such systems can automate scheduling, analyze user preferences, and send personalized reminders, ensuring smoother operations and a better user experience. These innovations demonstrate how AI’s data-driven capabilities can optimize processes across various sectors, including healthcare.
Ads created by AI convert better
With the help of AI, it is possible to analyze previous trends and performance metrics and, based on this data, create better ad texts that will convert better. In this case, marketers go beyond standard A/B testing and use artificial intelligence and data-driven insights to predict how creative text will resonate with potential customers. This allows advertisers to move to proactively create ads and generate better-targeted bids and conversions.
In 2018, Salesforce’s research department studied Enterprise Technology Trends. Already then, 83% of IT executives said artificial intelligence and machine learning are changing customer interactions. 69% said they were changing their business.
Interactive experiences
Artificial intelligence can create more interactive experiences within conversational marketing. It allows you to launch ad campaigns based on online customer interactions with live conversations.
Interactive marketing tools like conversational marketing help create ad campaigns based on customer data interactions online through widgets on websites, social media, smart devices, etc. Chatbots with conversational artificial intelligence and machine learning bring personalized experiences to the digital ecosystem and platforms. These interactions are personalized and based on the wants and needs of the target customers.
AI helps improve ROI
Artificial intelligence is an analytical approach to advertising. AI tools process vast amounts of information and data to accurately predict future trends and derive analytics insights.
The great thing about artificial intelligence is that it is always improving just like humans. It learns and adapts as needed. This allows it to make better decisions in the future.
Advertisers may have difficulty evaluating the effectiveness of advertising campaigns. That’s when AI analytics comes to the rescue, helping to determine which strategies work and which don’t. Thus, in the future, advertisers can proactively take the right steps and make decisions that will positively impact their campaigns.
According to a study by international audit and consulting firm Deloitte, 73% of marketers and business owners who use AI technology in their work believe it is “very” or “critically” important to their business. At the same time, 64% said they have gained an advantage over their competitors by using AI. Personalized offers to target audiences with the right content marketing help reduce advertising costs and increase ROI.
AI helps in performance optimization
Performance optimization with AI also affects targeting and saves money. This is an important example of using artificial intelligence in advertising. Machine learning algorithms can analyze the effectiveness of advertising campaigns on different platforms and then recommend certain methods and strategies to optimize them.
5 сhallenges of AI in advertising
Here are the main challenges of AI in advertising you must be aware of.
Meaning bias
Advertisers rarely understand how algorithms work and how unconscious shifts in the meaning and message of an ad text can be coded into them. It can harm the effectiveness and ROI of the entire campaign.
This can be a problem for advertisers who optimize texts using artificial intelligence. Machine learning technology, if deployed correctly, can help reduce this bias.
As the advertising industry increasingly turns to artificial intelligence for audience segmentation and campaigns, machines are making more decisions. Marketers who use artificial intelligence try to remain objective in their decisions.
However, other users who are not AI experts often don’t understand how algorithms work and what meanings may be embedded in these models. Decisions can then be made based on unintended cues such as age or race, introducing bias into the campaign.
Training time and data quality
AI tools cannot always assess what decisions need to be made to achieve all goals. They must learn from company data, customer preferences, and historical trends to improve algorithms.
In addition, they must ensure data quality. If AI tools are not trained with accurate, timely, and representative data, they will make less effective decisions.
Data privacy
Marketing teams have a responsibility to keep their customers’ personal data secure. If their integrity is compromised, companies risk serious fines, other liability, and damage to their business reputation. This is a serious problem.
Investment
Not all advertisers and marketers may embrace AI technology to optimize advertising. Key metrics such as ROI and ROMI effectiveness can be measured, but showing how AI improves the customer experience is not as easy or transparent.
AI bots
AI technology is not only used by advertisers and marketers to optimize advertising campaigns. AI is a key tool for fraudsters who attack digital advertising with advanced bots.
Attackers are developing AI scripts to perform next-level attacks: ad-skipping, generating fake leads, stealing content and personal data, scraping (for example, completely copying an online store’s catalog), finding vulnerabilities, and hacking sites.
Bots based on artificial intelligence better imitate human behavior on the site, so they are harder to detect. Only AI-based cybersecurity systems and machine learning can counter them.
3 trends in AI advertising
The advertising industry is constantly changing, and it’s important to keep a close eye on industry trends to work ahead of the curve. Below, we’ll list the trends to keep an eye out for when it comes to AI advertising.
Traditional A/B testing
A/B testing is not the best or only way to create more effective ads. While it is a traditional way to test ad relevance, using predictive audiences can help a company create better ads and creative texts before ads are shown and evaluated for effectiveness.
Artificial intelligence can process massive amounts of data to make recommendations before spending the budget. Advertisers can save time and money on creating the right ad campaign.
Cookies will disappear, but personalization will remain
With the new online privacy regulations, it will become more difficult for marketers and advertisers to target audiences because they will not have the additional information from cookies. Even after cookies are prohibited, artificial intelligence will still be able to recognize patterns of target audiences.
AI will not need to resort to using the user’s sensitive information. Instead, it could look at contextual advertising, location data from the user’s device, or other triggers to effectively show relevant ads to the user.
Customer behavior is changing
Many advertisers experienced so-called customer churn during the COVID-19 pandemic. At that time, their behavior patterns were changing rapidly. So, the models and strategies used to work and convert may have changed.
Advertisers need to be able to incorporate current information into their ad campaigns. They also need to have algorithms that can adapt to changes in the market.
Conclusion
The impact of AI technologies on marketing and advertising is undeniable. AI tools allow businesses to achieve high efficiency and ROI. AI will replace many specialists by 2030.
However, designers, copywriters, and marketers should not worry about this. They will not be out of work because machines take over the digital routine and the technical side of projects, while creativity and emotions are left to humans.
