The Rise of Artificial Intelligence (AI) in Programmatic Advertising
With the evolution of the online world and digital spaces, marketing has been experiencing rapid growth. Traditional billboards slowly evolved into web banners, and mailing lists turned into newsletters and promotional emails. Marketers took advantage of this new technology, and now digital marketing has become what we know today—the industry with the largest growth in spending, recently valued at $626.9 billion.
The amount of global interest in this area has resulted in the ongoing development of new marketing tools. What started as simple algorithms and basic customer engagement techniques have developed into a worldwide marketing network that attracts hundreds of millions of users daily.
Modern tools like omnichannel marketing platforms, data management platforms, DSPs, and chatbots all play a big role in generating profits for advertisers. All of them have one thing in common: the use of machine learning and AI that helps them grow and advance to the next level. Recently, AI marketing has changed the landscape of the industry, with over 61.4% of marketers now using it in their campaigns. This indicates that they already consider artificial intelligence to be extremely important in their businesses and judge that it will continue to have a big impact on sales in the future.
So, what exactly is AI marketing, and how can you use it for your own projects?
Artificial Intelligence: Understanding The Future of Programmatic Advertising
Before we delve further into the topic, it is important to emphasize that AI needs a basis to operate on, i.e., a programmatic advertising platform. It can automatically handle things like bidding, data-based targeting, purchasing ad space, ensuring wide reach, and supplying advertisers with campaign performance data. Here, machine learning and artificial intelligence act as supportive mechanisms, enhancing the experience of both customers and advertisers.
But how do they accomplish that?
What is AI in Programmatic Advertising?
To get a better grasp of AI, it is best to turn to programmatic advertising first. It accounted for over 80% of digital ad spend in 2022 and is the most effective way to deliver ad content to your audience. In this type of advertising, platforms buy ad space, which is then bidded on by advertisers; since the process is automated, there are no extended negotiations or time expenditures to place the ad. The bidding starts and ends before the website is loaded, and it is easy to see why this format is popular. It benefits all three sides: advertisers, programmatic advertising platforms, and customers.
Now, the application of AI in programmatic advertising is able to enter the picture. Loaded with an immense amount of data, it automatically analyzes customers visiting the website and then displays the most relevant ad to them. Now, your ads can reach desired audiences that are more likely to interact with them, boosting both CTR and conversion rates.
The combination of AI and programmatic advertising is best viewed as the work of a sniper and a spotter. Ultimately, it is the sniper (the platform) that makes the decision, but AI will mark the best targets. Without it, advertisers would have to shoot in the dark, and their options for both targeting and retargeting would massively decrease, inversely increasing their operation costs.
The World of AI Variables
As we already know, to do its job properly, AI needs data. The more information it knows about customers, the better results it will provide. There are a number of ways to receive data, but it can be boiled down to these important categories:
- Instant data. As soon as the customer visits a website, cookies provide several pieces of basic information about them. These typically include things like operating system, device type, browser language, or the website the customer came from. It already allows AI to build an outline of the user and start matching the ads.
- Contextual data. In this case, AI shifts its focus to the environment, gathering information about the time of day, the day of the week, the weather at the time, or contents of the website visited. This information may be necessary to bring out the most appropriate ad at the perfect time, but it is very prone to change due to its nature.
- Tracking data. Mainly collected through tracking cookies, this is fundamental for building an exhaustive user profile. This type of data concerns things like websites visited previously, gender, age, and preferences. It completes the picture of the potential customer and allows AI to make the best decision when it comes to showing the ad.
The Hero or The Sidekick? The Role of AI in Programmatic Advertising
Without AI to support it, programmatic advertising would not be as effective or as widespread as it is today. Solely responsible for analyzing large data sets, enhancing targeting, and identifying the audience, AI seems almost inseparable from modern digital marketing. On the other hand, it is not a panacea; the presence of AI does not guarantee that the campaign will be successful or that the targeting will be perfect.
In this regard, it is better to take a look at domains where artificial intelligence shines and fields where it can still be improved.
Optimizing Bidding Strategies
Each customer has a different value to an advertiser depending on their target audience and goals. As a consequence, advertisers want to avoid showing ads to users who are not going to take an interest in their product and help conversions. AI solves that problem by allowing them to target the right customers on the right website. This precision helps to keep costs lower as well; by minimizing the number of unproductive impressions, advertisers can spend less on bidding and still come out on top in terms of targets and conversions.
Improving the KPI
Key performance indicators are substantial for every marketing campaign out there, and advertisers closely monitor their KPIs to measure the performance of their activities. With the help of modern AI, virtually every metric across the board can be enhanced, and if marketers notice that some are lagging behind, AI can help them focus on that metric instead. It is especially useful for increasing CTR, CAC, conversion rates, reach, and decreasing churn rates.
Plotting Your Future Campaigns
By seeing the performance of your marketing campaign and the types of customers that interact with your ads, AI can not only build individual user profiles but also create focus groups of the most receptive people. Then, based on that group, it can use lookalike modeling to identify new potential customers.
With that feature, advertisers can use their existing audience to massively increase their reach, discover new niches, or plan future advertising campaigns. Lookalike models are also particularly useful in cases where advertisers are not sure about their target audience, as grouping helps to point out the common characteristics of their customers.
Supporting, Not Replacing
With the emergence of AI, marketers no longer need to manually analyze their audiences, putting dozens of hours into menial jobs. Artificial intelligence does that quicker and more efficiently than a group of seasoned market analysts.
Still, it is not the be-all and end-all of digital marketing. To work properly and come out on top, AI still needs constant and precise data input. Its predictions entirely depend on the amount and accuracy of the given data; ensuring the quality of that data is something that only advertisers can do. AI that is not monitored and fine-tuned on a regular basis can backfire, resulting in incorrect analysis and mismatched audiences.
Ultimately, artificial intelligence can become a powerful tool – but it needs you, the marketer, to achieve that.
Reaping Benefits From AI in Programmatic Advertising
Apart from being the driving force behind programmatic advertising, AI and machine learning have their own array of benefits. The reason why AI will prevail in the marketing industry in the near future and is not going to wane anytime soon is because of its sophisticated mechanisms and adaptability. They allow artificial intelligence to evolve even further and take on more complex tasks, and for the most part, this happens automatically.
Learn-Adapt-Learn Cycle
The combination of predictive analytics and machine learning creates a looping cycle that allows AI to only get better over time. As it ingests more data, AI creates new pathways to potential customers, improves accuracy, and changes its own behavior to suit customers’ and advertisers’ needs. As soon as the results of the AI-powered campaign come in, it can once again analyze its performance and provide new insights to advertisers.
With AI, the improvements are ongoing and depend only on how much information you can provide to the algorithm.
Personalization
Understanding your customers and connecting with them on a deeper level has proven to be a very efficient tactic that may result in earning more than a 200% ROI. AI takes away the need to personally analyze your audience, providing exhaustive user profiles and groups to easily discover common points and focus on them. It can not only help advertisers perfectly match their ads to the desired group but also precisely target them using the collected information.
Anti-Fraud Mechanisms
AI, with its massive amount of already processed data, can also quickly notice anomalies in the new information it receives. For example, it can notify the advertiser about the rapid growth of CTR that does not result in any conversions — a very massive red flag of click fraud. With artificial intelligence, the advertiser does not need to closely monitor and correlate these metrics regularly while still learning about the fraudulent activity as quickly as possible.
A Place For Innovation
Advertisers can use AI as a tool to test your newly acquired insights and see their performance. For example, it can analyze the performance of ads in terms of the fonts, colors, and images used in correlation with the time of day, geography, or other variables. This way, advertisers can discover new ad formats that may have better outcomes for their target audience.
Additionally, it can help marketers choose between several ad creatives by measuring their performance and marking those that are not doing well. It enables advertisers to optimize their marketing strategies and constantly choose the most reliable options.
In Pursuit of Perfection: Drawbacks of AI in Programmatic Advertising
Even though we have listed a number of the benefits of AI, it still encounters its fair share of problems, from consumers’ skeptical perception of the new technology to biases, inaccuracies, and even regulatory problems. While most of these difficulties are temporary, advertisers should still take notice of AI’s shortcomings to avoid disruptions to their projects.
Let’s explore some of the issues you should be aware of when turning to AI solutions and how we can minimize the risks.
Data Dependence
The problem. Dependence on data is the thing that makes artificial intelligence so precise and overwhelming in the digital marketing industry. That very quality, however, may also be its biggest pitfall.
AI does not have ’intelligence’ in the traditional, human sense; it does not have critical thinking to distinguish good from bad data. It will process just about anything advertisers input and make assumptions based on that information, even if it is incorrect. That may lead to completely unreliable analysis results that just drag advertisers’ campaigns’ performance down instead of improving it.
The solution. To avoid this, marketers should thoroughly check not only the data they input manually but any automated data sources that feed information to AI as well. Inaccuracy even in one source can profoundly change the decisions that AI makes, and that may negatively reflect on the campaign.
Biased Decisions
The problem. AI’s work is largely algorithmic, and these algorithms are not perfect. Often, they simply perform their functions without regard to human factors like mindsets or societal categories. If, for some unfortunate reason, the data entered was biased against certain groups, the artificial intelligence may unfairly target entire demographics or show ads to audiences that may even be offended by them.
The solution. Apart from double-checking the data the AI has access to, it is best to monitor which ads are being shown to whom. This is the case where guidance from a real human is crucial; fortunately, modern programmatic advertising solutions have enough ranking settings to solve this problem fairly quickly.
Transparency Issues
The problem. Algorithms used in AI are complex, and the decision-making process is often unavailable for advertisers to view and judge. All of the ad delivery, pricing, and bidding is done automatically without advertisers’ input, and that can create unease and uncertainty when it comes to trusting the new technology to do the right thing.
The solution. Choose platforms that can show how the data is processed and evaluated to make sure that everything is fair. The good news is that everything is moving in the right direction, as unattributable ad spend decreases every year and programmatic platforms are actively trying to collaborate with their users to share data.
AI Regulation Rules
The problem. Since AI works with large data sets that may contain sensitive information, governments and authorities implement various regulations that pose a challenge for advertisers wanting to utilize artificial intelligence for their projects.
Data privacy has been one of the biggest concerns for customers in recent years, and in response, regulations like GDPR and CCPA emerged to protect their personal information. Initiatives like third-party cookie removal from Google Chrome also make it harder to gather additional data about customers, limiting the data sources AI could have access to.
The solution. Using ethical and regulation-approved methods of both gathering and using customer data is the way to go. Usage of first- and second-party cookies is still encouraged by Google, and data clean rooms that do not single out individual consumers are allowed as well.
The Future of AI in Programmatic Advertising
Artificial intelligence solutions have already cemented themselves into the marketing world, and giants like Facebook and Google are using artificial intelligence advertisements for their services. The former fully utilizes predictive analytics and their users’ data to target their customers, while the latter has enhanced their ad system with AI to help marketers find new audiences and increase conversions.
Even though global regulations may make the task more difficult, smaller companies will undoubtedly catch up in the near future. Right now, the only real problem is cost, as both gathering huge data sets and running them through AI take a high toll on a budget. However, AI and ML will only become more accessible from now on, seeing how ubiquitous programmatic advertising has become.
The development of AI technologies that will specifically suit digital agencies and platforms is already underway, and it will not stop there. Soon, we may see AI flow into more common marketing areas, with entire AI-generated ads and maybe even campaigns. Right now is the best time for innovation, and artificial intelligence will only continue to provide new ways to capture the hearts of your audience.
