Introduction: How Artificial Intelligence Chooses The Ads You See
In just four years, business usage of artificial intelligence has grown by 270%. A majority of leading business ventures have existing investments in the field of artificial intelligence. There is no denying that the development of AI is driving the world forward.
If you have ever browsed the internet and later saw an ad about something you searched previously, then you witnessed artificial intelligence in action. One of the main challenges that advertising agencies used to face was matching ads with the right audience. Through artificial intelligence, this now happens automatically based on your interests. The goal here is to increase revenues generated, but it also holds promising results for the consumer – it helps them find what they are looking for.
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We discuss the methods used to ensure AI can deliver targeted ads to an audience in this article.
Reinforcement learning is the type of artificial intelligence used in ad serving platforms. This technology is commonly used in games but doubles as a tool for delivering targeted ads. With games, reinforcement learning detects when a certain goal has been reached and takes the most appropriate action based on the player’s performance, current stats, and other factors.
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When it comes to serving ads over the internet, a strategy is used that experts generally refer to as a multi-arm bandit. The goal here is to create a single-step learning program that uses artificial intelligence to analyze ads – including performance, impressions, consumer behavior, and other factors. How artificial intelligence chooses the ads you see ?
The objective here is to find the ads that have the best performance while also ensuring the entire budget is not spent on this test. The process results in higher CTR rates and better results for the advertiser.
A/B testing is something referred to as split testing too. The idea behind this method is relatively simple. You decide to run two different ads in order to find the one that offers the best results. You continuously monitor the performance of both ads over a period of seven days – or perhaps even a few weeks.
By the end of a specified timeframe, you have enough data to determine which ad gives you the best CTR or click-through rate. You then increase the budget on this ad and may consider stopping the other ad.
While this is a simple scenario, consider the fact that advertising platforms generally serve billions of text, banner, and video ads every single day. Manually testing different ad formats can be time-consuming, especially when this is expected from the agency and not the advertiser.
Artificial intelligence can help to streamline the process of A/B testing. This technology automatically places ads and analyzes their performance. The AI technology can be configured to automatically adjust spending on ads, placements, and other factors as it learns more about the performance of each unit in the group.
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Exploration Vs. Exploitation
This is an area that is often difficult to choose between. With an exploitation model, ads that have already been proven successful will be used. The company will not implement new ads, as they have already conducted appropriate tests and will now stick with the text, graphics, and other content that have been established.
Exploration, on the other hand, means continuing to test additional options while prioritizing the ads that perform better.
There are times where one ad may not perform well during an initial test but could outperform other ads at a later time. By choosing an exploration model, it is possible to avoid missing out on such an opportunity.
AI systems used in ad-serving platforms will usually weigh exploration versus exploitation. The system may start by running a few different ads, then see which ad gets the highest CTR. The system then chooses to focus on this ad but may still offer the other ads a chance to be displayed on certain occasions.
Adding Context To The Model
Another way that ad targeting is customized with AI would be related to context added to the strategies. Most people have smartphones. These devices are useful – but they also contain a lot of personal details of an individual. The data is collected in the background and stored in a database. The same happens with social media platforms, such as Facebook and Twitter.
The information collected helps ad serving platforms determine your age, gender, where you live, the type of device you use, and your general interests. This data can be used by AI to customize ads according to who you are, where you are from, and what you like. The ads become more personal, making them more effective on the audience.
AI is using various methods to deliver better targeting with advertising campaigns. The technology analyzes billions of internet users, detecting interests, behaviors, and other data. The information is then processed and utilized to target individuals who may be most interested in a specific ad, based on keywords provided in the copy and other media used in the ad format.