Artificial Intelligence (AI) encompasses a myriad of concepts, all of which can be used for the benefit of various fields and industries. Like the Internet-of-Things (IoT), the cloud, and other rising tech alongside them, AI concepts such as neural networks, deep learning, machine learning, and big data are now being used by businesses for mobile customer service, consumer behavior forecasting, file transfer, fraud detection, and even personalized advertising.
That last part – that AI can be used for personalized advertising – is slowly becoming a trend for a lot of businesses in different industries. After all, if AI can help analyze patterns in consumer trends, we should be able to use it for advertising, right? This brings us to our topic today – that while AI can be “taught” to analyze and interpret data, it doesn’t mean AI can be the immediate go-to for personalized content. And for something as complex as determining human interest, can we really trust AI for our ads?
Turns out, that depends on what part of advertising we’re talking about:
Big data allows AI tools to analyze and interpret trends for better targeting
We can say an ad “wins” when they get to convert audiences into leads, and that more or less can only happen if we get to target the right audience. Thanks to the proliferation of various digital platforms, apps, and software, AI tools can find it much easier to analyze huge datasets and make accurate interpretations of advertising data thanks to prior human supervision and guidance. In the case of digital advertising, AI tools can make ads more user-friendly and more tailored to the tastes and needs of users. This makes it much easier to advertise not just products and services, but also various software and applications across a variety of gadgets, especially smartphones.
AI tools can get a lot of useful information with what audiences and users provide software they use. This explains how ad tools from popular sites like Google and Facebook get to be effective with targeting consumers. Thanks to the proliferation of AI tools today, you don’t need to be a Silicon Valley giant to take advantage of good AI tools for ads.
Efficient AI algorithms can help advanced AI tools analyze and interpret data from user behavior – such as search queries, sites visited after said queries, and then classifying them for further use. Products and services that meet these classifications will be pushed to audiences via ads. The more data we feed our AI tools, the more accurate and “helpful” these targeted ads can get. This is helpful given around 3.5-billion smartphone users own a smartphone, as per Tech Jury, meaning AI tools can tap into a huge data stream to make more consumer-tailored ads for mobile platforms.
AI tools get especially efficient when we use these alongside existing ad tools and platforms. AI algorithms can help analyze consumer behavior to help optimize aspects of an ad campaign based on habits, dislikes, and interests. Meanwhile, both the supply-side platform (SSP, the ads team) and demand-side platform (DSP, or consumer search) coordinate to provide ads that help “match” the analysis of the AI tools.
Ad creation becomes transformative, efficient thanks to programming
An example of how once can AB test numerous variables. In this example, the CTA or ad caption is AB tested.
Ad teams rely on analyzing customer data, consumer trends, and different forms of testing to check which ads can potentially work with consumers. This can be very cost-intensive, as we need a lot of time and manpower to brainstorm and assess concepts, and even statistics. Thanks to advanced AI programming, AI tools can be programmed to be more proactive in analyzing consumer trends and match those with existing ad samples that need extensive testing. This “simultaneous” tackling of various ad concerns not only makes ads creation more efficient, but this leaves a lot of room for experimentation.
Thanks to a concept known as Supply Path Optimization or SPO, AI tools can maximize the data it has on consumers to assess, compare, and evaluate various ad options to aid in efficient ad creation. The programmatic nature of AI tools removes the need for ad makers to manually (or even randomly) assess the possibility of their ad options to appeal to their audiences. Instead, AI tools can sift through the ad options and determine the best choice depending on the audience, the price, and the timeframe. This, alongside the fact that people in the United States spend almost 3 hours with their smartphones as per E-Marketer, means AI tools can have a lot of basis for ads creation and testing.
AI tools also make testing and semantic research much faster and much more efficient to perform. AI algorithms can perform faster and more accurate A-B testing with hundreds of variables, both quantitative and qualitative. Semantic research also allows AI to recognize language patterns in texts and groups to aid in their data classification. This helps you make more cost-friendly ad campaigns that can still deliver your projected KPIs. It’s thanks to advanced AI tech that advertising apps also become capable of providing helpful and real-time insights and assessments on consumer trends and available consumer data.
AI in Advertising: We may be due to an AI Ads Revolution
As we transitioned to a new decade, industries have begun allocating resources to understanding and appealing to their audiences better – ensuring products and services become tailored specifically to the needs of their users. It’s surprising to see that AI, which we use mainly for deep learning, neural networks, and big data, can actually be used to help create and curate efficient ads for our consumers.
What’s more surprising is the fact that AI for ads doesn’t just encompass the insertion of curated ads in websites and social media pages. AI for advertising includes using the potential of AI tools for advanced programming and algorithms for faster, more efficient big data assessment and analysis for consumer analysis, ad creation, and consumer targeting.
About the Author: John Wyatt: John Wyatt considers himself as a very tech-savvy but also very traditional person. He enjoys typing on his laptop just as much as he writes with a pen, and this is reflected in his creative works – be it articles, blogs, or even simple posts. He loves writing about science and technology, psychology, health and wellness, and other topics he knows his readers will love to explore.
About the Author: John Wyatt: John Wyatt considers himself as a very tech-savvy but also very traditional person. He enjoys typing on his laptop just as much as he writes with a pen, and this is reflected in his creative works – be it articles, blogs, or even simple posts. He loves writing about science and technology, psychology, health and wellness, and other topics he knows his readers will love to explore.
