Machine learning and artificial intelligence technologies have come a long way in the past few years. Learn more about how machine learning is bringing value to advertising.
Marketers are taking it up a notch when it comes to their advertising game; innovations and developments in technology are revolutionizing the way modern marketing is done.
Among the many developments and advancements in advertisement are those in artificial intelligence (such as generative AI and predictive AI, data science, augmented reality, and more. One particular advancement in modern advertising that’s taking the marketing world by storm is machine learning.
Machine learning may seem like an intimidating concept. However, it plays a huge role and brings a lot of value to today’s advertising landscape. Understanding its role can give you an edge and help you stay competitive in a crowded market.
Today, we take a closer look at the benefits and advantages of machine learning in advertising and why marketers should consider investing in technology and strategy.
Breaking down machine learning in advertising
Quite often, the concepts of machine learning and artificial intelligence are confused with one another. It’s a common misconception, especially in the world of marketing. However, there is some merit and basis as to why marketers often confuse the two.
Machine learning is a type of artificial intelligence that falls under the umbrella of artificial intelligence. It is used to describe systems and software applications that are designed to “learn” based on analyzing data sets.
In other words, it is a type of AI that gives computers the ability to learn things by being programmed specifically to the tasks at hand, just the way the human brain does. But how does that work exactly?
Machine learning systems are created using algorithms that can analyze data and make conclusions. This enables them to diagnose, predict, and plan various tasks. These systems can also learn and improve in specific areas by continually enhancing their intelligence with more exposure to data.
To put that into the context of advertising and marketing, machine learning is the process by which ad technology receives data, analyzes it, and formulates conclusions to improve or streamline a task. The more data a machine learning technology processes, the more it learns about the task and as a result, it gets better at completing a particular task.
Machine learning can be used for various purposes and applications in advertising. This includes software programs that let advertisers quickly analyze and extract insights from large amounts of data, automated copywriting, optimizing media buying, audience segmentation, and customer journey mapping to name a few.
Benefits of machine learning in advertising
Because of how powerful machine learning can be and how it can be applied to many tasks in the marketing realm, more and more ML integrations and applications are done today. Here are some specific use cases marketers are implementing with machine learning and why the phenomenon is here to stay:
Better targeting and customer segmentation
Gone are the days when marketers would rely solely on survey results and focus groups to gain customer insight. Today, advertisers can segment populations into targeted groups via machine learning algorithms that recognize and analyze patterns in consumer behavior and determine which messages resonate best with each individual or group.
As a result, ad firms are now able to better target their campaigns to consumers who are highly interested in what they’re selling, bringing a deeper level of personalization and relevancy.
Media buying optimization
Through machine learning, the process and common challenges of media buying are easily mitigated.
Machine learning helps predict campaign outcomes by storing and updating past data on customer behavior. Algorithms in machine learning understand and learn from this data to make predictions.
This simplifies the tasks for media buyers, letting them focus on strategic decision-making and bigger-picture priorities.
Campaign planning optimization
Estimating an ad campaign’s success has traditionally been difficult, but with predictive AI and machine learning, advertising teams can now gain valuable insights into potential success.
Predictive analytics involves making predictions about future outcomes based on historical data patterns. High-quality data and AI are essential for the effectiveness of the predictive process.
Advertising teams can use the analysis to discover hidden campaign and audience opportunities. Brands can also test the effectiveness of campaigns before distributing them using this system. Thus, they can pinpoint which customers are most likely to be converted by their campaigns.
Predict and improve ad performance
Using machine learning can automate tedious work, saving time and money while providing better insights for your campaigns.
Machine learning helps identify necessary adjustments in your strategy by generating suggestions tailored to your goals, resources, and multivariate testing results. This can be through optimization of your ad performance on social media based on gender, age, location, etc.
By assessing data from various sources, including historical ad performance and similar advertisers, the system can predict the likelihood of achieving positive outcomes.
See how illumin’s machine learning capabilities can shine a light on your campaigns.
Work and perform better in real-time
Machine learning allows for a dynamic and flexible marketing approach in which ad campaigns use real-time data to solve real-time problems. This means that marketers can adapt to consumer behavior and can make adjustments and responses based on constantly changing and evolving data, instead of making adjustments to new campaigns when an old one has finished.
This is done through systems in which they can identify correlations and patterns from large amounts of complicated data. This also ensures their campaigns always remain relevant and valuable to target audiences and lets marketers reach their audiences more precisely.
Final thoughts
Any brands on the fence about integrating machine learning and AI in their strategies should consider doing so. Machine learning has revolutionized the way marketing is done, streamlining processes which were typically tedious.
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