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If you work in advertising, you’ve probably heard the terms artificial intelligence, machine learning and data science. These words can conjure up images of sci-fi movies in which intelligent robots dominate the world — leading to many questions about how this technology could affect our industry.
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If you’re still trying to piece it all together, you’re not alone. This is still a new frontier for advertising as a whole.
Artificial intelligence is a technology that makes computers capable of performing tasks that would otherwise require a human brain. AI is promoting a revolution in several industries, including our own, allowing the media-buying process to be automated.
To do that, we have to use machine learning, 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.
Machine learning systems are made of algorithms smart enough to understand data and draw conclusions and correlations from it. As a result, they can diagnose, predict and plan things. They can also teach themselves to become better in a certain area (media buying, for example) and improve their intelligence over time as they get more exposure to data.
In advertising, machine learning allows us to essentially replicate the brain of an experienced buyer as software to make the same optimizations that a buyer would do. Plus, the system learns over time and generates more accurate results as it works with new campaigns, making correlations that can be tough for the human brain to detect.
There is not a lot of machine learning software available in the market, which means that advertisers who start using it now can gain a competitive advantage. If you’re still not sure how you can benefit from this technology, here are five ways machine learning will improve your advertising.
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1. Machine learning can predict and boost ad performance
A machine learning system can save you time and money by automating this more tedious work, resulting in better insights for your campaigns.
We know multiple variables can affect your advertising performance on social media. You can optimize your campaign by gender, age, geolocation, device or time of day, among other variables.
With machine learning, you can easily detect what adjustments need to be made in your strategy. The system will generate suggestions based on your goals, the amount of time and money you have and the results of multivariate testing.
This is possible because the system assesses the chances of reaching positive outcomes based on data originated from multiple sources, including your historical ad performance and the performance of similar advertisers.
Once you start using machine learning in advertising, you won’t want to stop because the system only gets smarter. Just like any good buyer, a computer powered with machine learning will learn from past experiences to provide better insights into future campaigns.
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2. Machine learning can draw correlations
Social media platforms are an incredible source of relevant data. These networks are the place where people talk about their interests, follow their favorite artists and comment on the places they have visited. Machine-learning systems can access this information to generate inputs that will help advertisers reach their primary target audience more precisely.
When you feed a computer a big pile of data, you can obtain interesting correlations that would be harder for the human brain to produce. After analyzing some data, a system that uses AI might conclude, that young men who like a particular type of music and are interested in sports are more likely to download an app, for example. If the goal of your campaign is apps downloads, the system will make sure this audience will be able to see your ads, which will be reached through optimizations a buyer would never think of doing.
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3. Machine learning can make media-buying teams smarter
Inexperienced media buyers often run into mistakes. For instance, some might not know that advertising costs are twice as expensive in December as they are in January. That could easily result in overpromising and under-delivering on CPV to a client.
With machine learning, however, you can more easily predict the outcomes of a campaign. The software stores all past campaign data and continuously updates information about customers’ behaviors. The story is in the data, and the algorithms can understand and learn from it.
Machine learning also makes it easier to scale a team. But don’t worry, it doesn’t mean that a robot will take the job of humans, as usually shown in Hollywood movies. Machine learning simplifies the work of media buyers, freeing them to focus on big-picture thinking.
Even having all the data provided by a machine, you might have to make some tough gut decisions at times, such as deciding how to use a certain budget to deliver the best outcomes in a campaign. That is to say, there are certain times when no machine can do what humans can do. On the other hand, with the help of machine learning, even a junior team member will be able to perform like a professional.
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4. Machine learning can reduce costs
What happens when you use data and algorithms to predict outcomes and set up a campaign? Results improve, and costs lower, as you will maximize the results for each ad dollar you invest. It can go as far as dropping the CPA of a campaign from $60 to $30.
This is difficult to achieve if you only have one campaign as a reference or many spreadsheets around you. With machine learning, however, you have a powerful system that can easily comb through a significant amount of data.
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5. Machine learning can create better reports
Forget pivot tables and all the mess that goes into collecting data from your campaign to put it on a spreadsheet so you can find some insights and measure results. Advertising systems powered by machine learning make campaign analysis simpler.
Media buyers can automatically generate detailed reports that are easy to read and share. The reports get straight to the point, and there is no need to develop advanced calculations to understand the stories the numbers want to tell you. Media buyers will save the time they would spend digging through numbers, instead focusing on strategy and results.
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What’s next for machine learning in advertising?
Machine learning will get better throughout the years. As technology advances, computers will be able to make increasingly better correlations, such as understanding how the audience on one social platform correlates with the audience on another.
As we move toward an increasingly mobile world, advertisers need to rely more and more on social platforms to deliver their message. By using data and machine learning, they will be able to achieve the best results.
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Of all the advancements in modern advertising, few are more exciting than machine learning. It’s changing the way businesses collect and analyze data, and even the things that data can do.
What is machine learning in advertising?
1: Which of the following algorithms is most suitable for classification tasks?
Machine learning in advertising refers to the process by which ad technology takes in data, analyzes it, and formulates conclusions to improve a task. In simpler terms: it’s how ad tech learns.
What it learns depends on the tech. It could be anything related to advertising: media buying, customer journey mapping, audience segmentation, etc.
The more data a machine learning technology processes, the more it learns about that task, and the better it gets at completing it. Just as a human would.
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Start using machine learning to boost conversions
Advertisers always look forward to better applications of current technologies. That’s the case with machine learning as much as any other: better chatbots, voice recognition, image processing, etc.
But machine learning can have a major positive impact on your campaigns today. Bidding strategies, creative, and most of all, personalization, can improve exponentially when you find a machine learning model that works for you. Undoubtedly, there’s something for everyone. Even if it’s just Smart Bidding, or Google’s responsive search ads.
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Tasks of machine learning in advertising
Same as for other industries, the main task of online advertising machine learning is to analyze data points and detect correlations that are not so obvious to the human brain.
In simple terms, in the industry of digital advertising, machine learning helps the brand to draw conclusions about customer needs, create effective ad campaigns, and optimize campaign performance on the go.
ML and AI applications become popular among businesses that run B2B ad campaigns.
Benefits of ML and artificial intelligence technologies applied in B2B advertising:
More than 84% of experts in digital advertising and marketing think that AI and ML are the main components that enable the most effective ad personalization.
- 43% of marketing executives consider AI and ML as the main factors that help them to innovate in 2022.
- 83% of early adopters of AI-driven advertising systems achieved substantial (30%) or moderate competitive advantage (53%).
- Essentially, artificial intelligence and machine learning algorithms can be effective for all stages of online advertising, including customer acquisition and retention.
- With traditional advertising approaches, ad agencies have a very limited understanding of how to target audience of the brand.
The same happens with companies and independent advertisers who run advertising campaigns independently. However, modern marketing or advertising system can accumulate a large amount of data about users and their behavior.
