Innovative technologies such as machine learning, deep learning and programmatic advertising are some of the hottest topics in advertising right now. All these terms are often used interchangeably, but they are definitely not the same thing.
All the buzz around these technologies comes from the fact they are transforming the way we work and bringing significant changes and improvements to marketing and social media advertising.
If you are working in businesses that can benefit from them, learning how each of these technologies can help you in your social media ad strategy can put you ahead of the competition.
What makes machine learning, deep learning and artificial intelligence different? How is programmatic buying related to all of this? You have questions and we have got answers.
Programmatic ad buying is the process of using software to buy digital ads. Instead of going through human negotiations and manually inserting orders for ads on digital platforms like Google and Facebook, media buyers use software to go through an auction-based process to have their ads served in a network of their choice.
Buyers use big data to target their most valuable customers by segmenting their audience through characteristics like age, gender, region, among others. They then go through an auction process and choose if they will pay the price an ad is worth at that moment to have their ad seen by this specific audience.
Programmatic ad buying reduces costs and improves brand performance in the ad industry. This technology is now getting an upgrade and advertising software is becoming smarter due to artificial intelligence.
Artificial intelligence is the concept of replicating human intelligence in machines so they can perform activities that would require the human brain involved, such as making data-based decisions.
AI-powered systems help companies save money by working at a faster speed than human beings and with less potential errors. If you apply this AI to the advertising industry, you bring efficiency to the media buying process, freeing media buyers from tedious work to focus on strategic and creative tasks.
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Machine learning is a type of artificial intelligence that provides computers with the ability to learn things by being programmed specifically to certain tasks, improving its knowledge over time the same way the human brain does.
It focuses on mimicking our own decision-making methods by training a machine to use data to learn more about how to perform a task.
Imagine you drive to work every day. Over time, after trying different ways to arrive at your destination, you will learn which path is faster or maybe which route is better according to the day of the week. This is how machine learning works. You feed a machine with large amounts of data so it will analyze information from the past and learn from it to apply the newfound knowledge to any new data it receives in the future.
In terms of advertising, machine learning algorithms can analyze data and draw conclusions from it. It means you can basically replicate the brain of an experienced buyer in a computer so it becomes capable of diagnosing, predicting and planning things.
Deep learning is a branch of machine learning. It also generates insights based on data but focuses on more specific aspects of machine learning. With deep learning, you combine multiple layers of information to go even deeper in a specific subject.
If you want a computer to be able to identify animals in photos, for example, you can use deep learning. The computer will analyze an image in layers and use previously acquired knowledge based on data to identify the different parts of a dog – such as an ear, the tail, the muzzle, the paw – to conclude that all those pieces together compose the image of a dog.
In advertising, you can use deep learning as one way of combining different factors to draw conclusions from them and learn, for example, how people who live in a particular region have a specific age and like folk music are more likely to buy sports clothing.
Get ahead of the competition
When it comes to computer intelligence, some of the terminologies can get a bit muddled by confusing or incorrect definitions. By understanding what these terms mean and how these technologies affect your work you can potentially get ahead of the competition.