How is machine learning impacting digital advertising?

Machine learning systems are made up of algorithms that are intelligent enough to comprehend data in a way that leads to a “diagnosis”, prediction and organisation.

The more data they are exposed to the more they are able to improve. They can also teach themselves to become smarter over time as they are increasingly exposed to data.

Machine learning and AI

Machine learning allows us to “imitate” the mental process of the buyer “optimising” the choices just like a normal buyer would. This system has the ability to learn over time and generate more accurate results applying its “knowledge” to different campaigns, making those associations that can be challenging for the human brain to pick up on its own.

Machine learning is now everywhere when it comes to digital advertising and is being applied to different aspects of it:

  1. Data measurement (What is Tom’s pattern of algorithms?)
  2. Prediction of device association (Based on IP info is that Tom’s ipad AND iphone?)
  3. Intent prediction (The likelihood that Tom will buy those new shoes in the next month or so)
  4. Response prediction on an ad impression level (Will Tom click on the ad, or view the whole video?)
  5. Fraud detection (Is Tom real?)
  6. Audience insights (Can I extract some of Tom’s behavioural patterns for instance to inform creative design?)

The next steps for machine learning
Machine learning will only improve as the years go by. As technology advances, computers will be able to make more adept correlations, and as we move into an ever more mobile world, advertisers need to rely more and more on the multiple platforms in order to deliver their message.

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