Machine Learning - the future of Digital Advertising?

22 August 2018

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With the digital marketing industry becoming increasingly more involved in machine learning, it is important to understand exactly what impact it has on digital advertising as a whole.

With the digital marketing industry becoming increasingly more involved in artificial intelligence (AI) and machine learning, it is important to understand exactly what the technology is, and what impact it has on digital advertising as a whole.

 

In definition, machine learning is an application of artificial intelligence that provides computer systems the ability to automatically learn and improve from previous experience without being explicitly programmed. 

 

There is a common misconception that advancements in AI and machine learning will render humanity simply redundant; however, the reality is much less of a Hollywood movie plot. Machine learning is simply used to aid or amplify some of the things that humans do best, including interpreting data and analysing performance.

 

The process of machine learning begins with observations or data, such as examples, direct experience, or instruction, in order to look for patterns in data and make better decisions in the future based on the examples provided. The ability to predict behaviours, diagnose issues and control variables and outcomes is fuelled by algorithms, which teach themselves to grow and change when they're exposed to new data.

 

2017 was a significant year for the evolution of machine learning in PPC. We are moving away from a solely manual Ads management process, with Google Ads already having a suite of tools that can improve the performance of campaigns through machine learning and this is continually expanding.

 

As the supply of data continues to expand, and AI research continues to make progress, we can expect the quality of machine learning-driven features in digital advertising to improve.

 

However, although machine learning is an incredibly powerful tool, it is imperative to incorporate a human element in digital advertising. The volumes of data generated won't reveal anything in themselves: Human expertise is required to make sense of them.

 

Human input is crucial in terms of digital strategy, business priorities, external factors, analysing competitor behaviour and in real marketing decision-making. The challenge in bringing together complex data sets is a lack of commonality and this is where human expertise is vital in adding layers of value by quantifying the right parameters, linking data to relevant content and building relationships.

 

There is little doubt that machine learning is an incredibly useful development in digital advertising, by interpreting data faster and more efficiently to predict future events. However, more important than the data are the human experts who can engineer that data in ways that add real value and accelerate growth for the business.

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