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THERE IS LESS MYSTERY AND MORE BENEFITS IN MACHINE LEARNING THAN MANY THINK
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April 10, 2020
THERE IS LESS MYSTERY AND MORE BENEFITS IN MACHINE LEARNING THAN MANY THINK

There is a lot of talks these days about machine learning – but what is it? In simple terms (and there is no point in getting into the complexities) machine learning is cognitive technology. It is a subset of artificial intelligence, which focuses on using statistical techniques to build intelligent computer systems in order to learn from databases available to it. Currently, machine learning has been used in multiple fields and industries. For example, medical diagnosis, image processing, prediction, classification, learning association, regression etc.’

Research recently completed by international advisory Deloitte found that some 76% of businesses expect cognitive technologies to transform their businesses within two years. Some 16% suggest that this transformation is occurring now, and only 1% do not anticipate it happening at all. Machine learning will have a profound effect on marketing.

Applications of machine learning include:

  • Image recognition
  • Speech recognition
  • Statistical arbitrage
  • Learning associations
  • Classification
  • Prediction
  • Extraction
  • Regression

Applications of machine learning in marketing include:

  • Enhancing customer experiences
  • Creating new revenue streams
  • Developing new products and services
  • Content optimisation
  • Personalisation
  • Reducing waste
  • Engaging customers

The use of machine learning in marketing is increasing. Consider:

  • 75% of enterprises using machine learning enhance customer satisfaction by 10%+
  • 84% of marketing organisations are implementing expanded machine learning strategies
  • 3 in 4 organizations implementing machine learning increase sales of new products and services by more than 10% 

Machine learning generally involves two types of learning:

  • Unsupervised learning – group and interpret based only on input data.
  • Supervised learning – develop predictive model based on both input and output data.

In practical terms, machine learning involved taking data in varying quantities and from one or more sources to provide a basis for effective decision making. It is especially effective where large volumes of data from multiple sources are required. It is in essence a more sophisticated version of automated marketing analytics.

The team at DQ Australia is well versed in the range of issues relating to machine learning and its many applications in marketing. For now, suffice to say that machine learning is creating exciting opportunities for marketers and all business people should become more familiar with its potential.

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