Machine Learning for Business Intelligence



Machine Learning for Business Intelligence

Even though advanced algorithms have been used in the field of Business Intelligence for many years, recent developments in Machine Learning (a branch of data science that gives computers the ability to learn without being explicitly programmed) have expanded the realm of their applications, and made Machine Learning a keystone of business Data Analytics.   

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New Possibilities

 Machine Learning technology, the engine behind Artificial Intelligence endeavours such as natural language recognition or self-driving cars, also has numerous applications in the field of Business Intelligence.

Combined with data mining/wrangling and traditional and Bayesian computational statistics, Machine Learning tools provide insights and techniques in a wide range of subjects, such as customer segmentation, anomaly detection, price optimisation or predictive analysis, enabling organisations to:

  • Optimise pricing policy
  • Increase accuracy of sales forecasts
  • Improve sell-through and margin (retailers)
  • Engage customers in differentiated ways relevant to their needs and tastes
  • Identify key customer groups to optimise growth and retention
  • Fine-tune marketing plans based on effective ROI
  • Adjust product offering to development priorities

Although priorities and ROI vary between sectors, Machine Learning techniques deliver value to virtually any industry, from online and brick and mortar retail to services and manufacturing.   

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The Human Factor

However powerful and diverse they have become, algorithms are only a part of the solution.

Essential to in unleashing the most value from available data lies in pairing the best set of algorithms with business objectives and the nature of the task at hand.

In order to provide the highest ROI, understanding business drivers, risks and opportunities is as important as technical expertise in Data Analytics.  

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