Where I can apply Machine Learning?

Your company may not be the size of Netflix or Amazon, but you can still apply Machine Learning to make it better. This technology can be used to define and apply strategies, predict future actions and optimize and automate processes in areas as diverse as marketing, operations, human resources or finance.

For example, in marketing and customer service. It is not enough to have a good (and updated) database: the more you know your customers, the better offer you can give to meet their needs. But you shouldn’t stay with what they tell you; thanks to this technology you can discover patterns of behavior that might otherwise stay unnoticed.

By applying Machine Learning you can optimize customer profiles to the maximum, which allows you to identify and understand them better, being able to take the necessary measures to retain them or improve the services. Additionally, it is possible to predict the income that each client will contribute in the future. This allows you to customize the actions of marketing and customer service, relying on the knowledge about them.

Moreover, Machine Learning is also applicable to pricing policy through so-called dynamic pricing. Times, when there were a fixed price and a period of sales, are far away. The hotel industry and the flight ticket industry are examples of dynamic pricing - prices that change depending on the current market demands. For this strategy to be effective and profitable for the company, all possible data must be considered, but a lot of that data is not evident or accessible unless you have the ability to process Big Data and use computational calculation.

Fraud detection is another area where you can apply Machine Learning. In the insurance sector, Machine Learning is used together with business rules to detect the risk of each client based on the likelihood of committing some type of fraud or in the finance sector, Machine Learning is used for credit granting and risk analysis.

What about you? Are you already using Machine Learning in some industries that we didn’t mention?

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