Every day, new applications for machine learning combined with big data and artificial intelligence has been doing its rounds in almost all fields. With Google, Amazon and Microsoft introducing their own machine learning platforms, it has attained newer levels of fame!

Here are some pointers for using machine learning to solve problems in different sectors and a few practical applications.

Do you have sufficient data? Relevant, authentic and useful data is important for implementing any solution through machine learning. One cannot stress enough on the importance of clean data, which is essential to get accurate and usable results.

If you have a lot of unstructured data or inaccurate data, there is a high chance that the results won't be worth the effort. Therefore, before you implement machine learning techniques to solve a problem, think about the data you have and it's usability. Also,are there human contributions to the analysis?

What many forget when employing machine learning is that it can only know as much as the data you feed in. Information that is only known by human can’t be predicted by the machine learning algorithm.

How can you know if machine learning can solve your business problem? There's no secret that machine learning can bring a significant difference and positive results to the problem you have but, you will also need to be mindful of the investment needed in time and money to get it set up and running. The first question, "Is the business problem you have, costing your company enough to use machine learning and are the answers worth investment?".

Here are a few significant applications and solutions of machine learning that can be compared with the business problems:

Customer Segmentation - Customer retention, churn prediction and lead generation have always been a major challenge for all marketers but with the advancements in machine learning, marketers can now eliminate the guesswork and get real-time, accurate results in customer segmentation from the past and current data. Marketers can now get the complete analysis of each segment’s behavior which can be leveraged in their marketing campaigns for more specific results.

Customer Service - Customer service is a department that every company has no matter the size and volume of the business. With machine learning technology, businesses can analyze past data from customer support and provide better services to customer while also reducing the manpower.

Product Recommendations - This is used in e-commerce where websites use machine learning to tempt the customers into buying more things. Remember the section of ‘Also Bought’ in many popular e-commerce websites where you will be displayed related items for the things you just added to a cart?

This has been widely used by almost all online shopping websites where, based on the customer historical data of the individual customer and the total gathered data, the top predicted things that the customer will most likely buy will be displayed in the home page and in some sections of the product pages too.

Machine learning can definitely make a major impact in solving the business problems if the right approach and the right set of data are used.

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