Machine Learning and Problem Solving in Businesses
Here we will see about some pointers for using machine learning to solve business problems in different sectors and a few practical applications to employ it in.
Machine learning’ is one of the popular buzzwords that have been slowly moving from the tech side to the other departments. 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 to employ it in.
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 usable and accurate 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 if the data you have is usable.
Is there a human contribution to the analysis?
What many forget when employing machine learning is that it can only know as much as the data you feed in. Any other information that is only known to humans can’t be predicted by the machine learning algorithms. Therefore, when you are working with a machine learning software, make sure the results obtained from the analysis make sense.
One example of this was reported by the machine learning researcher Rich Caruana. He and his team were using machine learning at the University of Pittsburgh Medical Center to study the complications developed by the pneumonia patients. When studying, they came across a disturbing pattern where the pneumonia patients who were also asthma sufferers were sent home as it was obtained from the model that said that the asthma sufferers never had any severe complications. What if failed to notice was that the asthma sufferers were almost immediately rushed into intensive care thereby preventing any casualties. This human factor when not included in the analysis of machine learning could cause in coming to improper conclusions.
How can you know if machine learning can solve your business problem?
It is no secret that machine learning can bring a significant difference and a positive result to the problem you have but you will also need to keep in mind the investment you need to put in for it. For the business problem that you have at hand, check whether if it is worthwhile enough to use machine learning and the investment you will be making for it.
Here are a few significant applications and solutions of machine learning that can be compared with the business problems you have:
Remember how Facebook automatically tags your friends accurately when you upload a group picture? Facebook started using machine learning to record the faces of the millions of Facebook users and store them and identifies them with the faces in the picture you upload.
This face recognition technique from Facebook is just one application of machine learning in image recognition. There are a lot of other applications in assembly lines in factories, in healthcare applications and it has also been tested out with the driverless cars.
This has been widely used by the marketing departments across all businesses. 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 is yet another department that every company will have no matter the size and the volume of the business. With the machine learning technology, businesses can now analyze the past data from the customer support and provide better services to the customers while also reducing the manpower.
An example of that is Zendesk, a popular CRM provider, which used machine learning technology for answer bot to provide self-help services to customers for the commonly asked questions. As mentioned by Zendesk, Forrester data shows that 76% of customers prefer self-service to a live phone call and therefore, Zendesk enabled the self-help service through machine learning by which customers can immediately get their queries answered without waiting on a call for simple questions.
This is majorly used in the e-commerce service sectors where the websites use machine learning to tempt the customers in 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.