Machine learning analyses raw data and provides helpful information as an output. Businesses in various industries can benefit from it, so many companies are now adopting this in their operation. Below are some ways how machine learning is beneficial to businesses.
Improve customer satisfaction
One of the most popular uses of machine learning today is in e-commerce. Many people do their shopping online, and artificial intelligence or AI determines users’ interests based on patterns, including items previously purchased and those they often search. Based on this information, the site offers them recommendations of things that they might be interested in, which will make them happier since it makes their shopping experience more efficient.
With improved customer satisfaction, business sales may also increase. With the customers seeing more of the things they like, there is a higher chance that they will purchase something from e-commerce sites. In addition, the more the users browse the site and purchase items, the more the site will learn about their buying behavior, thus helping businesses tailor their offerings to them. For instance, if a user often searches for a diamond ring, and your site has diamond rings on sale, you may show this on their next visit as something they might be interested in, or perhaps send them a marketing email about the deal.
Fraud is prevalent, so companies must be extra careful with their online and offline security. Anti-virus and firewall prevent these attacks, and all of these are included in machine learning. For instance, anti-virus software has a set of characteristics that will help determine a potential attack. Another example of machine learning is fraud detection when you log in to your email in different locations. It determines which devices and locations you often log in, and gives you an extra authentication step if it detects an unusual login. Therefore, it prevents unauthorized access to your account, especially if it’s a business email containing vital information.
Another use of machines in learning in business is image recognition. An example of this is an AI that can detect which apples are ready for harvest. However, ineffective data labelling may cause an issue and may prevent the algorithm from working correctly. Images must be labelled appropriately so that the program can effectively detect once the apples are ready for picking. Another use of image recognition is at the workplace. Biometrics like face recognition or fingerprint detection is used in gaining employees’ access and recording time when they clock in for work. The right personnel or the IT team will get the picture or thumbprint of the employees and label them with their names to generate the correct information once they enter the workplace. It ensures the security of the work premise as it guarantees that only authorized personnel have access to specific areas. Automating the entry also provides accurate and more convenient time tracking on employees.
Email providers use AI to identify which emails are spam or not. It is helpful as it can save business owners or employees dealing with emails time handling all the emails themselves. Going through a long list of emails and eliminating spam can be a time-waster. As you report certain emails as spam, the AI will learn what you consider junk so that they will go straight to the spam folder next time. It becomes more and more accurate as time goes by as it learns more about your preference.
Medical practitioners also use machine learning to efficiently analyze data and make diagnoses and treatments based on the result. It helps in giving a more accurate output, which is beneficial for the patients as they will know the best course of action to take. It also greatly benefits the physicians as they can give the best service to their patients, thus building their names and making them more trustworthy.
Machine learning is also widely used in the finance industry. A popular example of this is the stock exchange. AI determines the flow of stocks and gives forecasts, which is beneficial to traders. Fraud happens not only in networks and computing but in finances too. AI can help determine forged financial documents, thus preventing loss to the company.
Accuracy in data entry
Data entry is a typical process in many businesses. If working with a long list of data and more are added each day, it can be hard to determine which ones are duplicates. Machine learning can detect a duplicate entry, so you can delete it and keep the items on the list unique. Plus, in the advancing age of data-driven decisions, learning tools like Power BI would be quite useful.
These are just some of the benefits of machine learning on businesses. As long as it’s used efficiently, it will help with the growth and development of the company.