If you are a small business owner, you probably can’t go a day without hearing or reading about the phrase “machine learning”. Machine learning is a subset of the wider field of artificial intelligence. In the simplest sense, machine learning is the area of technology where computers are fed large amounts of data which the machine then applies algorithms to. This enables the computers to find patterns and make accurate predictions based on that data without any human intervention.
Finding Hidden Patterns Within Your Customer Base
One way your small business can immediately benefit from machine learning is by finding hidden patterns within your current customers’ habits and then utilizing those patterns to sell more products or services. One type of machine learning algorithm is called clustering. These mathematical models find way to group data sets into meaningful buckets that perhaps a human couldn’t easily do or even consider. In this case, machine learning can help you perform customer segmentation in revolutionary ways. Once you are aware of these new groupings, you can easily tailor your business offerings to a bunch of warm leads and likely increase revenue in a short period of time. You can contract an outside programmer who specializes in machine learning to create this analysis for you, but you can also utilize relatively inexpensive cloud-based solutions from companies such as IBM and Amazon.
Making Product Recommendations
Another great way to use machine learning to grow your business is to utilize machine learning recommender systems. The perfect of example of a machine learning recommender system is on Amazon’s website. Based on the data of millions of customers’ buying and browsing habits, Amazon “knows” which specific products you are likely to purchase. Then it places those products right in front of you.
But recommender systems aren’t just for big companies like Amazon. Any business with an online or mobile presence can develop and deploy one of these systems. Netflix uses one to recommend movies you might like, LinkedIn uses one to predict people you may know, BestBuy grew its online sales using a recommender system, and the list goes on. If you sell products or services online, you too can improve your business sales with a recommender system. The caveat is that these are complicated systems that take lots of time and money to build.
Fraud Protection and Data Filtering
Depending on your business and platform, you might find it very useful to use machine learning for fraud protection and data filtering purposes. These types of problems fall in the machine learning bucket known as classification problems. If you run an online business, these machine learning capabilities may be even more important to you. Algorithms applied to fraud protection can help decide whether a financial transaction is real or fake.
A classic example of machine learning applied to data filtering is spam filtering for email. Based on various pieces of data within the email (and some data not seen by the email reader), algorithms can decide whether the email is legitimate or fake. These types of algorithms can be applied to other problems such as whether a user’s posted comment or content is age-appropriate, against company rules, and so on.
Machine learning is certainly here to stay, and as its adoption among businesses begins to grow, its capabilities will increase and the costs associated with using it will go down. It is very likely that your competitors will use the technology going forward, and for your business to stay competitive, you should continue to stay aware of the news and changes in the machine learning sphere so that you know what machine learning technology is available for your business.