These days, technology is more sophisticated than ever, especially when it comes to artificial intelligence (AI). The most advanced systems can now do things that were previously only possible for humans to do, and they are assisting organizations in making better business decisions than ever before.
Machine learning, a type of AI in which computers can improve and adapt their processes without being explicitly programmed by a human, has proven particularly useful for people who do business by selling products or services online.
If you run an eCommerce business, there are a number of ways you can harness the power of machine learning to provide a better user experience, become more agile, and open up previously inaccessible revenue streams.
Recognize patterns and trends
Wouldn’t it be great if you could truly understand what makes your average customer tick, what they require, and what they think of your products or services?
Machine learning can bring the Holy Grail closer than ever before by identifying trends and discovering patterns in large amounts of data without being programmed to recognize the pattern or trend. It’s easy to see why more and more eCommerce companies are shifting away from manual analysis and toward machine learning. It’s agile, accurate, and automated.
Product search has been vastly improved
The importance of search in the success of any eCommerce business cannot be overstated. How will potential customers know you exist if your products do not appear in front of them? Machine learning algorithms can significantly improve eCommerce product search results, thereby increasing click rates, customer ratings, and conversions.
Machine learning allows users to get so much more out of their search experience and can pinpoint the products or services they are looking for with pinpoint accuracy. When machine learning is strategically integrated into the search process, search results become more meaningful and tailored to the shopper’s actual needs rather than what they typed into the search bar.
Product recommendations
Product recommendations are one of the most effective forms of marketing in on-site merchandising. To determine when and how to make a recommendation, current product recommendation solutions typically analyze a product’s popularity.
Machine learning, on the other hand, will draw on more specific and individual data, such as a shopper’s specific purchasing habits, preferred colors or looks, and the type of budget they may have to work with. Going a step further, a machine-learning solution can prioritize product recommendations that are most likely to generate revenue or incremental sales.
While many larger retail corporations are already utilizing machine learning to determine how to recommend products, there are numerous third-party tools available to assist smaller businesses in harnessing the same technology.
Is machine learning appropriate for your company?
The robots are on their way, and they aren’t just coming to steal our jobs and take over the world as we know it. Machine learning is set to become a huge asset for eCommerce companies looking to automate many of their most resource-intensive and costly manual processes in order to gain meaningful insights about their customers and, more importantly, to generate clicks, purchases, repeat visits, and positive ratings.