It’s impossible to run a successful eCommerce business without using machine learning. Ecommerce sales amount to an astounding 4.88 trillion dollars globally. According to Gartner, 80% of customer interactions are all managed by AI. Using AI/ML is the next that helps your eCommerce business keep with your business competitive and compete with other eCommerce businesses
Ecommerce only exists thanks to advanced technology and the internet. Then, the next step forward was the worldwide spread of smartphones, putting online stores in virtually everyone’s back pocket. It’s no surprise that eCommerce would make use of AI and machine learning to help eCommerce businesses run smoothly.
Machine learning is having a great impact on eCommerce businesses worldwide. There are many ways in which machine learning can be applied within eCommerce.
Machine Learning for eCommerce
Almost every aspect of running an eCommerce business relies on machine learning. From the customer experience to inventory management, machine learning is at the forefront of innovation for online businesses. Here are some other benefits that machine learning has on the eCommerce industry.
1 Increased conversion rates
“Any online business relies on turning leads into dedicated shoppers and customers,” says Robert Smith, a business writer at the PhD Kingdom and Next Coursework. Machine learning algorithms yield smarter search results; through natural language processing, they can understand what’s typed in the search bar. Then they use what was learned from previous searches to show what the searcher truly wants.
Algorithms that power product recommendations are also smarter. These algorithms can analyse the behaviour of visitors to an eCommerce site. While a browser is visiting the store, they will look for products and possibly make a purchase or two.
With machine learning, the next time that same customer visits the site, that individual will be presented with similar items to those they’ve shown interest in before.
2 Price Optimization
People who shop online tend to be very price aware. “They want the best deal they can get and are less likely to buy it if the price online matches the price in-store,” says Julie Ventura, a journalist at Origin writings and Brit Student. They are more likely to go and assess the item first-hand at the shop and buy it while there. Online shoppers are also more likely to do price comparisons across several different online retailers, searching for the best deals.
Dynamic pricing is the best route for eCommerce businesses and with machine learning in place, it can change and readjust prices based on several factors, like competitor prices, product demand, and the like all at once.
3 Machine learning can help prevent fraud.
A lot of buyers, especially first-time buyers are nervous about online sales. They tend to believe that they are not secure enough, and it is somewhat true that eCommerce companies are particularly vulnerable to fraud, and they must be incredibly careful.
Fraud detection and online security is the area where online companies cannot afford to cut corners. Using machine learning, eCommerce businesses can help eliminate the scope of fraudulent activities drastically by detecting any anomalies in the data.
4 Run more targeted marketing campaigns.
The best marketing campaigns are campaigns which are very specific and reach their target audience. This is where machine learning and big data lend a helping hand. Businesses of all kinds, including eCommerce, have access to much more information than ever before. Machine learning helps eCommerce businesses make sense of all the customer data in order to make better, more targeted marketing campaigns that are more specific to what interests your customers.
5 Better customer support
If you want your business to remain the best, you have to have excellent customer support. It’s simply not enough to offer an amazing product. Customers despise calling helpline numbers, waiting on hold for too long, and spending ridiculous amounts of time listening to automated menu options. They want to talk to a person, not a machine. Worse still is waiting for impersonal email replies, which are usually delayed.
From the business side, it’s a challenge to keep up with customer complaints and requests. This is where machine learning helps eCommerce, by automating customer support and enabling self-service. Chatbots are a great example of the type of automation we are talking about. Chatbots are great at helping identify and resolve customer issues through natural conversation.
6 Make your operations run more efficiently.
While it’s true that machine learning helps the customer-facing end of your eCommerce business, there are plenty of algorithms that can help make your in-house operations run much more efficiently.
By analysing customer data using machine learning, you can manage your stock levels and account for inventory much more easily and swiftly. Not only that it can help predict future demand, as well as business costs like warehousing, and make accurate tax predictions as well.
7 Help you make more informed decisions
Machine learning is a great tool for vastly improved decision-making. Whether you are trying to decide your new product line is right for your business or to take a leap into dropshipping, you can make any eCommerce decision based on reliable data and have a pretty accurate idea of whether the decision is a good idea.
8 Omnichannel marketing can be boosted by machine learning
It’s a fact that omnichannel marketing boosts customer satisfaction and retention levels. We also know that omnichannel marketing is centred around customer data, or else how would you know if you were reaching your target audience successfully. Machine learning is based on gathering data and improving algorithms over time, as more data is collected. Therefore, using it to help your omnichannel marketing strategy makes a lot of sense. It will only become more powerful as data gets constantly updated.
Machine learning has so many positive benefits when paired with eCommerce business models. It offers a deeper insight into customer data, creating a seamless user experience, reaching more customers, and boosting sale conversions.