The eCommerce industry is growing exponentially with the growing technologies. The growth is equally fueled with complexity. Those who go hand-in-hand with the latest trends, survive, leaving behind the rest. When we talk about emerging technologies, Machine Learning is the most harnessed trend in eCommerce today.
Machine Learning enabled eCommerce tools are being effectively used by the companies to push the limits of innovation, create value for customers, and accelerate revenue generation.
Here, we will have a look at how market leaders are using machine learning in eCommerce, and you should too to grow your online business.
1. Smart Search
Source: fastsimon.com
Machine learning software can help integrate voice search and image search features to your online store. Online buyers find it easy to search the product they require by uploading an image or expressing their exact information through voice search. Machine learning also enables automatic spelling correction to the search queries inserted by the buyers delivering intelligent results. Sometimes, the buyers cannot express what they are looking for in the textual form; machine learning helps overcome this challenge.
2. Personalized Recommendations
Machine Learning software is used to cater the online shoppers with personalized recommendations based on their browsing history, past purchases, demographics, preferences, and other metrics. ML-based recommendations include product, category, and price suggestions and deliver real-time targeted notifications to buyers. This helps online businesses to deliver a delightful shopping experience and gain customer loyalty and accelerated sales.
3. Calculating CLV (Customer Lifetime Value)
Machine Learning has the potential to calculate the customer lifetime value based on past purchases accurately. The customers with high CLV deserve your special attention in terms of offers and discounts. Machine Learning software allows you to treat the customers with high CLV in a special way and thus earn their loyalty and more business.
4. Inventory Management
Source: prismvs.com
Inventory is the lifeblood of eCommerce businesses and, if not managed properly, can create unhealthy situations. Machine Learning integrated into eCommerce applications can help predict the drop or rise in sales activities enabling you to analyze the inventory requirements accurately and thus eliminating the overstocking and low stocking issues. ML can help with certain decisions like introducing new discounts on the overstocked products and placing orders for the products in high demand so that there are no missed sales opportunities.
5. Fraud Detection
eCommerce is at the highest risk to online frauds and scams. Machine Learning can help online stores protect themselves and their customers from fraud by identifying suspicious and abnormal activities like fake returns, different shipping and billing addresses, the customer spends a higher amount than their usual spending behavior and many more such instances. ML has the ability to catch implicit cases with the help of existing data and can also evolve with each new consumer behavior pattern on a real-time basis.
6. Controlling Returns
Providing the product returns facility to the customers is a great relief for them and benefits online business. But, many customers misuse this facility by returning the fake products and keeping the originals with them or unnecessarily ordering and returning items they don’t need. This can be a massive loss to the business in terms of high spending on shipping and handling costs. If the product is returned in bad condition, then it becomes scrap for you. Thus, implementing ML-based features like virtual dressing rooms and size fitting tools can help in reducing the instances of returns and, at the same time, achieve customer satisfaction.
7. Managing Prospects and Customers
Source: pcmag.com
Machine Learning features in CRM can help you manage your prospects and customers more effectively using minimum human resources. It helps in predicting and prioritizing the leads that need to be focused on first. Cart abandonment is another obstacle to online sales. The machine learning features in eCommerce applications help analyze the reasons for cart abandonment and planning strategies that help reduce cart abandonment issues.
8. Churn Prediction
Customer churn is calculated based on the number of customers that stop buying from a particular store and start buying from their competitor. Machine Learning algorithms can deliver the data relating to what customers do when they are about to churn. This valuable information can help you stop the instances that encourage customer churn. Also, you can customize and tweak your marketing campaigns to keep your customers onboard and experience improved sales figures.
Conclusion
Machine Learning benefits the eCommerce business in terms of satisfied customers and increased conversions. Machine Learning can be applied in every facet of eCommerce, whether in-house operations, inventory management, or executing innovative marketing campaigns. The secret behind the success of machine learning in eCommerce is its ability of algorithms that can deliver highly invaluable data beneficial to make smarter decisions.
Thus, the benefits of Machine Learning for eCommerce businesses are many. If you are running an eCommerce business and you are yet to invest in an eCommerce tool that has MI-based features, then this is the right time.. From inventory management to shopping experience, integrating machine learning in eCommerce software can help you excel at everything and make you more efficient.
Including machine learning in your online business may be easier than you perceive it to be. You just need to find and execute the best eCommerce software that includes machine learning features and make its optimum use to achieve your predetermined business goals. If you are finding it challenging to select the right option, just go through the Goodfirms’ list of eCommerce software and make your search process quick and easy.
