Future-Proof Your E-Commerce Marketplace: Applications of Machine Learning

Anyone can start an e-commerce marketplace easily and gradually let vendors list their products, but what after that? As the technology is moving at a faster pace, a product or a service popular today can easily become redundant in the near future. Why will people want to come to your e-commerce marketplace again and again? The work of an e-commerce owner does not simply stop after seeing few products which are getting sold every day.

To ensure a steady supply of buyers, you need to future-proof your marketplace because if you do not, your competitors will overtake your business and you will not be able to satisfy the growing demands of hungry buyers.

So, this post talks about several facts where machine learning can help in redefining future of e-commerce sector at a faster rate.

Smart Recommendations

Both the big and small e-commerce portals are already using product recommendations based on search and buying history. Two major companies Amazon and Google are pushing the limits of machine learning to recommend the most relevant products for its customers, which is personalized for each user. It is based on a collection of data on each customer.

Better Customer Segmentation

Creating customer segments is very crucial to maximizing the reach of your e-commerce store. Customer segmentation analysis, in most cases, is judged on the basis of age, gender, demographics and more, but, it is important to consider various other indicators as well. Machine learning can help e-commerce marketplaces to uncover new customer segments with similar sort of behavior.

Real-time Solution to Customer Queries

Answering queries from buyers and sellers in real-time require an e-commerce marketplace to hire a team which can provide support 24*7 around the clock. Machine learning and Artificial Intelligence-based solutions, such as chatbots, can prove to be a good return on investment as they can answer the questions of buyers and sellers quickly and easily.

Some of the examples of machine learning driven smart assistants include Apple's Siri, Google Assistant, and Amazon Echo.

Fraud Pattern Analysis

E-commerce marketplaces get spam orders across the board and are also prone to some of the online frauds. No technology is completely secure and this is why it is important to take several preventive measures. Machine learning technique can be used to fight online fraud.

With machine learning, the algorithms can learn from the knowledge base as well as observe patterns to figure out the probability of a fraud. Since machine learning involves constant learning, the algorithms can be programmed to easily optimize its accuracy.

Customer Churn Predictions

Most e-commerce marketplaces spend huge money on getting new customers, but they fail to understand that retaining old customers can be highly profitable and more economical. Excessive churn rate can make an owner take drastic steps that can prove catastrophic for the health of the marketplace.

Demand Estimation

Why spend hours in reviewing monthly, quarterly and yearly sales to estimate the growing demand? Getting the right demand estimates is important for an e-commerce business as it is important to know if your marketplace has a limited amount of stock or in bulk. In both cases, the owner suffers a financial loss.

Always keep in mind that demand and supply go hand in hand but foreseeing the growing demand can only be done with the algorithms of machine learning. Not just demand, machine learning can be used for easy delivery route optimization, grouping of orders, warehouse space optimization, and many more.