Ecommerce has always been an industry disruptor. From rocking the brick and mortar industry and forcing traditional retailers to rethink the way they do business to riding on the back of technological advancements like mobile apps and e-wallets, the eCommerce sector continues to reinvent the game. This constant evolution, all to keep the customer engaged and delighted has made the field of play extremely interesting to watch. Now, advanced technologies like Machine Learning (ML) and Artificial Intelligence (AI) are set to change the game again.
An interesting disruption is taking place which will further change the way retailers sell and consumers buy. Machine Learning capabilities are attempting to solve real-world issues, moving beyond customer segmentation. The COVID-19 pandemic has accelerated this development for many companies. According to Servion Global Solutions, by 2025, 95% of all customer interactions will be controlled by AI technologies.
Better Inventory Management
Supply chain management is a domain where industry leaders have been working hard for technological advancements over the past decade. Machine Learning can help eCommerce companies optimize business operations in ways that appeared science fiction decades ago, from planning next month’s shelf supply based on satellite data to inventory management of all the products listed on company’s website. Additionally, ML can determine if a product is well-stocked or needs replenishment.
Chatbots for Personalised Product Recommendations
E-commerce websites offer a wide variety of products which often lead to confusion or difficulty in finding the product of your choice. The prime objective of incorporating ML in eCommerce is to make buying easier for the customers. There is where chatbots play a major role, beginning the era of conversational eCommerce. Chatbots enable brands to learn from customer input, interact with them through virtual avatars, and fine-tune their responses for accuracy. They lead the users to the desired item they are searching for, making the purchase process easy and pleasant.
Faster Product Discovery
A typical eCommerce website has thousands of products across various categories, often uncountable. When the variety is so vast, helping the customer find the right product from the store catalogue can be a daunting task. Here, Machine learning can be a great value addition. It can connect the dots between the customer profile criteria like location, age, gender, buying habits, previous product views etc.
Trend Analysis
Predicting user behaviour, preferences and trends is a difficult task and almost impossible without the assistance of technology. ML in eCommerce makes this difficult task possible and easier. It can study customer behaviour and predict the wave of sales of products i.e. which products will be more in demand during a particular time.
Better Marketing Strategy
With trend analysis and consumer behaviour prediction, it becomes possible to understand which products are in demand and when. Once you understand the mindset of your consumers better with ML, you can prepare an effective marketing strategy that can result in a growth in sales.
Dynamic Pricing
We often wonder how the price of a product keeps fluctuating on an eCommerce website, for instance, when we add a product to the cart but don’t place the order, then the price drops after some days. This is done through ML and not manually. The algorithms keep track of all products, and keep changing product prices, determining the best price for all products for users. While doing so, the algorithm also takes care of warehouse inventory.
Summing Up
Machine learning in eCommerce helps in better decisions, efficient marketing of the company, maximizing sales and better understanding the demands of customers. Since ML algorithms keep on evolving, it will continue to benefit the eCommerce industry in a better way.
By Rajeev Kumar Aggarwal, CEO, StoreHippo
Credit: Google News
