1. Search engine optimization:
According to a report from 2018, 4 in 5 customers use a search engine when shopping online. As the number of products in the eCommerce websites keeps going up, it is important that the search results are accurate and helpful for the users.
Machine learning can help in several ways to users such as search query predictions, sorting search suggestions as per the history, and putting extra focus on image and voice search. With this data-driven process, we can accurately determine what the users are looking for if we use machine learning.
2. Optimized results:
With machine learning in eCommerce sites, we can sort the search results page in a variety of ways. It could be as per the product category, relevance, sorted by price or featured. The relevancy of the products could be decided by using information from the user’s search engine, search history, order history, and profile information. Results that utilize a user’s data to procure optimized results have better chances of converting into sales rather than randomly generated results.
3. Inventory management:
Machine learning can help eCommerce store with the inventory management of all the products listed on the website. This is a very useful feature of ML in eCommerce because the more the number of products listed, the difficult it becomes to keep stock.
By understanding the sales reports and looking at the number of products left in the warehouse, it can help you determine which products need replenishment and which are still well-stocked.
4. Trend analysis:
It would be weird buying Christmas lights in May, wouldn’t it? ML in eCommerce studies customer behavior and predicts the wave of sales of products. Hence, it can analyze behavior and trends to understand which products will sell more during a particular time.
5. Better marketing strategy:
With predictions and trend analysis, it becomes much easier to understand what products are being sold more and when. Using ML in eCommerce can help you understand the mindset of your consumers better. If you tried to analyze all the data manually, it will not be as effective. Hence, this data and analysis can play an important role in your marketing strategies which can result in a growth in the number of sales.
6. Dynamic pricing:
Have you noticed that if you add a product to your cart and don’t place the order, then the price of the product drops after some time? (If you didn’t know this before, now you know how to get some extra discount!) This isn’t done manually but with the help of machine learning only. By keeping a track of all products, the algorithm specifically keeps changing the prices of all the products for users. This allows them to determine the best price for all the products and suggest. While displaying discounts, an optimal price and giving offers to customers, the ML algorithm also takes care of the warehouse inventory. This is done specifically to maximize the sales and keep a track of the inventory.
The Final Say
Machine learning in eCommerce helps add a new layer of depth that helps companies get the most from their online store. Based on these insights, eCommerce company owners can easily make better decisions, maximize their sales, market their company efficiently and understand the demands of their customers too. Since machine learning algorithms and use cases keep on learning to improve accuracy, there will be many more ways in which it will benefit the eCommerce industry. Therefore, the future of the eCommerce industry is very advanced and highly prosperous.