5 Ways Machine Learning is a Perfect Fit in Ecommerce

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The ecommerce industry has evolved to be one of the most competitive and crowded spaces. With so many ecommerce platforms to choose from, retaining the customer in your business is becoming all the more difficult by the day. Thankfully, we have technological advancements that can help you better serve your customers and grow your business. Yes, we are talking about machine learning in ecommerce.

Machine learning is a subset of artificial intelligence that has been creating immense value for retailers today. Machine learning algorithms are trained using multiple datasets, to improve their performance over time with experience. What are the applications of machine learning in ecommerce, you ask? There are plenty of machine learning use cases. Let’s discuss 5 use cases in detail:

5 Use Cases of Machine Learning in Ecommerce

  1. Product Recommendation

The most widely used application of machine learning in ecommerce is the recommendation engine. An effective product recommendation engine can help contribute largely to your revenue and average order value (AOV).

A recommendation algorithm is a powerful data filtering tool that uses machine learning algorithms to recommend the most relevant product to a customer. The algorithms tap into relevant details like last bought product, buying habits, the colors they prefer, usual budgets, etc. to recommend products that the customer is most likely to buy.

2.  Dynamic Pricing

In today’s competitive markets, pricing strategy is the name of the game. Businesses are well aware that buyers like to compare pricing of the same product across different ecommerce platforms before finalizing on their purchase. Today, retailers and ecommerce platforms, big and small, make use of machine learning algorithms to offer dynamic pricing.

Machine learning enables retailers to calibrate the prices based on different factors like supply, demand, minimum price, operating costs, competition, etc. All of this would be incredibly difficult to do manually. Machine learning automates vast amounts of data collection, processing, analysis to offer better dynamic pricing in real time. This also helps businesses in anticipating early trends and predicting demands for products that do not have transaction data.

3. Enhanced Search Results

As an ecommerce platform, It is crucial to have all the necessary products in stock, but it is even more important that the customers be able to conveniently find the products that they are looking for. Hence, the search feature’s efficiency is a critical factor in deciding whether your customers stick around on your platform.

Searches are powered by keywords but not all buyers are great with them. For buyers to easily be able to find the products, machine learning has a solution. Machine learning algorithms enable optimized search results by identifying patterns in search, purchases, clicks, and preferences. Search results based on machine learning help customers easily find products that they are looking for, and also suggest similar and relevant products.

4.  Fraud Detection and Prevention

First-time online shoppers are often unsure of the security of ecommerce platforms. Moreover, ecommerce companies are often susceptible to fraudulent activities regarding the users’ data, transaction details, etc. Such data breaches not only harm the customers, but also the company’s reputation, thereby forcing them to shut shop.

Thus, it becomes very important for companies to invest in advanced technologies like machine learning and artificial intelligence to detect and prevent fraud. Machine learning in fraud detection can easily process large volumes of data and detect unusual behavior, thereby preventing fraud. This also means that the machine processing data and flagging anomalies will be more efficient and quicker than manual analysis performed by humans.

5. Forecasting

Managing demand and supply is crucial to maintaining smooth operations in the company. For accurately forecasting demands and having adequate amounts of supply, it is important decisions are backed by data.

Machine learning algorithms are capable of processing exhaustive amounts of data. This makes machine learning a very effective solution in accurately managing demand and supply. Machine learning algorithms are also capable of analyzing the data and deriving insights that can help the company better understand customers and improve their products.

Wrapping It Up

Looking at the immense value provided by machine learning in ecommerce, more and more companies are willing to invest in tech solutions that empower their customers and enhance their products.

At Maruti Techlabs, our machine learning services ensure that we enable rapid decision making, quicker anomaly detection, and business process automation for our clients. We have worked with companies from across the globe and implemented customized solutions tailor-made for each business. If you too are keen on finding out how machine learning solutions can help your business, feel free to reach us.


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