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3 Benefits Of Predictive Analytics For eCommerce

3 Benefits Of Predictive Analytics For eCommerce


To put it simply, Predictive Analytics involves using machine learning to analyze information and make predictions. Several years ago, adoption of the process was very limited due to the expense and the complexity of the adoption. This has all changed and now companies from various industries and different sizes are scrambling to employ predictive analytics solutions. Here are some valuable uses for predictive analytics in eCommerce:

  • Customer Suggestions and Promos

With Amazon cashing in on their highly lucrative recommendations and suggestions features, it’s no surprise that this is often the most cited example when predictive analytics benefits are discussed. Predictive analytics uses machine learning to understand a customer’s specific behavior, including past purchases matched with the general trends and performance of various products on the eCommerce site, to come up with relevant suggestions that have a greater chance of creating a sale.

When it comes to promotions, predictive analytics works the same way. It identifies deals that have been successful before and then suggest the most ideal promos in real-time based on a customer’s patterns.

  • Predictive Search

One of the major ways that a customer interacts with an eCommerce site is through their search function. If their site search is made to be more predictive and able to anticipate what a potential client is looking for, customers are more likely to make a purchase. Results from predictive search is determined after an analysis of customer history, preferences and click-through behavior—all done in real-time. Relevant matches are shown with the help of continuous analysis, and most solutions are cloud-based and easily deployed. It looks simple to the consumer, and it was designed that way. Effortless search is a must especially when competitors are only a click away.

  • Managing Prices

An underrated benefit of predictive analytics is its pricing management capabilities. It analyzes current trends in pricing in correlation with sales data to determine the ideal prices at a certain time in order to maximize profit and revenue. Store pricing is managed with the use of a predictive model that references historical data for customers, sales and products. With this model, the price of a specific item can be predicted any time.


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