With the adoption of mobile, over the past decades, e-commerce has grown at a notable level, by bringing shopping literally into consumers’ hands. Technologies impact every stage of the customer’s online shopping journey —from personalized marketing to price managing, and behavioral analytics.

One of the most influential technologies in the industry - retail predictive analytics. Business owners are aware of the fact that providing value through a targeted campaign is no longer enough. The ability to be the first who predict trends is a new distinguishing factor.

Wonder, how predictive analytics work? Read the article to answer this question.

How is eCommerce predictive analytics works?

Predictive analytics is statistical modeling that analyzes historical data, and with the help of different techniques, methods and tool (data mining, data modeling, deep learning, machine learning, and AI algorithms) make predictions on the future. Predictive analytics in the retail industry understand risks and opportunities, analyze buyers’ behavior, assist with inventory management with the help of the data patterns that are possible to predict. In simple words, predictive analytics turn past and current data into valuable future actions.

Also, eCommerce predictive analytics covers what if?’ scenarios: what if I raise the price in April by four percent? What if I add another sales promotion in May?

This year the market is expected to reach up to $11 billion in revenue, compared to $7 billion in 2020. Because more and more businesses make use of predictive analytics in retail and other industries.

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