Online retailers have long been able to provide product recommendations based on factors such as previous purchase history, items viewed, keywords, and price points. With advances in e-commerce technology and big data for retail, retailers can now tailor product and content recommendations to customers based on the context of their current shopping visit, their intent signals,, the products they engagement with and how they behave relative to the thousands of other shoppers before them.
Using personalization to anticipate and meet the needs of shoppers in the moment helps retailers to drive conversion rates, order values and additional revenue.
By focusing on retail trends prominent in social media and elsewhere, smart retailers can tailor product recommendations to each demographic, or even each customer with pinpoint detail. Retailers can then begin to automate difficult tasks, including price point tracking, inventory tracking, and developing promotions in real time, based on location, and other factors, which can increase related sales, and further drive revenue.
The retail industry is changing rapidly. It’s important to capitalize on these changes by taking advantage of all of the customer data that is created with every web shopping visit. Big data for retail is a popular term these days. But what does it mean? It means simply that by aggregating and analyzing this data, retailers can make intelligent marketing decisions, which can grow revenue from your online marketing efforts.