When was the last time you opened Netflix and decided to scroll through the new releases and categories at random? How much time did you waste browsing? Perhaps you gave up and didn’t watch anything at all? 

Compare this to opening the app and being greeted with the next episode of the documentary you were watching last night. When you’re finished, there’s a similar series lined up for your next binge, as well as a carousel of the shows everyone’s talking about right now. 

Your experience is personalized and powered by recommendations. You’re engaged and ready to press play. 

eCommerce is no different. Almost half of the shoppers have left an online store to buy from another site because they were overwhelmed by poorly curated or too many options, according to Accenture. They claim that this “burden of choice” means 91% of consumers are now more likely to shop with brands who remember them and provide relevant offers and recommendations.

Powered by AI

Onsite 1:1 personalization in search, navigation, and recommendations has been around for a while, but until now it was only retail giants like Amazon who were providing a truly customized experience. Advances in software solutions mean this is no longer the case, with platforms like Nextopia dynamically displaying AI-powered content on eCommerce sites with just a couple of lines of code.

AI-powered recommendations remove manual merchandising intervention and allow retailers to automatically display personalized content, from the products shown in a user’s search results to the special offers that apply to those items. Shoppers will find carefully tailored suggestions based on their personal browsing history, rather than a generic list of unrelated products, thereby shortening their path to purchase.

Personalizing Every Stage of the Journey

Even new visitors to your site can experience personalized recommendations. Whether based on dynamic bestsellers at that precise time and location or fueled by the behavior of other users from a similar demographic, you don’t necessarily need large volumes of data on an individual customer to start refining their experience. 

“People who purchased this item also viewed” is a consistently reliable way to cross-sell to those who have not yet established their individual preferences on your site. Not only can you display similar items, the option to suggest complementary products can increase average order value. If you’re considering buying those trousers, why not ‘complete the look’ with this matching blazer?

In fact, why not sign up for 10% off your first order while you’re browsing? The Accenture study found 83% of shoppers are willing to share their data to enable a personalized experience. The merchant captures that first vital piece of data about the new visitor, while the customer has an incentive to purchase and is on track to a more intuitive shopping experience.

Returning Visitors Become Repeat Buyers

Of course, the longer the user spends on your site, the more personalized and real-time your offering can become. If a new visitor searches for footwear-related keywords on a sports apparel site, they can then return to the homepage to find sneakers and running shoes displayed, rather than the default clothing offers. Or, if they view multiple pairs of men’s running shoes, their search results can begin to prioritize other men’s products, without the customer manually filtering by gender. 

Personalized recommendations don’t have to be exclusive to your site either. Triggered emails can have a significant impact on lowering cart abandonment rates as well as prompting follow-up purchases of similar or previously viewed products. 

The Future is Personal

Too much choice isn’t always a good thing. A highly personalized site can suggest the right product to your customer before they even realize what they’re looking for. As you begin to plan your eCommerce strategies for 2020, consider how AI-powered site search solutions could increase sales, improve customer satisfaction and start turning your browsers into buyers.

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