by Nikki Hallgrimsdottir

For decades, consumers have relied on friends and family, product reviews and tastemakers when making purchasing decisions. A loved one could recommend a particular brand that’s worked well for them over the years. A consumer watchdog publication could inform and educate on car models that offer the most reliability. A fashion magazine could highlight the latest trends that speak to a particular style. But while each of these different influencers remains relevant to today’s buyers, today’s shoppers seeking out buying advice are increasingly guided by artificial intelligence.

Through sophisticated AI, retailers are diving deeper into personalization by building solutions that suggest the best products for a user to purchase bolstered by data-driven insights.

Thanks to powerful AI-driven supply chain management, retailers can easily track what’s in store, what’s being shipped and what’s in the warehouse; ensuring customers can get what they want when they want it. But to create a more personalized shopping experience, retailers are also putting together better product collections, embracing trends like “showrooming” and crafting entirely new ways of shopping.

Here’s a look at how AI-driven personalization is transforming brick-and-mortar retailing:

1. b8ta

Retailers long maligned the trend of “showrooming” — that is, trying out a product in-store to make an eventual purchase online. AI-driven supply chain management allowed omnichannel retailing to alleviate some of these fears. New retailers like b8ta are embracing this trend by building new stores around the showrooming concept. Offering retail-as-a-service, b8ta is an open-concept store that provides companies a flexible way of selling through brick-and-mortar locations. Companies can showcase products in b8ta stores from online brands that desire a physical presence.

b8ta changes the game for consumers who wish to purchase something online but also want to see it in person. Online retailers with a wide range of SKUs can showcase their products with AI-gathered data for personalized product targeting.  A manufacturer can also offer a small sample of its most popular products for customers to try out in real life.

2. Amazon 4-Star

If you’re buying a kitchen gadget, how do you know it’s the best kitchen gadget? Well, if you’re Amazon, you know it’s the best because it has a wealth of rich customer purchasing data.

Amazon’s newest retail store in New York City: Amazon 4-star  carries a curated selection of products which received a large amount of four-star ratings. Amazon uses its sophisticated product recommendation engine to bring its bestselling, most popular items into physical stores.

By offering a hand-picked selection of products that are beloved, trending or hidden gems, the service allows customers to shop from a collection of highly personalized recommendations in a brick-and-mortar setting.

Considering 35 percent of Amazon’s revenue comes from its AI-enhanced product recommendations, it’s a profitable shortcut to give customers what they already want.

Selling only the top-rated products might also be the right approach for adjusting an existing retail strategy. In early 2018, home furnishing retailer Crate & Kids shuttered all physical locations of its children’s furniture chain. The Land of Nodand began offering a smaller, curated collection of the same products under its in-store label, Crate & Kids. For Crate & Kids, it became clear that offering a more personalized selection of products to its customers was more valuable than propping open underperforming retailers that featured wider selections.

3. AlgoFace

Buying new makeup can be a long and messy process. Dropping by Sephora or the makeup counter at Macy’s means waiting for an associate to help you apply lipstick or eyeshadow to find the perfect color — from a tube that’s already been used by somebody else.

AlgoFace is making this process simpler (and far more sanitary) through its virtual-makeup SDK,  available for makeup retailers to build into their apps. Shoppers can virtually apply an endless array of makeup shades to a live video of their face. Their AI-driven augmented reality interface makes it look like users are actually, physically wearing the makeup they’re thinking about buying.

The result isn’t just a highly personalized experience that lets users try out makeup combinations with no mess: It’s an incredible way to cut down on costs by saving on makeup samples. As for the customer experience, this means being able to try out different looks in a mobile app or at a physical location.

Nikki Hallgrimsdottir is a co-founder of algo.ai where she helps enterprises leverage Artificial Intelligence, Augmented Reality, and Data Analytics to transform their business. Nikki believes that the way we work, shop and play is changing, and pairing Human and Machine Intelligence in a responsible way can create a better future for all of us. Nikki and her family recently relocated to Seattle after spending 10 years in the San Francisco Bay Area.