Big data helps retailers make better decisions. With the right data operation in place, any customer purchase or point-of-contact can become a useful piece of information that determines product strategies and identifies areas of improvement. Purchasing data, in particular, makes it easy to identify items or trends that are already popular with customers, guiding retailers towards offering customers products that they’re already interested in.

Here’s a look at a few retail companies that are using purchasing data to curate their own collections of best-selling products:

1. Coca-Cola

The Coca-Cola Company’s Freestyle soda fountain dispenses beverages in dozens of different flavors: from Diet Coke to sparkling Dasani water. Freestyle machines also let customers customize their flavor combinations, leading to thousands of different possibilities.

Armed with data gathered from the drinks customers were pouring for themselves, Coca-Cola determined new beverage flavors that were already a hit with customers to develop new retail products. One result was Cherry Sprite, a customer favorite that led to the release of its own ready-for-retail canned beverage.

2. Rent the Runway

The popular subscription fashion service Rent the Runway allows users to rent designer clothing on a one-time or recurring basis, giving subscribers access to high-end fashion at a fraction of the traditional retail price. To improve its product selection, Rent the Runway partnered with fashion designers Derek Lam, Prabal Gurung and Jason Wu to power its exclusive Designer Collective, a capsule of outfits created with the help of extensive customer feedback.

Using data gathered from customer surveys about each clothing rental’s fit, the occasion it was used for and the number of times it was worn, Rent the Runway helped the designers determine the types of rentals that were most popular with customers to help guide new designs.

3. Starbucks

Coffee giant Starbucks has embraced purchasing data to inform its entire retail operations. Using exclusive customer data gathered through its Starbucks Rewards loyalty program, the company gains insights into popular drink orders and determines how users are choosing to customize their beverages.

After data made it clear that customers don’t always add cream to iced coffee or add sugar to iced tea, Starbucks developed and released bottled unsweetened iced coffee and K-Cups of unsweetened tea to appeal to existing customer tastes. The frequency and popularity of customer purchases also help Starbucks determine where to build new locations, decide how to optimize its menu boards based on the weather or time of day and boost customer loyalty. 

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 of tools that’s worked well over the years. A consumer watchdog publication could inform and educate on which car models offer the most reliability. A fashion magazine could highlight the latest trends that speak to any style. But while each of these different influencers remains relevant to today’s buyers, shoppers seeking out buying advice are increasingly being 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 only to make an eventual purchase online. AI-driven supply chain management has allowed omnichannel retailing to alleviate some of these fears, but new retailers like b8ta have embraced this trend even further by building new stores around the showrooming concept. Offering retail-as-a-service, b8ta is an open-concept store that offers 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.

For consumers who wish to purchase something online but also want to see it in person, b8ta changes the game. And for online retailers with a wide range of SKUs or a limited desire to expand into physical retail, b8ta offers the best of both worlds by showcasing products for limited amounts of time. Combined with AI-gathered data for personalized product targeting, a manufacturer could take advantage of b8ta by offering a small sample of their most popular products that customers wish they could 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’s got a wealth of customer purchasing data behind it. This includes star ratings, which lets users rank products after they’ve been purchased.

That’s the core concept behind Amazon’s newest retail store in New York City: Amazon 4-star. Carrying a curated selection of products that have all received large amounts of four-star ratings, Amazon uses its sophisticated product recommendation engines 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 & Barrel shuttered all physical locations of its children’s furniture chain The Land of Nod and began offering a smaller, curated collection of the same products under its in-store label, Crate & Kids. For Crate & Barrel, it became clear that offering a more personalized selection of products to its customers was more valuable than propping up an underperforming retailer 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, which is 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 customer experience, this means being able to try out different looks in a mobile app or at a physical location.

 

Article originally published on Medium and reposted with permission from Humans for AI.

As the use of AI enabled platforms continue to grow within all industries and markets, we will also see a greater level of AI platforms being adopted by retail companies. There are four factors that will influence the adoption of AI in Retail:

Think Big, Start Small

Retailers who adopted AI early are already benefitting from this innovation. Retailers that are new to using AI in their day-to-day operations will benefit from starting with the “basics.” It is important for retailers to remember it is not about solving all their problems at once, but to focus on fixing one problem at a time. People often get caught up in the task at hand or distracted with too many problems. It is very important to remember the strategy of “test and learn.” Make one adjustment towards personalization for the consumer and test it before you move on to the next.

AI Boosts Conversions, Revenue, and Customer Satisfaction

IDC Retail insights predicts by 2019 40% of retailers will have developed a CX architecture supported by AI. IDC forecasts customer satisfaction scores to rise by 20%, employee productivity to rise by 15%, and inventory turnover to rise by 25%. This is all going to be possible due to AI paired with AR and IoT data which will give retail companies the ability to hyper-personalize each customer’s experience.

Mobile Devices Will Help AI Flourish

The vast majority of the population has access to mobile devices and conducts most their activities on these devices. This allows for a huge adoption in AI on this platform. The data collected from all these mobile devices will allow companies to improve their customer’s experience. One company that is already successfully implementing an AI platform is Starbucks. One thing their AI platform does is recommend specific orders for customers based on their prior purchase history. AI will play a big role influencing AI adoption in retail.

The Lack of Knowledge and Cultural Biases Will Hold Back the Adoption of AI

Two problems many companies face is the lack of knowledge and their cultural readiness for innovation within the company. These become a problem when people within the company are afraid to innovate new technology they don’t understand. Another hurdle retailers have to jump over is the cost of implementing an AI platform into their existing system.

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September 14, Talk Business and Politics

Machine learning falls under the realm of artificial intelligence (AI), and though the technology has been around for a long time, it’s becoming more relevant when married with big data, according to Amjad Hussain, CEO of Detroit-based Algomus, who provides AI assistance to retail and suppliers.

During a recent workshop in Bentonville, Hussain demonstrated how AI is used by some retail suppliers such as Sony. He said AI, when used as a business assistant, can enhance productivity in an office. Hussain said machine learning combined with human creativity creates collaborative intelligence. Mathematically, he said it’s something like 1 + 1 = 11.

“John Daly, senior vice president of worldwide production services at Sony Pictures, said the Algomus business assistant — aka Algo — makes it easy to target his underperforming stores and devise a plan to raise them.”

Read the Full Article Here