Razorfish shows what a top-to-bottom connected retail experience would look like
Last week, at the Adobe Summit, interactive digital agency Razorfish gave marketers a whirlwind tours of what a top-to-bottom connected retail experience would look at feel like. Its hypothetical store demonstrated how it can take all the data and content trapped up in the cloud, where it serves 9% of all shoppers, and bring it into the store to create relevant personalised experiences for shoppers where 91% of purchase decisions are made.
Adobe Summit: Agency gives marketers a tour of top-to-bottom connected retail

Last week at the Adobe Summit in Salt Lake City, UT, interactive digital agency Razorfish Global gave marketers a whirlwind tour of what a top-to-bottom connected retail experience would look and feel like.

Called RZR Shop, its hypothetical store made use of mobile devices, interactive in-store screens and product RFID tagging. But it went beyond the shiny hardware and showed how those technologies could be combined with intelligent processes and real-time data to create a holistic “phygital” journey — Razorfish’s word for a digital experience in a physical space.

“What I mean is a store that takes all the awesome data and content that we have trapped up in the cloud, where it serves 9% of all shoppers, and we bring it down into the store, to create relevant personalized experiences for shoppers where 91% of purchase decisions are made,” said Jason Goldberg, Razorfish VP of commerce strategy and mastermind of the operation.

Adobe Marketing Cloud director of industry strategy Michael Klein played the customer/guinea pig for the demo. As a loyal return customer to a menswear outlet, he started by booking a consultation with a stylist on his mobile device.

Paul Elliott, EVP marketing and innovation for Rosetta, the customer engagement-focused subsidiary of Razorfish Global, played the digitally enabled stylist. As soon as Klein entered the store, Elliott got a notification on his tablet, telling him his appointment had arrived.

But Klein was eight minutes early, which, Elliott claimed, should give him enough time to quickly help another customer. “The algorithm tells me that because I can typically service other clients in that timeframe, I’m available to service someone,” explained Elliott.

The fictional new customer, Jennifer, got his attention by pinging him from her own mobile device. Along with her help request, Elliott saw info about what type of customer she is (an indulgent trend setter) and her favourite product category (jeans).

“I’m able to get at the science behind the art in preparation for this interaction,” said Elliott. “The intention here is for me to arm myself with an understanding of who Jennifer is, what motivates her, and what I can do to help her have the best experience.”

Jennifer was looking for a specific pair of pants she’d seen in a personalized email promotion. Since the email was designed within the Adobe Marketing Cloud — which also powers all of the in-store signage and store operations — Elliott can easily jump to the email to find the item and see whether it’s in stock.

Jennifer purchased the pants from Elliott on the spot, paying by credit card on his tablet. She decided to have the receipt emailed to her.

Then it was time to meet with Klein. He was looking for a new style, so Elliott pulled up the curated outfit he’d picked out for him, and swapped it onto a nearby 4K screen to create a “co-shopping” interface. The screen showed Klein hi-res images and details on each of the items Elliott had suggested.

Once Klein found something he liked and had the fit right, he swiped the screen’s contents onto his phone, and sent it to his wife to get her opinion.

At the last minute he decided he wanted to look for shoes. In the shoe department, the nearby signage, remembering the outfit he’d already picked out, showed several options for items that would match with what he planned to wear. When he selected a pair, he could see additional information like user ratings and reviews, pulled down from the cloud in real-time. If he wanted to try the shoes on, the shelf where the RFID-tagged item was displayed would light up to draw his attention.

With the customer visit complete, Elliott took a moment to show off the analytics that Adobe built from Klein’s transaction and others like it. As a manager, he could look at conversion rate effectiveness at the store, category or product level, plus detailed foot-traffic heatmaps and physical customer paths through the store, extracted from mobile beacon data, all on his tablet.

At least one audience member wasn’t impressed, saying the experience felt too invasive for the shopper, and all he really wanted to do was buy his pants.

But RZR Shop had an answer for that too. Embedded in the analytics available to each sales associate was a score showing the specific customer’s willingness to be engaged. A “self-sufficient” shopper scores a 0; Jennifer, who initiated the interaction with Elliott, scored a 6.

So the store of the future knows when to leave shoppers alone.

Goldberg made it clear that none of the individual technologies demoed by RZR Shop were new. All of them are already being used by retailers. But that doesn’t mean they’ve been figured out.

“What tends to happen is a retailer will say, ‘I’m going to put a digital sign in my store,'” he said. “Everyone comes and it looks great and we all break our arms patting ourselves on the back. But there’s no plan to ever change the content. No plan to ever measure whether it influences sales and refine the messaging based on how customers are behaving.”

What Razorfish is really doing is putting the various pieces together and creating a system that can be implemented at the scale of a national or international retail chain, on an ongoing, self-sustaining basis.

Most of RZR Shop is beneath the surface. It uses a range of tools from Adobe Marketing Cloud, like Adobe’s new Experience Manager Screens for cross-screen user experience design, as well as Adobe Analytics for measurement and Adobe Target to optimize content against different customer segments. On top of that, there was Razorfish’s Bluetooth Low-Energy Experience Platform (BLEEP) for mobile beacon interaction and Rosetta’s customer intelligence interface for the sales associate’s tablet app.

The way Goldberg sees it, all of those capabilities have already been developed and implemented in e-comm, and it’s just a matter of translating them to the physical store.

“What we’re showing here is, ‘Hey, you have the Adobe Marketing Cloud. You know how to produce content on an ongoing basis, you know how to optimize that content based on audience response. Let’s leverage all those disciplines on that big screen in the store and make it more scalable,'” said Goldberg.

Both Razorfish and Adobe are convinced that this kind of data-powered, interactive experience is a major growth opportunity for retailers. Speakers from both companies cited the Forrester stat that e-comm only makes up 9% of commerce interactions in the U.S. multiple times throughout the conference.

Meanwhile, Goldberg said, digital channels influence some 52% of all in-store sales. That’s not something retailers can ignore.