RetailNext wants to help brick-and-mortar retailers adapt to an ever-evolving digital world.
“E-commerce is real and it is disrupting a lot of different business models,” said Alexei Agratchev, chief executive officer of RetailNext. “Customers are comparing prices, reading reviews and social media can amplify experiences that happen in stores.”
To date, the seven-year-old company has raised almost $60 million from August Capital, StarVest Partners, American Express, Activant Capital and others to help retailers collect and analyze data pertaining to the in-store experience.
Today, the customer is in charge and retailers have to adapt to this, he said. In order to do so, companies must find the optimal mix of online, mobile and stores; maintain a branded experience across all channels, institute a flawless in-store experience and use analytics to continually monitor shoppers across channels.
He said the questions RetailNext frequently gets from retailers include: What does it mean that traffic is down but conversion is up? Why are shoppers spending half their time on their phones? Why do they buy? Why do they not buy?
Perhaps most importantly, he urged the offline world to use technology to better listen to customers.
He said shoppers will allow retailers to collect data if those stores are going to do something positive with the information. “But they have to trust you as a brand,” Agratchev cautioned, noting that online retailers use data to continually enhance the shopping experience, while their brick-and-mortar counterparts “look and feel similar to how they did 15 years ago.”
He compared images of Amazon’s homepage from 1999 and Macy’s homepage from 1997 to how each site looks today, highlighting the massive innovations each has undergone.
He cited brands such as Bonobos, Rent the Runway and Warby Parker as disrupting the retail world, explaining that their stores can access analytics in three separate layers of information to weld shopping across all platforms.
The first layer, “in-store activity,” looks at what customers are doing in the store without actually knowing the identity of each person, such as when they come in, where they go and how they interact with sales associates. The next layer, “shopperbase analytics,” looks at attributes of consumers such as gender, age, whether they are a new or repeat customer and cross-store spending. The program also uses video to gather information to understand the shopping process better.
“You can also see the common path for males who purchase in the same store, [as well as] the flow for women ages 30 to 39 who purchased versus those who didn’t. You can [even] get data on where they spent money before and after they entered your store,” Agratchev said, adding that while in-store, you can see what other sites consumers visited.
The last layer, which is opt-in only, allows the retailer to go deeper using mobile devices integrated in displays and fixtures.