Making a splash

Upstarts poised to impact retail in 2017
Startups have flooded the retail industry in recent years, defying norms and upending traditional ways of doing business. Backed by a steady flow of venture capital, the retail industry has been the beneficiary of hundreds of new technologies poised to reshape the customer experience, reorient supply chain and logistics and retool digital marketing.

STORES worked with Ken Seiff, managing partner of Beanstalk Ventures; Scott Friend, managing director of Bain Capital Ventures; Deborah Weinswig, managing director of Fung Global Retail & Technology; and Jeff Hoffman, co-founder of ColorJar, to identify five retail startups expected to make a big splash in 2017. If you’re attending Retail’s BIG Show, be sure not to miss the Sunday session, “The Store of the Future: Radical Startups Transforming Bricks-and-Mortar Retail,” moderated by Hoffman.

Bringing order to the off-price segment

Mission: Enable brands to sell excess inventory to retailers in private, online showrooms.

 

Entrepreneur Ronen Lazar marvels at the strides retail companies have made in enhancing their customer-facing operations. Brands and retailers have focused time, energy and financial resources “on areas that everyone can see,” Lazar says.

In the same breath, however, the CEO and co-founder of INTURN might ask them about the inventory systems and processes that operate in relative obscurity. Are they meeting challenges, such as managing inventory across channels in real time, leveraging up-to-date data and analytics or making business decisions based on accurate reporting?

INTURN was founded with the express purpose of enabling brands to sell excess inventory efficiently to retailers in private, online showrooms as a means for turning inventory faster, improving cash flow and optimizing returns. Lazar says the reception for INTURN’s platform has been positive because companies realize that front-end innovations to engage consumers are only one part of a technology-fueled retail revolution.

“What we’ve seen recently is that brands and retailers are starting to put a little more focus behind the scenes in their back offices,” he says. “What retailers are seeing is that it is time to get with the times.”

Lazar says off-price retail has not seen much innovation in 25 years, with many operations still performing inventory manually or via rudimentary spreadsheets, yet it is one of the industry’s hottest-performing segments. He considers the sale of off-price inventory a last frontier along the retail technology continuum.

“There is a lot of subjective decision making without adequate visibility and oversight,” he says. “The net result is that a lot of money is being left on the table by those supplying goods to the market.”

A July 2016 survey from The NPD Group found that consumers who purchase at off-price retail represent 75 percent of apparel purchases across all retail channels. INTURN collaborates with brands and retailers in verticals like apparel and footwear to ensure its process encompasses all their “diverse pain points and needs.”

Apparel and footwear are characterized by complexity, Lazar says, noting the multitude of styles, sizes, colors, lengths and widths. INTURN has honed in on the vertical’s urgency to turn around product quickly amid rapid price declines. The overselling of inventory, for instance, is one visible indicator of an inefficient inventory process: Lazar estimates the unsold apparel inventory market to be greater than $250 billion annually.

“The technology that needed to be built out for this isn’t something that just fits in a box,” he says. “It isn’t one-size-fits-all. It’s a lot more complex.” Lazar declines to identify brands the company works with, but representatives associated with Gilt Groupe, Burlington Coat Factory, Polo Ralph Lauren and Ross Stores are noted in an advisor section of the company’s website.

Not requiring complicated systems integration is a strong selling point of the INTURN platform; data is exported to clients in formats both the seller and buyer can digest, Lazar says. INTURN is seeking to expand into international markets this year, and “We also believe there is an opportunity to launch new verticals outside of apparel and footwear for companies looking for product or sitting with inventory that needs to be cleared,” Lazar says. — M.V. Greene

Digital ‘pre-visit’ syncs online and stores

Mission: Drive store traffic using advanced location data, customizable content and appointment, event and promotion management.

 

David Munczinski, founder and CEO of Brickwork software, has much respect for Silicon Valley and other software firms that excel at advancing innovative technologies to address retail market solutions. Brickwork can be classified as one of those firms — only Munczinski believes it has an intrinsic edge: He and his team are retailers and brand marketers.

Consequently, “We were more acutely aware of the realities of the market, of how retailers and brands evaluate technology, buy technology and implement technology,” he says. “We use that awareness today as a differentiator as a business, and we use that awareness to go about it differently than many software companies go about entering this market.”

During his time with Polo Ralph Lauren, Levi Strauss & Co. and Indaba Music, Munczinski observed that companies were doing a great job of investing in software to propel their growing e-commerce businesses, but there was a fundamental shift in shopper behavior as related to bricks-and-mortar businesses that they did not seem to notice.

“What we were finding was that upwards of 80 percent of customers who were buying in stores were beginning their customer journey online, and increasingly on mobile.” Munczinski’s goal for Brickwork is to advance a software platform that uses digital technology, including advanced store locators and location pages, customizable content and appointment, event and promotion management, to drive in-store traffic via a digital “pre-visit.”

He’s clearly on to something: Deloitte has reported that digital interactions are heavy influencers of store purchasing behavior. In a 2015 global survey, “Navigating the New Digital Divide,” Deloitte surmised that digital interactions were influencing 64 cents of every dollar spent in retail stores — a total of $2.2 trillion.

More and more retail organizations are creating shared incentives for e-commerce and store teams based on total sales, and inventory management between channels is improving, Munczinski says. The gap remains most pronounced in the area of customer experience: Online purchasers might not be able to return unwanted products to stores, for instance, and few retailers have a “virtual dressing room” in which shoppers can place items that will then be waiting for them to try on when they arrive at the store.

Last October, Brickwork received $5 million in Series A venture capital financing to focus on expanding its sales and marketing efforts and strengthening its technology backbone with enhanced analytical capabilities. “Technical mountaineering” is how Munczinski describes the future he sees for Brickwork.

“You’re always under-resourced as a small company and you have to adapt to changing conditions. It’s very similar to what climbing a mountain is like,” he says. “You’re halfway up the mountain. You’re there with the people you have around you. It’s very clear that you have a very big, ambitious mission, which is to getting to the top and getting back down again.” — M.G.

Message in the emotion

Mission: Offer a cognitive content platform that crafts marketing messages designed to boost sales by appealing to key human emotions.

 

At the dawn of the mobile marketing age — around 2000 — Alex Vratskides was working with mobile network operators to push offers to subscribers in the form of millions of text messages each month. Vratskides noticed that one message might get a 2 percent response rate, while another with similar but slightly different phrasing might get a 10 percent response. He also sensed that too much of message development was being left to chance.

“It was astounding to me that there was no complete method to actually ensure that every offer would get its full marketing potential,” says Vratskides, who was then working for Upstream, a London-based mobile commerce platform he co-founded.

What Vratskides and his team at Upstream learned was that changing even a single word significantly affected consumer response rates. “Everything was down to how you phrased it,” he says. “A text message is words in its purest form. No color. No sound. Nothing else. Just words. So the choice of words meant all the difference.” Vratskides and Upstream, where he served as CEO from 2004-2012, began experimenting with mathematical equations to generate what he calls “message permutations” for driving the best response.

Persado, spun off from Upstream in December 2012, offers a cognitive content platform to retail and digital marketers and other industry segments that presents wording in messages based on key human emotions — achievement, excitement, safety, gratitude, exclusivity — that appeal to consumers. Persado algorithms are generated through machine learning and artificial intelligence technologies via a database of more than 1 million curated motivational words based on 15 primary emotions.

Persado markets this approach of tapping into advanced linguistic data and cognitive technologies as mindshare to assist marketers in creating engaging content for digital channels. Consumers can be blind to the abundance of digital ads targeted to them, and Persado’s platform is designed to rise above that market chatter and deliver content optimized to get consumers to act.

Persado has deployed cognitive content for display ads and email, mobile and Facebook campaigns. Some 100 global brands and retailers, including American Express, Citi, Verizon, Microsoft, Neiman Marcus, Lucky Brands and Expedia, are engaged with the platform. Some campaigns have seen response rates of 70 percent or more, and the company claims some $1 billion in incremental revenues generated for its clients.

“The marketers will bombard you with offers until you bite, but the consumer is not a passive actor in this,” Vratskides says. “They experience the marketing, and all they care about is whether it is relevant to me and does it makes sense.” In August 2016, Inc. Magazine ranked Persado No. 16 in its annual ranking of the 500 fastest-growing private companies — joining better-known brands like Zillow, Pandora, Yelp, Timberland and LinkedIn. The company reports three-year sales growth of nearly 9,400 percent.

Vratskides, who holds Ivy League degrees in applied mathematics and operations research, acknowledges surviving many risks inherent with entrepreneurship.

“All of this innovation is fine, but you need to actually have persistence in watching objectively what works and what doesn’t and make very fast corrections,” he says. “It could have gone easily the other way for me. The biggest thing is luck. That’s super, super important. With luck, you survive.”

Speak and ye shall find

Mission: Provide artificial intelligence-based conversational commerce.

 

 

Imagine a shopper visiting the Best Buy website and instead of typing in a generic search query, being able to say, “I’m looking for a quiet dishwasher that’s on sale and has free shipping.” There’s no need to imagine. Natural language search is a reality, and once shoppers become accustomed to asking for what they want — and getting precise results — there will be no turning back.

AddStructure, founded by Will Underwood and Jarrod Wolf, is an end-to-end search solution for retailers that enhances the user experience by improving search and making product more discoverable. The technology is an offshoot of a graduate research project on semantic search and analysis that initially focused on gaining a better understanding of online restaurant reviews posted on Urbanspoon. Shortly after, Underwood and Wolf began working with Best Buy executives who were seeking to gain a better grasp on how shoppers talked about products in reviews. They quickly determined that the technology they were developing could be applied to solving numerous retail problems.

AddStructure tackles three components of search: external, which helps consumers find a website; internal, which aids in locating products on a retailer’s site; and personalization, which provides the most relevant content.

“At the core of this technology is an engine that understands natural language,” Wolf says. “The system reads through all of the structured and unstructured content and tags every piece of content with information. Once we add structure to the content, a retailer can leverage it in a variety of ways.”

Wolf provides an example of how AddStructure works for Best Buy. “If someone launched a Google search for ‘sturdy camera’ a few months back, they would not have landed on Best Buy,” he says. Now “the system repurposes and restructures all the content into a landing page that’s highly relevant. User-generated content related to the search query — along with descriptive words that are associated with ‘sturdy’ — are now displayed. It leverages natural language to capture larger amounts of organic search.”

Best Buy shoppers overwhelmed by the volume of reviews for even a single item can use the system to summarize content contained in user reviews. For every item with more than 10 reviews, AddStructure creates a list of pros and cons, allowing shoppers to read the reviews that align with the product attributes that are most or least important to them. (Best Buy executives have found that being upfront about the “cons” has proven valuable in building shopper trust and reducing returns.)

Underwood believes that natural language search implemented via voice command will ultimately upend today’s search. “We want shoppers to be able to go to an app or a website and say what they’re looking for. Our technology understands their priorities and delivers the best possible results — making it quick and frictionless to transact,” he says.

Underwood concedes that Amazon has a significant head start in the area of natural-language commerce, “so we’re trying to level the playing field. If a retailer wants their shoppers to be able to transact using voice … AddStructure can get them in that ballgame.” Deploying the technology is not an enormous undertaking, Underwood says. The company provides everything as data via an application programming interface that the retailer can pull into its existing search engine. “It delivers natural language capabilities without having to change back-end infrastructure.”

The real value of natural language search is the revenue lift. Underwood and Wolf calculate incremental revenue based on the difference in click-through rates before and after implementation. “It’s a more natural behavior and it’s more convenient,” Wolf says. “Once consumers experience it, they’ll feel more comfortable tapping on the microphone instead of typing in a box.”

The data-driven stylist

Mission: Deliver carefully chosen outfits to customers’ doorsteps by marrying data-collecting algorithms with the human touch of trained stylists.

 

Monica Phromsavanh refuses to be boxed in by long-established norms. The founder and CEO of ModaBox has a different perspective on how women want to shop and an unconventional outlook on blending technology with the need for a human connection. “Women buy so many articles of clothing, yet most say they don’t have anything to wear because they don’t know how to build outfits,” says Phromsavanh, who emigrated to the United States as a teen from a refugee camp in Argentina.

“When I was operating a store, there were women who would spend hours shopping with us because we helped them to create outfits. It started me thinking — what if we could identify preferences, understand needs, budgets and favorite brands, and then match shoppers with expert stylists to deliver personalized service to them, at home, by utilizing technology? That’s why ModaBox was born.”

ModaBox — from a Spanish word for fashion — debuted in September 2014. It delivers carefully chosen outfits direct to customers’ doorsteps by marrying data-collecting algorithms with the human touch of trained stylists. Phromsavanh relies on chief technology officer Daniel Chvatik to perform the heavy lifting on the tech side of the business, describing their alliance as the perfect combination of her understanding what the customer wants and his expertise in building a system to achieve that objective.

ModaBox is not the first company to tap into the need for convenience and a curated approach to dressing women, and Phromsavanh is quick to note what sets her company apart. “It’s not a subscription service,” she says. “You’re not obliged to receive a box every month.”

Styling services and shipping are completely free; Phromsavanh considers them part of a dynamic purchase proposition. The onboarding process includes a request to share social media and Pinterest boards, which help provide greater insight into style and personal preference. With every delivery, she hopes to increase conversions, cultivate new brand awareness and reshape shopping habits.

Having cut her teeth in retail, Phromsavanh is “selective” about choosing brands and committed to emerging labels that shoppers won’t find in traditional outlets. She considers the ModaBox customer to be more aspirational and fashion forward. In addition, she stresses that it’s up to the customer to determine how often they want to freshen up their wardrobe; if there is a specific outfit needed for an upcoming vacation, a conference or a reunion, the stylists are ready to respond by email or text.

A key differentiator for ModaBox is that its customers “love having a stylist they can interact with,” Phromsavanh says. “We’re using technology and machine learning to filter down preferences and choices because we want to scale the business, but customers still want a human element. It took us a while to understand how important the human touch is but we realized that every time we added a human element into communication, customers were more enthusiastic.”

The retail experience is changing, says Donnetta Campbell, founder of TheSocialArchitects.com. “Customers don’t just appreciate a good product — they expect great service that is seamless, convenient and personalized. At ModaBox, Monica leverages today's innovation in technology to maintain and grow personalize customer experience. It is this focus on each customer that sets a tone for a breakout year."

The goal for the coming year is to continue learning from customers. “We will keep refining our processes on the back end with the goal of maintaining the lifetime value of the customer,” Phromsavanh says. “It really comes down to giving everything we’ve got to our users.”

Phromsavanh, whose personal story is one of unwavering determination despite relentless struggles, gives back to others. ModaBox has partnered with Bottomless Closet, a nonprofit organization that provides professional apparel for unemployed women. Each ModaBox includes a note encouraging the customer to donate and return gently worn pieces in the included prepaid envelopes.

This article was published in the January 2017 issue of STORES Magazine.