Product recommendations are vital to brands and retailers. Now a new startup aims to change the way companies collect the key, underlying data: Lose the surveys and turn the consumer experience into a game.
Three-year-old Trendage, powered by $1.5 million in angel funding, officially came out of stealth mode to spotlight its game app, Style Challenge. The game went viral on Facebook Messenger, where it added 1.5 million new users in just two weeks.
The premise is simple — users put together outfits using apparel, accessories and footwear from hundreds of top brands, and the app’s growing community of fashion-minded members vote for their favorites. Players can also create individualized avatars from selfies and match body type, so the experience feels more personal. It also ties in with the company’s image-processing algorithms, which size the digital garments for different body types. For instance, a knee-length skirt would land at different spots on a statuesque person and a petite customer.
It’s easy to see how this model can yield a windfall of style and preference data — both in how the fashion gamers mix and match items and how the community responds to different combinations or themes.
Beyond the crowd-sourced expertise, Trendage brings artificial intelligence and visual search to the table, generating more than 10 million monthly style recommendations for stores. Those automatic product recommendations work as an up-selling tool for retailers, pointing out the apparel, accessories and footwear pairings for a given shopper’s age and area. The reports also cover predictive insights, tipping off partners on upcoming trends.
“Retailers are struggling to find ways to compete with online giants and fast-growing mail-based startups that have massive data,” said Vineet Chaudhary, chief executive officer. “The challenge of making sense of all the various data points gathered from web site views, email campaigns, sale and return data, however, is that the data is often not available until it’s too late to impact a shopper’s decision.”
For inspiration, the company looked at Netflix, Pandora and Spotify, all of which use algorithmic approaches to delve deep and “understand their user preferences,” he added. “That doesn’t exist in fashion today.”
Combining AI and the strength of a U.S. gaming community that’s 41 percent female, the company aims to zero in on what real women look like, wear and want to buy. And, thanks to machine learning algorithms, the system’s visual search powers and trend analysis are constantly evolving.
For instance, the software created 3 million outfits in January alone for its community members to vote on, and the company has identified as many as 216 common human body types. AI-driven results tend to increase in an exponential manner, which means the startup could have insights from many millions of data points in a matter of months.
“Brands often think they know who their core consumer base is, so they tend to tightly control how their products are styled and marketed. On the flip side, consumers like to stick with brands they are familiar with, and might not consider a brand that’s outside of their comfort zone,” said Roya Ansari, Trendage co-founder and business development lead. “Trendage has come up with an ingenious way for brands to put their apparel in front of a broader audience, one they may have never thought of reaching, to learn how consumers might mix and match their items with other brands. It’s also a great way for consumers to discover new brands that they would have never found otherwise.”
Trendage’s revenue model covers advertisements within the game itself, as well as the AI-driven recommendations. Retailers like Azalea have signed up, allowing the system to flow suggestions right into the e-commerce web site itself to “complete the look,” Chaudhary said.
Funding comes from investors in retail, technology and fashion, including Bhupen Shah, co-founder of Sling Media; Ilaria Galimberti, co-founder of Impressa Hong Kong and O’ahu Sport; and Nooshin Esmaili, founder of Sutro Footwear and ShoeBiz SF.