Emotional intelligence in female apparal retail…
Purva Gupta (Co-Founder of Lily, a shopping app using emotional intelligence to connect women with clothing that makes them look and feel their best – bio) joins Pavan Bahl, Rob Sanchez, Ilan Tito and Marc Raco for an On Air Challenge (a recorded and comprehensive paid consultation on business development).
A personal journey to Lily, creating trust, and working with retailers
Purva reviews Lily’s emotional technology that maps to clothing online and in stores, touches on the genesis of the company from a very personal place and personal shopping experiences. She points to shopping experiences as unintelligent, then her path to joining an incubator and speaking to women about what they were thinking when shopping for 10,000 hours for insights, and working with psychologists to look at human behavior creating perceptions of their bodies. The customer journey with product, the importance of starting with customer’s head and “why”, focusing engines with phenomenal conversation rates, tackling scalability, working with retailers, and an affiliate network for testing, plus other strategies exploring other relationships with retailers and a potential white label solution. Controlling the conversation with customers, the ability to provide trust, considerations for user experience being seamless, and user having a perception of trust, the focus on what was purchased and browsed, and understanding products and getting clean inventory, purchase and browse data from brands. The value or purchase and return data, but the ability to not need it by using Lily’s own data from app activity where purchase was made. The value in working with retailer for better product discovery. How Lily is a good fit for a license play, the ability to send retailer high quality lifetime customers, how Lily can be an acquisition play for retailers, plus cognitive insights, marketing methods, and other incentives, and marketing Lily to an offline retail network.
Possible uses, styling vs. perception engines, and the “solve”
Numerous ways the app could be useful including online purchasing, personalized recommendation email marketing business, locating desired products inside the store, fitting room recommendations, data feedback to brands for who customers are, hyper-targeting with relevance, understanding woman’s psychology and predicting what products make her happy, and potential with chatbots. The advantages of working with the platform working directly with designers and brands, ways the styling engine vs. perception engine both help with understanding a user’s body from their perspective mixed with changing with changes at store level in fit. And looking at the “solve”, while trying to keep trust of user.
Cash flow and scaling, data and analytics, and multi-brand retailers
The team’s recommendations cover supporting internal cash flow and setting up for scale, looking at platforms to reach many retailers vs. one-on one-negotiation, and that the user side has to be technology other people use. Looking at key data points, focusing on key metrics, providing analytics to brands, selling emotional intelligence as a plug-in, luxury insights, using chatbots to increase exposure, connecting with analytics companies, drop-ship marketplaces and software, responsive retail opportunities, and multi-brand retailers.
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- Intel [Episode 160]
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