Vatorx2
Genostyle
Location: New York, New York, United States United States
Founded in: 2014
Stage: Napkin (idea)
Number of employees: 6-15
Short URL: vator.co/genostyle
Awards and mentions
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The New York Fashion Tech Lab was cofounded by the Partnership Fund for New York City and Springboard Enterprises promoting Fashion Technology Innovation. The program connects a select cohort of Women-led Early & Growth stage fashion-focused technology companies with New York’s leading fashion retailers and brands fostering iteration, validation, and acceleration of technologies to advance the industry.
Vatorx1

Genostyle

Sequencing Fashion Style Genotypes
Startup/business
New York, New York, United States United States
http://www.genostyle.com

We provide solutions that break style down into quantifiable data and use that data to build a “style genome” of a person or brand. That genome then powers the relationship between retailer and consumer, creating a common, quantifiable language of style that guides the consumer towards products they love and retailers towards selling those products

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Company description

Innovative fashion algorithms that sequence style genotypes (fashion genome) to know your customers style and make it your competitive advantage. 

We provide solutions that break style down into quantifiable data, and utilize that data to build a “style genome” of a person or a brand. That genome then powers the relationship between the retailer and the consumer, creating a common, quantifiable language of style that guides the consumer towards the products they love, and the designers and retailers towards selling those products.

 

 

 


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Team
  • Ricardo Cuervo
    Ricardo Cuervo | Founder
    Founder Genostyle Founder Best Fashion Friend - fashion social networking platform (2011-2014) Owner, MD Manacor Group - Boutique management consulting specialized in tech and ops Consultant at McKinsey & Mitchell Madison Gr. MBA, M.Sc. Engineering
  • Veronica Cabezas
    Veronica Cabezas | Founder
    Veronica is the co-founder of Genostyle,a fashion tech start up that aims to solve the gap between fashion brands and consumers by deploying algorithm-driven solutions to optimize e-commerce and impact other verticals for B2B clients to increased ROI
  • Himanshu Panwar
    Himanshu Panwar | Founder
    I am an engineer from IIT Bombay with 6+ years of experience in data analytics and product development. I've led analytics engagements across top banks and retail companies in the US and India and have built several data products for retailers.
  • Alfredo Garcia
    Alfredo Garcia | Founder
    Alfredo Garcia is Professor of Industrial and Systems Engineering at the University of Florida. His research interests include dynamic optimization and games with applications in electricity and communication networks and industrial organization.
Business model

Genostyle is a B2B2C. Our clients are retailers and designers that need to know their customers’ style preferences in order to sell them and design for them products they really need and / or want.

We envision a pay-per-click, “powered-by-Genostyle” business model. Clients that make use of Gensotyle algorithms for their digital marketing and ecommerce efforts pay a fee per click on products (hyperlinks) that are filtered and prioritized using Genostyle algorithms. We are working on development of APIs that fully integrate with clients’ digital marketing and ecommerce platforms.

We also envision developing a vertical catering to digital marketing and advertising agencies, whom can incorporate deep style-driven analyses into their portfolio of services enhancing value added from marketing and advertising to their multi-brand retailer clients.

Lastly, in the medium term, we envision development of B2C solutions, catering directly to consumers (buyers, fashion bloggers, independent stylists), putting them in control of their own ‘fashion DNA’

 

Competitive advantage

Our competitive advantages are the power of our algorithms and innovative approach to solving the challenge of matching fashion based on style, a very subjective issue.

Fashion is in early adoption of big-data. Style matching engines are a white space opportunity in fashion ecommerce and digital marketing. Current recommender engines (e.g. Amazon) are relatively simple logistics regressions, which fail to predict what customers will like and buy. Brands/retailers need to anticipate and know customers’ style preferences in a cost-efficient scalable manner. Professional stylists are not a scalable business.

As we develop technology solutions that leverage our algorithms and seamlessly integrate with retailers’ digital platforms, we will continue to raise the bar.