Funds will be used for launching a mobile app and for team expansion. The portal curates designs basis interest graphs of audience
BestMediaInfo Bureau | Delhi | May 20, 2015
Red Polka, a curation-led podium which showcases brands, designers, their trendsetting products, and the unique stories behind them, has closed its first round of angel funding from a clutch of investors. Mumbai-based Red Polka curates fashion and lifestyle designs catering to women aged 23+.
The funds raised will be used to launch Red Polka mobile app and for team expansion. The app is expected to hit leading app stores in 2-3 months.
Vishakha Singh, Founder and CEO, Red Polka, commented, âRed Polka caters to discerning shoppers with a need to discover good designs. The shopper tends to explore more and gets delighted with handpicked designs that are recommended apropos her taste. Red Polka curates designs in categories like clothing, fashion accessories, home dĂ©cor and kidsâ products (up to the age of 8) and recommends them to shoppers. The curation is based on the interest graphs of the audience and is packaged with stories and tips.â
She further said, âMore than 30 per cent of our audience are repeat visitors and we have created that kind of pull due to our weekly themes which our users find relevant. For sellers, we provide them with a platform that helps them stay on shoppersâ top of mind. And these sellers are not just e-commerce players, but many small home-preneurs too.â
Red Polka operates in the e-commerce enabling space, which is a relatively new segment in India. However, their USP is curation. They not only discover and showcase designs in fashion, but also curate products keeping in mind their audience profile.
The company is also focusing on attracting the right talent to build a strong team. While Red Polka has an in-house team of curators, designers, content writers and relationship managers, the company has hired Parnil Mhatre as Chief Technology Officer. He comes in with a background in Artificial Intelligence and setting up predictive analytics and recommendation systems.