New Delhi [India], Feb 13 (ANI): According to an industry report the overall Indian fashion e-retail market value is expected to touch $35 billion by 2020. Consequently, the Indian fashion industry is spawning numerous startups that are striving to capture more market share as people buying pattern and preferences has changed with time.
Today we have so many fashion brands available in the market and it's so difficult to choose one. Browsing each one of those websites is time consuming. It gives you an experience to look for various options and buy from the stores near you. It is not only more convenient for the shopper to have everything in one place but also, it increase sales for sellers. Here is the list of TOP 5 fashion platforms that makes the shopping experience more memorable one
Shopholix is an India's first fashion and lifestyle couponing platform focused on offline retail. Incepted in July 2015 in Mumbai, it solves the key problem of effective marketing for brick and mortar retailers. A location-based platform for web and mobile apps, helps shoppers discover personalized content with the best deals, exciting offers, information on new stores opening, exclusive privileges, latest trends and collections from preferred brands, and much more.
Through the Shopholix platform, shoppers have at their fingertips around 2000+ retail outlets of popular fashion and lifestyle brands which they can virtually window shop, discover discounts from and redeem mCoupons at. It makes the experience of shopping most memorable one.
LooksGud, India's fashion discovery platform is showcasing top fashion products from multiple brands and multiple online stores under single roof. Amidst various fashion discovery sites, the USP of LooksGud is its online fashion community and human touch.
Thousands of online fashion stores, it is tedious work to find the best product to match your style and fit in your budget. Even the same problem exists in many discovery sites which use automated algorithm to show all the products from all stores. LooksGud claims to solve this problem by showcasing products recommended by in-house experts and is most loved by its community in different price range within each category
Voonik is India's first stylist-handpicked fashion store for women, founded in 2013 by two former students of ISB, Hyderabad, Navaneetha Krishnan and Sujayath Ali. Voonik is a popular fashion e-shop that was designed with the objective of personalizing customers' shopping experience. The venture started out as a small team of two web developers and two stylists, but now has about 450 employees who have contributed to building a customer base of 10 million registered users and enabled 8 million app downloads.
Limeroad is similar to an online fashion scrapbook which allows you to create your own look by choosing from products showcased by over 1500 vendors and share it online. Founded by Suchi Mukherjee, Prashant Malik, and Ankush Mehra, the brand helps you discover other styles and buy/share them. The business model they follow benefits all those involved - the customer gets a chance to exhibit his/her creativity and wins reward points, and the vendors end up selling more than one product as a part of 'the look'.
Wishary is a product discovery platform which enables its users to discover fashion products they love but don't know where to find. It has an image discovery technology which automatically sends recommendations to users from around the web's ecommerce sites to help them curate a look or a buy a product they love.
Wishary's fashion editorial team from around the country gives style tips related to the products the user is looking for, making the startup as their one stop online fashion destination. For example, an individual comes across a pair of shoes which she likes.
All that she needs to do is click a picture of it and the startup will give the product recommendations from their ecommerce partner sites along with style tips as to how the user can wear it in a formal setting or on an occasion. Startup's intelligent algorithm keeps a track of its user's search behavior and likes so as to make the experience more personalized. (ANI)