Wary of buying clothes online? Fitrrati has a tech solution to help you find the best fit
How many times have you returned a t-shirt or a pair of shoes that you bought from an e-commerce site because the size was not right?
How many times did you drop the idea of a beautiful pair of ballerinas to your friend or a premium fabric shirt to your father because you were unsure of what size will fit them well?
How many times have you tried to make sense out of product size charts only to find them to be unhelpful, inconsistent and more confusing?
The Fitrrati team learnt that the 15-30% order return rate in e-commerce across fashion product categories is largely due to ‘size and fit-related issues’. This causes inconvenience to the consumer and a significant loss for the e-commerce venture in terms of profitability and the opportunity cost of selling the returned goods.
Fitrrati (under Ayata Tech Labs Pvt Ltd) is a cloud-based and data-driven personalized Fit Technology enterprise solution for fashion brands and e-tailers. It aims to address the consumer issue of knowing the exact size while shopping online for fashion products like apparel and footwear.
How does it work?
Fitrrati’s approach is data-driven and the application corrects itself while learning from the consumer. The technology crunches brand, consumer and retailer data to make best fit size recommendation for any style across brands, product categories and fit types taking into account individual fit preferences. An adaptive learning engine in the technology learns from consumer feedback and corrects itself for individual consumer to improve the accuracy of recommendation. The more the consumer shops using Fitrrati, the smarter Fitrrati gets in understanding individual fit preferences (both implicit - return of product, and explicit – direct feedback to Fitrrati) and accordingly improves the recommendations.
When a user goes to a fashion e-tailer such as Myntra, Snapdeal or Jabong, they’ll see an option to ‘Find Fit’ or ‘Check Size’. On clicking, it will ask a few one-time questions, related to your size & fit preferences. Users can either provide their body measurements or details of their favorite clothing in their wardrobe which fits them well. Once the user provides this input he/she will be able to see size recommendations for all the products in that category on the e-tailer’s portal. More the data and more accurate the data input, the more precise will be the recommendations and fit details. Fitrrati is also working with e-tailers to integrate the technology to show size recommendations based on user’s purchase history.
From idea to concept
Fitrrati’s Co-founder and CEO Amit Monga is not new to the e-commerce space. Earlier, he built a niche e-commerce portal for sports and fitness products, eSportsBuy.com, which was later acquired by Snapdeal.com. He has worked closely with Indian e-commerce companies to understand the pain points of online customers and e-tailers.
Fitrrati’s Co-founder and CTO Durai Balusamy has several years of experience in technical leadership working at top positions in companies such as Groupon, Yahoo and Sun Microsystems. While Durai was Head of Yahoo Shopping, he realized that sizing issues were affecting a consumer’s online retail experience.
Both Amit and Durai were introduced through a common friend and have been working on building this technology since April 2014.
The team delved into the root cause of the issue by speaking with designers, manufacturers and brand owners to better understand the sizing problem. They conducted consumer surveys to understand the thought process behind selecting one size over the other inside a fitting room. They even reached out to retailers and fashion brands to create a verified size related database. Currently, the database has 1000+ size related charts across product categories of top 200+ fashion clothing brands. Retailers using this technology can either use Fitrrati’s database or plug-in their own data. The technology works for both branded and non-branded products provided the data is available.Future plans include extending the platform to other fashion product categories – footwear, lingerie & accessories.
From concept to venture
In January 2015, Fitrrati launched its first version of product demo and received positive feedback from its potential clients which includes fashion brands and online retailers. Since then, Fitrrati is talking to and working with almost all major fashion e-tailers in India. Fitrrati not only helps retailers reduce their return logistics cost but also helps them increase conversion of active shoppers by turning browsers into buyers. Retailers can improve their customer loyalty by providing a personalized shopping experience where a user gets to see only the products which fit them well. It also helps firms plan and manage their inventories better. Fitrrati is scheduled to go live on one of India’s top 5 online fashion portals in the second week of April.
The five-member team comprises alumni from IIT Delhi, GEC Chennai, VIT Vellore etc. who have earlier worked in companies such as Yahoo, Groupon, Sun Microsystems, Price Waterhouse Coopers and Snapdeal.Ali Dasdan, Senior VP of Engineering at Turn.com, is an Advisor at Fitrrati. Ali has more than 16 years of research and development experience with both small and large teams in computational advertising, web search, vertical search, recommendation systems, e-commerce, and electronic design automation.
Fitrrati is currently bootstrapped but will soon start talking to strategic investors to raise funds for building their team and scaling operations. The scope of this technology is global (with US, UK, Europe & South East Asia being other big potential markets) but Fitrrati is currently focused to cater to the needs of Indian retailers. Future plans include enhancing the product features using machine learning algorithms and computer vision to better understand the body shapes and fit preferences of customers.
For more details on Fitrrati and to request a demo, interested people can reach out to [email protected]. Website: Fittrati
