Personalized Virtual Styling Meets E-Commerce
QuikFit is a custom fashion and e-commerce application designed to help shoppers visualize clothing on a digital representation of themselves before making a purchase.
Users create a personalized virtual mannequin based on characteristics including height, weight, body size, skin tone, and other physical specifications. Clothing products sourced from Amazon can then be displayed and styled on the mannequin, giving shoppers a more personalized way to discover outfits and understand how different products may complement their individual appearance.
Once users find products they like, they can add items to their shopping experience and continue through to Amazon to complete the purchase.
- Client : QuikFit
- Industry : Fashion
How We Helped
- Developed the QuikFit mobile application
- Built personalized user-profile functionality
- Created customizable virtual mannequins
- Integrated Amazon product listings
- Developed personalized fashion discovery experiences
- Built product and outfit styling functionality
- Connected products to Amazon purchasing
- Implemented affiliate tracking and monetization
- Developed the QuikFit brand and digital experience
- Created supporting web and promotional assets
THE CHALLENGE
Online fashion shopping gives consumers access to virtually unlimited products, but discovering clothing that matches an individual’s body type, appearance, and personal style can still be difficult.
Traditional e-commerce product pages typically display clothing using standardized models and product photography. While useful for showcasing a product, those images do not necessarily help every shopper visualize how an outfit may look relative to their own physical characteristics.
QuikFit set out to create a more personalized shopping experience by combining digital styling, body customization, fashion discovery, and e-commerce into one platform.
THE SOLUTION
Harris Digital helped develop QuikFit as a personalized virtual styling application that connects individual user characteristics with a large catalog of fashion products.
Users begin by creating a digital mannequin designed around their personal specifications, including factors such as height, weight, sizing, skin tone, and body characteristics.
The platform can then surface fashion products from Amazon and allow users to style those products on their personalized mannequin. Instead of browsing isolated product listings, users can experiment with different items and combinations to create complete looks tailored to their preferences.
This transforms traditional product discovery into a more interactive styling experience.
Personalized Virtual Mannequins
At the center of QuikFit is a customizable mannequin system designed to give each user a more individualized representation.
User-provided measurements and physical characteristics are used to create a virtual model that can serve as the foundation for styling different clothing products.
Rather than presenting the same fashion model to every shopper, QuikFit gives users a personalized canvas for exploring their style.
Amazon Product Integration
QuikFit connects the styling experience with Amazon’s extensive e-commerce ecosystem.
Fashion products can be incorporated into the platform and presented within the QuikFit experience, allowing users to discover products while building outfits rather than searching through individual marketplace listings.
Once a shopper selects the products they want, they can continue to Amazon to complete their purchase.
Affiliate Commerce Model
QuikFit was also designed with a built-in monetization strategy.
Qualifying products connect to Amazon through affiliate tracking on the backend, enabling QuikFit to generate affiliate revenue from eligible purchases originating through the platform.
This creates an e-commerce model where the application can provide the discovery and styling experience without needing to operate its own inventory, fulfillment, or traditional retail infrastructure.