FITMATCH is a B2B platform that employs patented LiDAR scanning technology and body shape algorithms to provide precise garment size recommendations tailored to individual body dimensions. This technology mitigates the issue of poor fit in online shopping, leading to increased customer satisfaction and lower return rates for apparel brands.
Funding
$26.3M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Online apparel shopping suffers from high return rates due to inaccurate sizing, as traditional size charts fail to account for individual body shapes and dimensions. This leads to customer frustration and increased costs for retailers.
Solution
FITMATCH offers a B2B solution that leverages LiDAR scanning technology and body shape algorithms to provide personalized garment size recommendations. The platform captures precise body measurements, creating a 3D model that is then used to match shoppers with the best-fitting clothes. This technology can be integrated into both online and in-store shopping experiences, reducing the need for returns and increasing customer satisfaction. The system also supports applications in healthcare and sports science, providing detailed body shape analysis for performance and recovery insights.
Target Audience
The primary target audience includes apparel retailers looking to reduce return rates and improve customer satisfaction, as well as healthcare and sports science professionals seeking advanced body shape analysis tools.
Features
- LiDAR-based 3D body scanning for accurate and private data capture
- Patented shape-matching algorithms for personalized garment recommendations
- eCommerce integration via API for seamless online shopping experiences
- In-store integration with Intel RealSense LiDAR technology
- iOS-based solution for mobile scanning and shopping
- Digital twin creation for visualizing body metrics and recommended styles
- GDPR compliance and robust data security measures