Finding clothes and shoes that fit well is a common frustration, especially for people with unique body proportions, disabilities, or busy schedules. Off-the-rack sizing often misses the mark, leading to wasted time, returns, and discomfort. While existing services like personal shoppers or subscription boxes focus on style, they rarely guarantee a perfect fit. This leaves an opportunity for a service that prioritizes precise measurements over trends.

How It Could Work

One way to address this gap is by creating a platform where users can hire a "body double"—someone with their exact measurements—to try on and purchase clothes for them. Users would input their detailed measurements (or complete a 3D body scan), and the platform would match them with a verified double nearby. The double would try on selected items, provide fit feedback (e.g., "tight in the waist"), and purchase approved pieces for delivery. Optional features could include styling advice or retailer partnerships for smoother returns.

Who Benefits and Why

This idea could serve several groups:

• People with hard-to-fit proportions, like those who are very tall, petite, or have atypical body shapes.
• Individuals with mobility challenges who find in-store shopping difficult.
• Busy professionals who need well-fitted clothes but lack time to shop.

For body doubles, this could be a flexible income source, while retailers might see fewer returns and more confident buyers. The platform could earn revenue through service fees, subscriptions, or partnerships with brands.

Getting Started and Scaling Up

A simple way to test the concept would be to launch a manual matching service in one city, focusing on high-need niches like wedding attire. Early adopters could be recruited through waitlists or gig platforms to gauge interest. If demand is strong, the next steps might include building an app with measurement-matching algorithms, expanding to new locations, and adding features like virtual try-ons. Challenges like ensuring accurate matches or recruiting enough doubles could be addressed through incentives, verification steps, and starting with common sizes before expanding.

Unlike existing services that prioritize style over fit, this idea could offer a more reliable way to shop by putting precise measurements first. Over time, the platform might even collect anonymized fit data to help brands improve their sizing standards.