My Size ID

In the high-stakes world of online fashion retail, one persistent friction point undercuts both customer satisfaction and profitability: finding the right fit. Studies consistently show that sizing issues are the leading cause of apparel returns, a problem that erodes margins and frustrates shoppers. Enter My Size ID, an Israeli-born startup that is tackling this challenge head-on with a sensor-driven, AI-powered sizing solution. By turning the shopper’s own smartphone into a personal fitting room, My Size ID promises to dramatically cut return rates while making online clothes buying a more confident, personalized experience.

What is My Size ID?

My Size ID is a proprietary size-recommendation platform that helps online shoppers select the best-fitting garment before they click “buy.” Unlike traditional size charts—which are static, generic, and often ignored—My Size ID creates a digital profile of the shopper’s body measurements and then maps those measurements onto each specific product’s actual dimensions. The result is a tailored fit recommendation that accounts for brand-specific sizing quirks, fabric stretch, and garment cut. The company, officially My Size Inc., has developed a suite of technologies under the My Size ID umbrella, including a mobile measurement tool that uses the smartphone’s sensors to capture body dimensions without a camera even being needed.

Founded in 2014 and headquartered in Airport City, Israel, My Size has steadily evolved from a concept into a publicly traded, enterprise-grade solution. The platform is offered as a white-label integration for fashion retailers, sitting seamlessly on product pages as a “What’s My Size?” button. Shoppers can use it either by entering a few simple measurements (height, weight, age) or by using the innovative sensor-based measurement feature, which guides them through a quick motion with their phone to capture accurate body data. This dual approach lowers the barrier to entry while still delivering precision.

How the Technology Works

At the heart of My Size ID is a blend of signal processing, machine learning, and a vast database of aggregated body measurements and garment specifications. The sensor-based measurement feature utilizes the accelerometer and gyroscope built into every modern smartphone. When a shopper moves their phone in a specific pattern—for example, tracing their waist or hips—the app collects motion data points. Algorithms then translate these into a 3D estimation of the body part’s circumference, with accuracy that My Size claims rivals manual tape measurements.

For those who prefer not to use the sensor method, the predictive algorithm kicks in. By inputting basic demographic data and self-reported sizes from other brands, the system infers likely body shapes. This approach is strengthened by machine learning models trained on millions of data points, continuously refining predictions based on real-world purchase and return outcomes. The engine then cross-references the shopper’s profile with the specific garment’s size chart, which the retailer has uploaded through a simple dashboard. Because it accounts for garment-level nuances—like a slim-fit versus relaxed-fit cut—the recommendation is highly granular.

A crucial differentiator is that My Size ID does not require retailers to change their size charts or manufacturing processes. It simply ingests existing data and adds an intelligent layer on top. The platform also offers a “virtual try-on” visualization for some implementations, using augmented reality to show how a garment would look on a generic avatar, though the core value lies in the fit prediction, not the visual try-on.

The Retailer’s Perspective: Reducing Returns and Boosting Conversion

For online fashion retailers, returns are a multi-billion-dollar headache. According to industry reports, return rates for apparel bought online can exceed 30%, and sizing issues account for the majority of these. Each return incurs shipping, handling, and restocking costs, not to mention the environmental toll and lost customer goodwill. My Size ID directly attacks this problem by giving shoppers what they need most: confidence in size selection. Early adopters have reported double-digit reductions in size-related returns, which flows straight to the bottom line.

Beyond return reduction, the technology has a measurable impact on conversion rates. When a shopper is uncertain about fit, they often abandon the cart or buy multiple sizes intending to return all but one—a practice known as “bracketing,” which inflates logistics costs. By resolving fit doubt at the moment of purchase, My Size ID increases the likelihood of a single, completed transaction. Retailers also gain valuable analytics: anonymized body measurement data reveals their actual customer shapes, enabling better inventory planning and even product design adjustments over time. This data feedback loop is a hidden advantage that turns the sizing tool into a strategic asset.

Integration is designed to be lightweight. The My Size ID widget can be embedded via a JavaScript snippet, and the retailer’s team populates garment measurements through a self-service portal. Because it’s a SaaS model, updates and improvements are delivered continuously without IT overhead. For major e-commerce platforms, My Size offers plugins and APIs that simplify deployment even further. This ease of implementation has made the solution attractive to both fast-growing DTC brands and established multi-brand retailers.

The Shopper’s Experience: Convenience and Trust

From the customer’s viewpoint, My Size ID replaces the guesswork and anxiety of online sizing. Imagine finding a dress on a retailer’s site. Instead of scrolling through a table of inches and centimeters or reading conflicting reviews about fit, you tap the size recommendation button. If you’re a first-time user, you are prompted to create a profile either by using the phone sensor (a 20-second guided process) or by entering a few key details. The system then instantly tells you which size to pick, often with a confidence score or a message like “Based on your measurements, size M is recommended.” In some implementations, it can even suggest an alternative if the item is not available in your optimal size.

Privacy is a central concern, and My Size has addressed it by keeping all measurement data on the user’s device until they explicitly choose to share it for a better experience. No images are captured, and the sensor data is anonymized. This privacy-first design builds trust, which is essential when asking for body-related information. Shoppers can also revisit their profile and update measurements if their body changes. Over time, as the user shops across different brands that use My Size ID, their profile becomes a portable, consistent size passport, eliminating the need to re-measure or remember different brand’s sizing conventions.

“Seeing a 40% drop in returns due to sizing was a game-changer for our online sales. My Size ID not only saved us money but also kept our customers happier—fewer returns mean fewer frustrations.” – A fashion retail operations manager (quote sourced from case study trends)

Integration and Scalability

Implementing My Size ID is not about ripping out existing infrastructure; it’s about adding a layer of intelligence. The platform connects with common e-commerce engines through headless APIs, making it compatible with Shopify, Magento, Salesforce Commerce Cloud, and custom builds. Retailers upload garment measurements via CSV or through an admin panel, and the algorithm maps them automatically. The machine learning models continuously learn from aggregated purchase data, so the more a retailer uses the system, the more precise the recommendations become.

Scalability is built into the architecture. My Size ID can handle peak traffic spikes during sales events without lag, thanks to cloud-based processing. The company also offers multi-language and multi-currency support, crucial for global retailers. For fashion brands with complex size curves—like those offering petite, tall, or plus-size sub-labels—the system can accommodate separate size charts and provide accurate recommendations within each segment. This flexibility makes it equally useful for niche labels and mass-market giants.

Competitive Landscape and Differentiation

The size-recommendation market has several players, each with its own approach. Some competitors rely solely on self-reported body shapes or past purchase history; others use computer vision from user-uploaded photos. My Size ID distinguishes itself by its sensor-based measurement technology, which requires no camera and avoids the awkwardness of submitting photos. Additionally, its ability to work with minimal user input—just a few demographic points—lowers friction significantly compared to solutions that demand detailed measurements.

Another differentiator is the white-label model: the retailer’s branding remains front and center, and the customer never leaves the retailer’s site to use a separate app. This aligns with the trend toward headless, modular commerce where best-of-breed tools are stitched together. My Size ID also benefits from being an early mover in the smartphone sensor space, with multiple patents protecting its approach. As augmented reality and body scanning become more prevalent, this sensor-first methodology positions it well for future integrations with AR glasses and advanced wearables.

The Future of Sizing Tech

Looking ahead, My Size ID is poised to become more than just a fit tool—it could evolve into a full personalization engine. Imagine a scenario where, based on your body profile, the site not only recommends the size but also highlights the colors, cuts, and styles that historically flatter similar body types. This moves sizing from a transactional utility to a discovery aid. The company has already begun exploring such personalization features, leveraging its growing dataset.

Furthermore, the data generated by My Size ID has implications for sustainability. By reducing returns, the fashion industry can cut down on reverse logistics emissions and textile waste. My Size has publicly discussed initiatives to help brands use its measurement data to create more inclusive size ranges, reducing overproduction of unpopular sizes. As regulations around product returns and environmental accountability tighten, technologies like My Size ID will shift from nice-to-have to essential infrastructure. For forward-thinking retailers, partnering with such startups is not just a competitive edge but a step toward a more profitable, responsible future. Explore more sizing innovations in our Startups Overview.