How AI Size Recommendation Works: From Customer Information to the Right Clothing Size
Choosing a clothing size online can sometimes leave shoppers uncertain about which option to select. A size chart provides useful information, but the customer still needs to interpret it and decide whether S, M, L, or another size is right for them.
AI size recommendation offers a more personalized way to support that decision. It can use information about the shopper together with a brand’s sizing standards to recommend a suitable clothing size.
Mirrorsize addresses this through MS QuickSize, an AI-powered sizing solution that uses a short customer profile to provide an instant clothing size recommendation. The experience is designed to be simple for shoppers while giving apparel businesses a way to bring personalized sizing into their digital shopping journey.
What Is AI Size Recommendation?
AI size recommendation provides sizing guidance based on customer information and the brand's sizing standards.
Rather than asking every shopper to interpret sizing information on their own, the technology uses the information they provide to create a more personalized recommendation.
With MS QuickSize, this starts with six quick questions. The customer provides basic information about their profile, and the solution uses those responses as part of the sizing process.
The goal is straightforward: help the shopper move from uncertainty about clothing sizes to a recommendation that reflects both their profile and the brand’s sizing.
How Does AI Size Recommendation Work?
The process behind MS QuickSize can be understood in three stages.
1. Collect Customer Information
The sizing journey begins with six simple questions.
The information used by MS QuickSize includes the shopper’s age, height, weight, gender, and body shape. This provides the customer profile needed for the recommendation.
The shopper does not need to take individual body measurements manually before starting.
2. Evaluate the Customer Profile
Once the questions are complete, the information is processed to determine the appropriate fit.
Mirrorsize describes MS QuickSize as a BMI-based sizing solution powered by patented technology. In this application, the customer profile is used specifically for clothing size recommendation.
The entire process is designed to take less than 10 seconds, keeping the sizing interaction short and convenient for the shopper.
3. Connect the Profile With the Brand’s Sizing
A personalized recommendation also needs to reflect the sizes offered by the business.
MS QuickSize matches customer profiles with brand size charts to provide personalized recommendations. Businesses can upload and manage their own size charts, allowing the sizing experience to reflect their specific sizing standards.
This connects two important pieces of information: the shopper’s profile and the brand’s sizing.
Can You Get a Size Recommendation Without Body Measurements?
A personalized clothing size recommendation does not always require the customer to physically measure their body.
This is an important part of the MS QuickSize experience.
Customers do not need to take photos or complete a body scan. A camera is not required, and there is no need for additional scanning hardware or devices.
Instead, the sizing experience is based on the information customers provide through the questionnaire. It works through a standard web browser or mobile application.
For online shoppers, this removes the need to complete a separate photo, scanning, or manual measurement process before receiving sizing guidance.
Why Brand-Specific Sizing Matters
A recommendation is more useful when it corresponds with the sizing standards of the products being considered.
Businesses using MS QuickSize can upload and manage their own size charts. They can also use multiple size charts to support different products and apparel categories.
This allows the sizing experience to remain connected to the brand’s actual product offering.
For example, the relevant sizing information for a shirt may be different from what a business uses for jeans, a jacket, or a uniform. Having the appropriate size charts available allows the recommendation process to work across those different categories.
Where Can AI Size Recommendation Be Used?
MS QuickSize supports a range of apparel, including:
- T-shirts
- Shirts
- Trousers
- Jeans
- Jackets
- Uniforms
- Sportswear
- Dresses
This makes personalized size recommendation relevant across different types of garment businesses.
Mirrorsize identifies apparel brands, online fashion retailers, uniform suppliers, and sportswear companies among the businesses that can use MS QuickSize.
The same core idea applies across these use cases: provide customers with sizing guidance before they make their final selection.
What Changes for the Online Shopper?
A standard size chart gives shoppers sizing information. Personalized size recommendation adds another layer by helping them use that information in the context of their own profile.
The shopper is still making the purchase decision. However, instead of relying entirely on their own interpretation of a size chart, they receive personalized sizing guidance.
Mirrorsize positions MS QuickSize as a way to reduce size uncertainty and support greater purchase confidence. The product page also identifies lower cart abandonment, fewer returns, and improved conversion rates among the intended benefits of providing the right size recommendation before checkout.
This makes sizing part of the overall customer experience rather than simply a chart shoppers need to interpret.
Bringing Personalized Sizing Into the Digital Shopping Journey
For apparel businesses, personalized sizing needs to work within the platforms their customers already use.
MS QuickSize provides APIs and SDKs for integration with web applications, Android, and iOS. It can also be integrated with Shopify and other eCommerce platforms.
This allows businesses to incorporate size recommendation directly into their digital shopping environment.
Customers can access the sizing experience, provide the required information, receive their recommendation, and continue shopping within the digital journey.
Mirrorsize also provides technical integration support for businesses implementing the solution.
A Simpler Route From Customer Information to Clothing Size
AI size recommendation can make online sizing more personalized without making the customer journey more complicated.
MS QuickSize demonstrates this through a short, profile-based approach. The shopper provides basic information through six questions, while the technology evaluates that profile alongside the brand’s sizing standards to provide an instant recommendation.
What makes the approach different is the simplicity of the customer experience. It does not depend on body photos, body scanning, manual body measurements, or additional scanning hardware.
For Mirrorsize, MS QuickSize provides a way to bring profile-based size recommendation into online apparel shopping. For apparel brands, online retailers, uniform suppliers, and sportswear companies, it offers a practical way to provide personalized sizing guidance at the point when customers need it most: while they decide which clothing size to choose.