Why Am I Getting Different Sizing Recommendations From Different Brands?

If you have used virtual try-on or an AI size finder across different brands and received different size recommendations, you are not experiencing a bug. You are experiencing the actual reality of how the fashion industry sizes its products — and understanding that reality is the key to shopping more confidently online.

Size labels are brand language, not a universal standard

There is no global standard that defines exactly what a "medium" or a "size 12" means in fashion. Each brand creates its own size chart based on its target customer, its fit model, its manufacturing tolerances, and its positioning in the market.

A brand that targets petite frames might cut its medium smaller than a brand that targets athletic builds. A brand known for relaxed silhouettes might cut its medium with more ease than one known for tailored fits. Even within the same brand, different product lines — performance wear versus formal wear, for example — may use different grading systems.

The result is that a shopper who is genuinely a medium in one context might be a large in another and a small in a third. This is not inconsistency on the part of the size recommendation tool. It is the tool accurately translating your fixed body measurements against three different brand charts.

Your body measurements do not change. The charts do.

This is the important conceptual shift. Your chest measurement is your chest measurement. Your waist is your waist. When VTS extracts over 20 measurements from your body scan, those numbers do not change between sessions.

What changes is the product data the AI is comparing your measurements against. Brand A might specify that their large is cut with a 42-inch chest. Brand B might specify that their medium is cut with the same chest measurement. If your chest is 42 inches, the AI will correctly recommend a large from Brand A and a medium from Brand B. That is not a contradiction. It is accurate information about two different garment specifications.

Vanity sizing makes the problem worse

Vanity sizing — the practice of labelling garments with smaller numbers than older standards would have indicated — varies significantly across the market. Some brands, particularly in fast fashion and mass market clothing, use generous vanity sizing where their medium is cut large relative to what medium has historically meant. Premium and luxury brands sometimes do the opposite, using very precise fit standards that run smaller.

Shoppers who buy across multiple price points will regularly encounter this variation. Virtual try-on and AI size finders are doing the most useful thing possible in this context: ignoring the label and comparing your actual measurements to the actual garment data.

When recommendations seem inconsistent across sessions

If you have received a different recommendation from the same brand at different times, there are a few possible explanations. The most common is that the product data has been updated. Brands occasionally revise their size charts or update measurements on specific products, and the recommendation will reflect the current data.

Another possibility is a change in your own measurements. Weight fluctuations, fitness changes, and posture differences in photos can all affect the measurements extracted by the AI. If your scan photos were taken in significantly different clothing or lighting conditions, slight measurement variations can occur.

The most robust approach is to complete your body scan in well-fitted clothing with consistent lighting, and to treat your measurement profile as something to update every few months rather than once and never again.

How to use different recommendations practically

When a tool recommends a large from one brand and a medium from another, use the fit heatmap to understand why. The heatmap shows whether the large is recommended because the medium is tight across the chest, or across the shoulders, or through the hips. That information tells you whether the fit difference is in a measurement area that matters to you personally.

Some shoppers carry more width through the shoulders but have a narrower waist. Others have the opposite proportions. Two shoppers with the same chest measurement might receive different recommendations for the same garment because one needs more room through the upper back and the other does not. The AI recommendation is personalised to your specific measurement profile, not just your overall size.

The alternative is worse

Before AI size finders, the recommendation for navigating brand size differences was to consult a size chart and convert your measurements manually. That assumes you own a tape measure, know how to use it correctly, record the numbers accurately, and then read the size chart correctly in each brand's labelling system.

Most shoppers do not do this. They guess based on the last brand they bought from. They read reviews hoping someone with a similar build left a comment. They order two sizes and return the one that does not fit.

Getting different size labels across different brands is a feature of the AI recommendation working correctly. It is telling you the truth about each brand's specific cut rather than applying a generic answer that ignores the reality of how fashion is manufactured.