What True Fit does — and where the limits are
Statistical model
True Fit collects purchase and return data and uses correlations to recommend sizes. Quality depends on data volume and improves only slowly.
Crowd-based logic
Recommendations are based on what "similar" customers bought. But body proportions, fit preferences, and clothing behavior are highly individual.
Limited garment analysis
Generic size charts serve as the foundation — without considering cut, material, and elasticity of the individual garment.
What maketribe does differently
Mathematical model, not statistics
Physics-based calculation, developed by mathematician Sona Gallinger. No dependency on historical purchase data — works from the first product.
0.59cm measurement accuracy
Highest precision on the market. Industry standard is 1.5–2cm. maketribe measures real body dimensions, not self-reported data.
Per-body-area fit analysis
Not just "Size M recommended," but: "Size M fits shoulders and chest perfectly, sits slightly close at the waist. Size L gives more room."
Real garment analysis
Actual garment dimensions, fabric type, elasticity, and cut pattern feed into the calculation.
Directly on the product detail page
Runs as a plugin directly in the shop. No app, no redirect, no IT dependency.
Making the right choice
Anyone looking for an alternative to True Fit or Fit Analytics should understand the fundamental difference between statistical and physics-based size recommendations. maketribe calculates fit based on real body and garment data using a mathematical model — not based on other customers' purchasing behavior. The result: 0.59cm accuracy, per-body-area analysis, and recommendations your customers understand.