The problem with conventional size recommendations
Statistical approach has fundamental flaws
Most size recommendation systems rely on a statistical approach: they collect purchase and return data from thousands of customers and derive patterns. This sounds logical — but has fundamental flaws.
Sizes aren't standardized
A medium from Brand A fits differently than a medium from Brand B. Size charts vary by region, manufacturing tolerance, and intended fit.
Bodies aren't comparable
Two people at 180cm and 80kg can have completely different proportions. Body measurements matter far more than aggregate statistics.
Clothing behaves differently
Cut, material, and elasticity fundamentally change the fit. Cotton stretches differently than polyester. A tight weave behaves differently than a loose knit.
The result: statistical guessing instead of real fit calculation.
maketribe's 4-Layer System
Layer 1: Body Model
Precise reconstruction of individual body measurements with up to 0.59cm accuracy. Not height/weight, but real measurements: shoulders, chest, waist, hips, arm length — per body area.
Layer 2: Garment Model
Analysis of the actual garment dimensions, cut pattern, material composition, and elasticity. Each product is individually modeled — not just assigned to a size chart.
Layer 3: Mathematical Model
Physics-based calculation of how the garment behaves on the individual body. Not a statistical model from other users' purchase data — but a deterministic simulation based on real parameters.
Layer 4: Fit Simulation
Per-body-area analysis: "Size M fits shoulders and chest perfectly, sits slightly close at the waist. Size L gives more room." The customer understands the fit and makes an informed decision.
Directly on the product detail page
maketribe runs exactly where purchase decisions happen — on the product detail page of your online shop. No redirects, no app, no extra step. Fit analysis is part of the normal buying process.
Plug & Play Integration
Runs directly in the shop, no IT dependency, API available.
Automated infrastructure
Product Data Processing
Automated product data processing — unstructured data is analyzed and adapted to brand logic.
Real-Time Calculation
Real-time fit calculation for every combination of body and garment, consistent across the entire catalog.
Continuous Optimization
Self-optimizing through integration of return and fit feedback.
maketribe is an automated fit intelligence platform that runs directly on the product detail page. The technology calculates in real-time how a garment fits on an individual body — based on a mathematical model instead of statistical prediction. With 0.59cm measurement accuracy, per-body-area analysis, and consideration of fabric properties and elasticity, maketribe sets the new standard for fit intelligence in fashion e-commerce.