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Size Suggestions & AI Engine

Configure the Smart Fit Engine to slash your return rates.

Up to 50% fewer returns Self-Optimizing Algorithm

How The Engine Thinks

The Smart Fit Engine doesn't just guess. It runs every customer measurement through a precise, 3-stage validation pipeline instantly.

1

Calculate Base Ease

The engine compares the product's exact garment dimensions against the customer's body profile.

Garment Body = Ease
2

Apply Tolerances

Every measurement is graded against your store's custom Comfort Boundaries. If a measurement falls outside the ideal zone, the AI applies a penalty score based on your strictness settings.

3

Weight & Recommend

The AI factors in your Priority Weights (e.g., Chest is more critical than Sleeve) to generate a final confidence score out of 100. The highest scoring size is recommended to the shopper.

Engine Configuration

You are in full control of the AI. Through your Shopify Admin dashboard, you can fine-tune exactly how strict or loose the engine should be when suggesting sizes.

Penalty per Inch

Controls how strictly the AI penalizes measurements that fall outside the ideal ease range.

Comfort Boundaries

Define the strict floor and ceiling for ease. Measurements within this zone get perfect scores.

Tie-Breaker Logic

When two sizes score identically, auto-select whether to recommend the looser or tighter fit.

Priority Weights

Assign a 1-5 importance weight to every measurement so the AI prioritizes critical fit points.

Engine Configuration Examples

Fit Score Thresholds

Perfect Fit
90 - 100
Good Fit
75 - 89
Acceptable
60 - 74

Priority Weights

Example
ChestHigh (4)
WaistMedium (3)
Sleeve LengthLow (1)
Growth

Smart Body Predictor

No measuring tape required. Our proprietary algorithm accurately predicts 15+ body dimensions using only the customer's Height, Weight, and Age.

  • Adapts to your demographic
  • Pre-fills customer profiles instantly
  • Accurate to within 1-2 inches
Enterprise

Continuous Learning AI

The engine gets smarter with every sale. It continuously analyzes accepted and returned sizes across your entire catalog to self-optimize its predictions over time.

  • Learns from return data patterns
  • Hyper-tunes to your specific sizing
  • Fully autonomous self-improvement