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Across Fit Week, we have looked at fit from multiple angles.
We explored how fit uncertainty shapes customer decisions, how it shows up in behavior long before returns occur, why sizing breaks down structurally, and how targeted interventions at the point of decision can reduce doubt.
What ties these perspectives together is the need for a shared system, one that makes fit visible, measurable, and actionable across the business.
This is where fit intelligence comes in.
The SAIZ Fit Intelligence layer is the foundation. Its role is to connect data that usually lives in separate places and turn it into a coherent view of fit performance.
SAIZ's Fit Intelligence platform brings together:
Instead of treating these as isolated datasets, SAIZ structures them around fit as a product-level signal.
This allows brands to understand how well each product aligns with their actual customer base, not in theory, but in practice.
Inside the SAIZ Fit Intelligence platform, brands gain several distinct views on fit performance.
Product Performance and FitRate™
FitRate™ shows the percentage of customers for whom a product is likely to fit as intended. Products can be compared across categories, seasons, and assortments, making it easier to identify which items create confidence and which introduce risk.
Fit Consistency
Fit Consistency highlights how predictable sizing and fit are across the assortment. Low consistency often correlates with lower trust and higher hesitation, even when individual products perform well.
Customer Avatars
Customer Avatars translate customer body data into realistic target groups. Brands can see who they are actually designing for, how body distributions differ by region or demographic, and how those distributions evolve over time.
Product Improvement and Predictive Product views
These views allow teams to analyze measurement tables, compare products against customer profiles, and predict fit and return performance before issues show up at scale.
Together, these views turn fit from an assumption into an observable system.
Understanding fit performance is only half the equation.
As we saw in the Fit Week case study, fit problems surface during the decision process. If insight stays upstream, customers still absorb the uncertainty.
This is why fit intelligence must be paired with activation.
SAIZ extensions bring fit intelligence directly into the shopping journey, where decisions are made.
Each extension addresses a specific moment of uncertainty.
SAIZ Recommender
The Recommender matches individual shopper data with detailed product-specific measurements to suggest the most suitable size for each product. It reduces guesswork and speeds up size selection.
SAIZ Charts
Dynamic size charts that are product-specific and easier to interpret than traditional tables. They reflect how a garment actually fits the shopper, rather than how it was intended to fit.
Automatic Nudges
Contextual fit cues shown on the PDP. These nudges highlight relevant fit information automatically, helping shoppers notice important details without interrupting their flow.
Checkout Nudges
Fit reassurance at the final decision point. These nudges help prevent size doubt and bracketing behavior just before purchase.
KAIA
An AI fit assistant that brings together product knowledge and customer context to answer fit-related questions conversationally.
Each of these extensions is powered by the same underlying fit intelligence layer. They do not operate independently or rely on generic rules.
The value of SAIZ lies in the connection between insight and action.
Fit intelligence identifies where confidence breaks down at product and size level. Activation tools translate that insight into clearer guidance for customers. Customer behavior then feeds back into the platform, refining future decisions.
This creates a closed loop:
Fit becomes a continuous process rather than a static setup.
Fashion e-commerce operates under increasing pressure. Assortments are larger, margins are thinner, and customers expect consistency across every touchpoint.
In this environment, fit uncertainty is costly.
Fit intelligence provides a way to manage that uncertainty deliberately, with shared visibility across teams and consistent activation for customers.
Fit has always influenced performance. What has changed is the ability to treat it as a system.
The Fit Intelligence Layer explains why fit issues occur. The activation layer ensures that insight reaches the customer when it matters.
SAIZ was built to connect both.
Together, they allow brands to move from fragmented fit decisions to a shared, data-driven understanding of fit, and to turn that understanding into more confident buying experiences.
If you want a practical way to spot where fit breaks inside your organization, The Fit Breaks Checklist from Fit Week helps teams identify the most common failure points across product, data, and the customer journey.
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