PerfittMerchandiser: Extending Fit Intelligence into Size-Level Inventory Planning

Most digital fit technology starts with a customer-facing question: “Which size should I buy?”

Perfitt is extending that question upstream with PerfittMerchandiser — a merchandising intelligence product designed to help footwear brands use fit and demand data before inventory reaches the market.

The goal is to support one of footwear planning’s most difficult decisions: which size range to carry, and how many units of each size to produce or purchase for a specific market.

From Size Recommendation to Merchandising Intelligence

PerfittSize helps individual shoppers find a suitable size by combining customer foot profiles with product-level shoe data and fit characteristics. Perfitt’s footwear database covers 400+ brands and 60,000+ shoe models.

As those interactions accumulate, they create another layer of information: foot-size distributions, regional differences, fit preferences, product characteristics, and purchase or return feedback.

PerfittMerchandiser is designed to apply that intelligence to merchandising decisions.

What PerfittMerchandiser Is Designed to Analyze

For a specific footwear model and target market, the product roadmap is designed to analyze information including:

• Region

• Age

• Gender

• Foot-size distribution

• Fit data and fit preferences

From there, the system is intended to help derive a more relevant size range and recommended planning quantities by size.

The shift is important: fit intelligence moves from helping a shopper make a better decision at checkout to helping a brand make a better inventory decision before the product is sold.

From Standard Size Curves to Size-Level Demand Intelligence

Footwear inventory is typically planned before individual customers arrive. Brands and retailers must decide which sizes to offer, how broadly to distribute them, and how many units of each size to allocate across markets and channels.

Historical sales, standard size curves, and merchant experience remain important inputs. But they do not always explain the underlying fit demand of the customers a brand is trying to serve.

PerfittMerchandiser is designed to add a fit-data layer to that process.

This becomes especially relevant for brands operating across multiple countries, where the same product can encounter different foot-size distributions, customer profiles, and fit preferences by region.

Rather than treating a size run as a fixed template, Perfitt’s approach is to make it more responsive to the people expected to buy the product.

Four Questions Behind Perfitt’s Fit Intelligence Strategy

Perfitt’s broader Fit Intelligence roadmap connects several stages of the footwear value chain:

• Which size should this customer buy?

• Which customers are most likely to fit this product?

• Which sizes are most likely to be needed in this market?

• How many units of each size should be planned?

PerfittSize addresses the first question. Fit profiles can support customer segmentation and size-based targeting. PerfittMerchandiser extends that same logic into assortment, inventory, and production planning.

“Our goal is to make fit data useful much earlier in the product lifecycle. Ultimately, the industry should be able to produce what is needed, in the quantities that are needed, and connect the right product and fit to the right person. PerfittMerchandiser is an important step toward that direction.” — Steena Lee, CEO of Perfitt

A Data Layer for Lower-Waste Retail

When size demand and planned inventory do not match, brands can be left with slow-moving sizes while customers simultaneously face stockouts in the sizes they need.

That imbalance can lead to discounting, inventory transfers, excess stock, and unnecessary production.

Fit and demand data cannot eliminate these challenges on its own. But it can give merchandising teams another evidence-based input when deciding what to buy, produce, and allocate.

The Right Product. The Right Size. The Right Person. The Right Quantity.

Perfitt’s long-term direction is to extend Fit Intelligence beyond checkout and into merchandising, sourcing, inventory planning, and eventually production decisions.

The idea is simple: personalization should not only help recommend products that have already been produced. It should also help brands understand what should be produced and distributed in the first place.

That is the role PerfittMerchandiser is being developed to play.

Related media coverage: Read the MustNews article on PerfittMerchandiser