Volumental Shows 3D Foot Scans for Better Shoe Fit

Two shoes carrying the same size label can fit differently. In this Retail Refined demonstration, originally published in 2023, the host visits Volumental at NRF to explore how a 3D foot scan can inform recommendations across shoe styles and brands.

Volumental’s chief marketing officer walks through the scan, its measurements and the resulting recommendations. He explains how the company combines foot-shape data with purchase patterns and available inventory. The demonstration follows the information from the store floor into online shopping, then turns to the self-service and mobile experiences the company was developing.

A fast scan that turns foot shape into usable measurements

The on-booth demo emphasizes speed and simplicity: the host steps onto the platform and the scan completes in “about four or five seconds,” producing a 3D rendering of both feet. The conversation also notes a common fit nuance—many people’s feet differ in size—while this particular scan shows left and right matching. The point is to make the scan quick enough to fit into real shopping behavior.

From there, the interface presents measurement “panels” staff or shoppers can click through. Volumental’s representative says the system captures around 11 measurements, but they don’t always walk through all of them—choosing what’s most meaningful to build confidence that whatever gets pulled from the back room will actually fit. In the demo, those highlighted measurements include heel-to-toe length, arch height, instep height, heel width, and girth around the ball of the foot.

From measurements to predictions: why size labels aren’t enough

After reviewing the scan, Volumental’s representative frames the core problem: shoe size labels can be unreliable not only across brands but even within the same brand. That inconsistency is presented as the rationale for using a 3D scan plus AI-driven prediction to estimate what size a shopper needs for each model. The episode positions this as a way to match “foot shapes” with what similar shapes actually buy.

The footwear tab in the demo shows how recommendations can vary by model: one running shoe appears as a size 6 while another is suggested in a 6.5. The list is described as ranked by best fit, and it includes a visualization indicating where a shoe might feel looser or tighter. The interface also supports “use case” filtering—such as road versus trail running—so shoppers don’t just get a size, but a curated set aligned with their activity.

A second layer of validation comes from what the representative calls “foot twins”: people with similar feet who purchased a specific shoe. In the e-commerce example shown, the interface displays a distribution indicating the percentage of those similar shoppers who bought that model in a particular size. The episode treats this as reassurance for customers who otherwise might hedge by ordering multiple nearby sizes.

Tying fit to inventory so recommendations stay actionable

The demo stresses that recommendations are not meant to be abstract. Volumental’s representative says the results connect to each store’s back-room inventory, effectively bringing forward only items that are actually available and expected to fit well. For multi-brand retailers, the host asks whether the system can differentiate across brands (for example, different athletic labels), and the representative says it can—supporting brand-to-brand sizing differences within one experience.

The representative also describes saving the scan and sending it to the shopper by email. In his e-commerce example, a customer signs into the retailer’s website and receives recommendations based on the same measurements and available inventory. The proposed benefit is continuity: the shopper does not have to start the fit process again when moving from the store to the website.

Returns and “bracketing” are framed as the downstream cost of uncertainty. The representative contrasts a confident single-size order with ordering several sizes and shipping extras back, describing that behavior as bad for consumers, retailers (due to costs), and the planet. They also connect the issue to a supply-chain-constrained environment, arguing that unnecessary shipping time can erode margin when inventory spends weeks moving between locations.

What Volumental says comes next: self-serve and mobile scanning

Volumental’s representative describes fit-specialist retailers such as Fleet Feet and Red Wing as early use cases for the technology. These are settings where staff already spend time helping customers find an appropriate fit. He then contrasts that assisted experience with stores where the number of shoppers makes one-to-one service harder to provide.

The next step discussed is a self-service flow for stores where staff are “vastly outnumbered” by customers, such as outlet or hybrid environments. In that model, customers can select a category, scan their feet, and receive recommendations themselves. They can then use a QR code to carry results on their phone while shopping, ask an associate to retrieve a recommended model/size, or take the recommendation home to order online.

Mobile scanning was another development discussed in the 2023 interview. The representative described a web-based version in beta with customers, intended to produce a scan from two phone images without requiring an app download. His stated goal was to make that process simple and fast enough for shoppers to complete. The episode presents it as a product in development at that time.