Enterprise catalogs tend to get complicated for a handful of recurring reasons: high SKU counts, multiple brands running on shared infrastructure, and product logic that doesn't map cleanly onto a standard variant model.
Hunter Douglas's window covering brands push all three about as far as they go. Blinds2Go, Tuiss, and Select Blinds US price every product live, using a formula specific to each individual item rather than any shared rate. Two products of the exact same length can carry meaningfully different pricing depending on the calculation built for that particular product, which meant almost nothing about how these brands sell could be reduced to a fixed price list.
We began working with Hunter Douglas in 2024 to move Blinds2Go, Tuiss, and Select Blinds US onto a single Shopify foundation. The ambition was to build one flexible global theme all three brands could run on, but the question underneath it was whether Shopify, a platform built around fixed product variants, could actually hold a catalog that recalculates itself line by line on every customer interaction.
Nothing off the rack
Across all three sites, pricing had never been something you could look up. There was no static per-unit price map to reference anywhere in the business, and the math wasn't standardized even at the category level. Nearly every part of the buying experience depended on it: the price shown on a listing page, and the number that updates the moment a customer changes a measurement or fabric selection on a product page. Each of those moments meant calling Hunter Douglas's own pricing engine and getting a correct number back instantly, not after a noticeable delay.
One page, every window treatment
On their old VTEX build, Hunter Douglas’ buying experience had grown independently across all three brands, with each one handling configuration and pricing display its own way. There was no shared pattern for how or when a price appeared, and because the sites sat on different platforms entirely, keeping any of it consistent meant duplicating effort across separate teams.
On Shopify, the product page runs on a single form that adapts to whatever a given product's configuration requires, rather than hardcoding a version of that product for every possible combination. As a customer selects dimensions, fabric, lining, or control type, the form pulls from data delivered by Hunter Douglas's own product catalog engine and reflects those choices back with a live price pulled directly from their pricing engine. For a roman blind, that can mean choices across:
- Lining option
- Installation method
- Control location
- Product insurance
That same logic carries into the cart, where a cart transform function keeps the displayed price matched to the exact configuration selected, and into checkout, where a validation step calls the pricing engine once more to confirm nothing has changed since the item was added, prompting the customer to update their cart if it has.
Additionally, we built Shopify's newer customer accounts directly into the theme, rather than pointing customers to a separate, standalone account experience. Now, Hunter Douglas can carry its own navigation and design language all the way through login and order history, instead of handing customers off to a generic account screen.
What's running behind the shade
Previously, all of the logic that made this pricing and configuration model work lived in custom VTEX code, built and maintained largely by hand for each brand.
On Shopify, that logic runs through a connected chain of systems instead. Hunter Douglas's own product catalog engine holds the master data for every product and pushes it into Shopify as product metafields. None of the configuration options, measurements, fabric, lining, control type, exist as individual product variants; they arrive as structured data and get converted into product options that the storefront reads to build the buying experience. Every time a customer changes a selection, Shopify calls out to Hunter Douglas's separate, purpose-built pricing calculator to return the correct number, and that same call happens again at checkout as a validation step.
At this level of customization, holding an inventory record for every possible configuration isn't feasible, since almost no two orders are identical.
Service, made to measure
That reality creates a problem downstream. Because products are effectively assembled on the fly, with no SKU or inventory record covering every possible combination, editing an order after the fact, for a customer who wants to adjust a fabric choice or correct a measurement, is unusually complex.
We built order edit functionality that lets Hunter Douglas's team make those changes directly rather than cancelling and rebuilding an order from scratch. We also built a custom app connecting Zendesk, the client's customer service platform, to Shopify admin, giving support agents visibility into an order's exact configuration and the ability to act on it: changing an order, submitting a refund, or remaking a product, all from the tool their team already uses daily.
Shedding light on Shopify’s ability to handle complexity
Blinds2Go, Tuiss, and Select Blinds US now run on one flexible codebase, capable of supporting three brands with genuinely different pricing histories and configuration needs, without forcing any of them into a rigid, identical template. Tuiss Denmark and Tuiss Ireland were followed by Blinds2Go, and most recently by Select Blinds US.
What Hunter Douglas's migration to Shopify ultimately demonstrates is that a platform built around standard variants and fixed SKUs can still support products that are, by definition, never standard, provided the underlying architecture treats configuration and pricing as data to work with rather than a limitation to work around.
The same lesson holds well beyond window coverings, for any brand selling made-to-order furniture, equipment built to specification, or apparel and accessories with enough personalization options that a traditional variant model breaks down long before the catalog does.
If your brand is running into the limits of enterprise SKU counts or custom pricing logic on your current platform, we'd be glad to talk through what's possible.
