Furniture 3D and AR case studies: Sweef, MELIMELI, Contura

This article covers what we built for three clients and what changed for their customers. We don't have verified conversion figures for these projects, so none appear here. The clients are a modular sofa brand, a design sofa retailer and a maker of wood-burning stoves, and each came to us with a different problem.

Sweef: making a modular sofa easier to understand

Modular sofas are hard to sell on a web page. Shoppers buy them because they can choose their own layout, and that same choice makes the sofa hard to picture. On a normal product page, a shopper has to keep several module combinations in mind and guess how each would look in their room.

Sweef already had 3D material in-house but no way to show it to customers. We turned it into a modular configurator with web AR, so a shopper can build a layout and then place it in their own room at real size.

The Sweef case study says the approach gave customers a clearer link between a complex product and their own understanding of it, so the complexity became something they could work through instead of a barrier. For a product with this many variations, 3D helps the shopper make a decision, and web AR matters because shoppers can place the product in their own space.

That is as far as the case study goes. We don't publish a conversion percentage for Sweef because we don't have one we can back up in public.

MELIMELI: bringing showroom habits online

MELIMELI's customers care a lot about design and expect a high standard, and the vast majority of MELIMELI's sales happen online. That mix causes a specific problem. A sofa is often the main piece in a room, and people have traditionally chosen one in a showroom, sitting on it, walking round it and feeling four fabric options.

Production is the other half of the problem. Inspiring, informative content for large furniture is expensive to make, and every fabric and configuration adds to the bill.

What we built lets customers explore the sofas, browse fabrics and see the furniture in their own home. The MELIMELI case study describes the result as a richer online shopping experience that gave customers new ways to explore the range. It also notes that the same functionality improved MELIMELI's internal work, so content became cheaper to produce while the customer experience improved.

The client's own summary on that page is worth repeating because it sets a condition as well as making a recommendation: if you are facing challenges providing a close-to-real-life experience of your products online, and if that is essential for your business goals, then go for it. The condition in the middle of that sentence matters most.

Contura: a range with many options, sold online and in store

Contura makes wood-burning stoves, and a stove is not a simple purchase. Customers compare models, weigh up specifications and think about how the stove will look in a particular room, and the range has many models and options. Buyers usually use the website and then visit a retailer.

We built the 3D assets from Contura's CAD files, which is the best starting point for a manufactured product with exact dimensions, and used them for the Build Your Stove configurator and a web AR experience. Customers could work through the configuration online and were no longer limited to static product content.

The Contura case study reports a more effective buying process across online and in-store sales. It also points out that in-store visits improved, because customers came to the retailer having already narrowed down their choice. The quote on that page describes the solution as supporting the full customer journey rather than one step of it.

For brands that sell through dealers, this is often where the value lies. The website sells directly, and it also prepares buyers before they reach the dealer.

What the three have in common

The categories differ, but the pattern is the same.

In all three cases the product was large, expensive and sold in many versions. Those are the conditions where a 3D model clearly pays for itself, and plenty of catalogues don't meet them.

Conversion figures

None of the three case study pages states a conversion lift, so we don't give one here.

The public numbers that exist come from Shopify, and they need careful reading. Shopify reported in 2020 that interactions with products carrying 3D or AR content converted 94 percent more often than those without. That figure compares merchant data and doesn't come from a controlled test. For individual brands, Shopify reports Rebecca Minkoff shoppers being 44 percent more likely to add to cart after viewing a 3D model and 27 percent more likely to place an order, with a 65 percent purchase lift on AR-enabled pages and a 5 percent reduction in returns at Gunner Kennels.

Those results come from other brands selling other products. Your own numbers should decide your project, which is why we suggest a measured pilot before rolling 3D out across the whole catalogue.

If you are considering something similar

The three projects had different starting points. Sweef had existing 3D material, Contura had CAD files, and MELIMELI had a content production problem and a showroom experience to bring online. The starting point affects the cost and the order of the work.

The cheapest way to find out where you stand is to give us one product. Send us a single product and we will build the 3D model for free. You keep it whether or not you go further. If you do go ahead, pricing starts at 10 dollars per product per month on Basic with a 12-month term and a 100-variant minimum, Value is 20 dollars per model per month with a 24-month term, and Enterprise is quoted. Everything we build is listed on solutions.

Sources

• CharpstAR case studies: Sweef, MELIMELI, Contura.
• Shopify, 2020 merchant data, AR shopping and 3D e-commerce.