Rugs Direct Dramatically Improves RPV and AOV with ML-Backed Search and Product Discovery
About Rugs Direct
Rugs Direct is the nation's leading source for area rugs.
It boasts a vast yet curated assortment of premier rugs for both consumers and trade professionals.
With a catalog spanning tens of
thousands of high-quality rugs, allowing shoppers to find the perfect rug as quickly as possible is of utmost importance.
It boasts a vast yet curated assortment of premier rugs for both consumers and trade professionals.
With a catalog spanning tens of
thousands of high-quality rugs, allowing shoppers to find the perfect rug as quickly as possible is of utmost importance.
Rugs Direct prides themselves on their IT team’s ability to keep core competencies in-house, but they're smart about it.
They prioritize spending their limited engineering time in the areas that are
really unique to them. With product discovery technology continuously advancing, they knew building search and discovery in-house would be reinventing the wheel. To compete with retailers like Amazon and Walmart that have massive search teams, they wanted to partner with someone that had done it many times before, and that had a strong road map for how they would be able to help Rugs Direct future-proof itself and continue to compete and help its users with a product discovery experience better than even its biggest competitors.
The Challenge
Everyone told them about "relevance" and "speed,"not KPIs that actually mattered to the business(like revenue and unit sales).
While search and product discovery technology at big retailers were advancing and driving KPIs, Rugs Direct noticed vendors they spoke with used the same outdated relevance-based "search and merch" technology they'd used for years.
Other vendors had showed AI-powered features in their demos, but didn’t actually have those features available after all. When Constructor reached out, Rugs Direct had every right to be skeptical, but they decided to give the product a shot.
The Results