Buying physical things on the internet is hard. You have to quality-check a product without touching it, double-check dimensions for where the thing will go, and evaluate a seller's credibility, often with little data. But buying furniture online is a special case of hard, because the market is deliberately deceptive.

Furniture sellers actively prevent consumers from easily finding the same item at other stores, or under other names, because this allows them to charge more. The sellers get to name the products and they name them in confusing ways to facilitate price discriminaton. For example, this table at Wayfair (https://www.wayfair.com/furniture/pdp/williston-forge-veroni...) can also be found at Appliances Connection under a different name for roughly half the price (https://www.appliancesconnection.com/modway-eei2034brn.html). With most online shopping, the products you want have unambiguous names—if you want, say, a TV, you can simply search “Samsung 55 inch” and see what both Best Buy and Walmart are charging. But with furniture, sellers work actively to disrupt an accurate product graph and keep the market inefficient.

The net result is that buying furniture feels icky, noisy, and predatorial. It is much like buying a used car from a used-car salesperson might have felt before Carmax. This is reflected in how much consumers hate the industry: across 14 of the biggest furniture retailers the average NPS is -11, compared with 37 for e-commerce as a whole.

At the same time, people are buying furniture online more than ever. It is a $50B online market per year (roughly 1/3 Amazon, 1/3 Wayfair, and 1/3 everyone else) but it’s nowhere possible to do a simple apples-to-apples search for like items. Even on Wayfair, you can find the same exact item with different names and prices.

There’s no reason why furniture shopping online shouldn’t have the same advantages over going to a physical store that, say, shopping for a TV online does. It just needs to become possible to search across the entire catalog of furniture inventory.

We encountered this problem when Dane moved to New York and went through the labor of buying and assembling an apartment's worth of furniture, only to discover that one of his pieces of furniture was listed at another store but called something completely different and sold for 50% less. We discovered this behavior was pervasive among furniture sellers. We devised a solution for a small set of items. Our findings generated excitement in several threads on Reddit (here’s one: https://old.reddit.com/r/HomeDecorating/comments/s1oz0p/urba...). Many users told similar stories of frustration and confusion without a good solution and there was a lot of energy in these reactions—it turns out that the feeling of being taken advantage of is universally infuriating.

At the time, we were working on a tool to enable service professionals to grow their businesses. We did not find an acute enough pain for our then-users. When we started getting all these positive responses to exposing exploitative discrepancies in the furniture market, we realized we had hit on something people really care about, so we decided to build Spoken.

We crawl, scrape, and map product data and metadata across 1,000+ furniture stores to connect the exact same product across the internet. The mapping uses both algorithmic and human-driven scoring to evaluate exact product matches. It can be tricky, but it’s doable, to determine which products are the same—in a world of information abundance, there are many crumb trails. Often photos are the same. We can’t give away all the details here. But we do also augment brute human pattern-matching with our own tooling.

We aggregate all retailers’ inventory equally and surface transparent results—without ads, business-preference, or leaving out competitors. This means connecting Amazon, Google, Wayfair, and the long tail of hundreds of regional furniture stores.

Some shopping comparison extensions and applications do in fact show users some places that they can buy items—including some furniture items—more cheaply. However, their business models involve partnering with sellers, whom they give special treatment and won’t undercut. So they will only ever offer partial, not full information. We’ve decided not to do this, as we believe that the most efficient marketplace has a good chance to win in the end.

Our site is live, and free to use (https://www.spoken.io/). Our next step will be to allow users to purchase directly on our site across multiple stores to consolidate check out flows and avoid marketing pop-ups and emails. We will charge a fee and offer users an option to offset the environmental effect of their purchase. The stores will fulfill the orders.

We’re eager to hear your feedback and your experiences with the furniture market!