Product discovery for furniture stores whose catalogs deserve better than a search bar
You carry the right piece, the shopper is on your site looking for it, and the two never meet — because a keyword search bar can't parse 'something like a cloud couch but firmer, under $3,000.'
ShowroomOps replaces dead-end search and filter maze with conversational discovery: shoppers describe what they need the way they'd tell a floor associate, and the concierge finds it in your live catalog — or honestly tells them the closest real alternative.
Free · a 30-minute walkthrough with the operator who built it, not a sales rep
Store Concierge
Answers from your catalog, policies, and floor inventory
Hartley Performance Sectional
112" · L-shape
$3,295 $4,695
In stock — on the showroom floor
See productMarlow Chaise Sectional
108" · reversible chaise
$2,850
In stock — ships in 5–7 days
See productEverett Track-Arm Sofa + Ottoman
104" combined
$2,390 $3,190
Custom fabrics — 4–6 weeks
See productThe real problem
How furniture catalogs hide their own inventory
The average furniture site owns thousands of SKUs and surfaces a fraction of them. The rest sit invisible behind discovery tools built for reordering printer ink.
Keyword search fails natural language
Shoppers search 'couch that fits a small apartment' and 'dining table for 8 that seats 10 in a pinch.' Keyword engines return zero results or 400 — both are exits.
Filters flatten what matters
Real constraints — fits a 96-inch wall, pet-friendly fabric, arrives by December — don't map to checkbox facets. So filters go unused and browsing becomes scrolling.
Category pages dead-end
A shopper who exhausts 'Sectionals' page 3 has no next move. Nothing asks what they're actually trying to solve, so a near-match in 'Sofas + Ottomans' stays unfound.
Sparse product data starves every tool
Missing dimensions, unstructured fabric attributes, absent lead times — discovery is only as good as catalog data, and most furniture catalogs have been maintained for humans, not machines.
What we install
Discovery that works like a floor conversation
Describe, refine, see options, decide — the loop every good showroom runs, installed on your website.
Natural-language catalog search
Plain-English briefs parsed into real constraints and searched against your live inventory — size, fabric, price, availability, style — with follow-up questions when the brief is thin.
Product cards at every step
Results as cards: image, title, price with strikethrough where on sale, availability note, and a link — then a recap of the best fit. Cards first, prose second.
Catalog data enrichment
Implementation includes structuring dimensions, materials, and lead times where your data is thin — the unglamorous work that makes discovery (and your ad feeds) actually good.
Graceful dead-end handling
No match? The concierge says so, shows nearest real options with trade-offs named, and offers the showroom or a designer — instead of a zero-results page.
Full module walkthrough on the product page.
First implementation
Built and proven inside a real furniture store
We watched shoppers on our own store type briefs our search couldn't parse — building discovery that answers them is where this whole system started.
ShowroomOps was built inside our own high-end furniture store — one large destination showroom, a deep new-and-consignment catalog, and a sales floor that closes most of the revenue. Live catalog, real policies, real customers. We share the store's identity and full detail privately, on the teardown call.
- outsold in one, at pace
- 5 yrs
- 2026 store revenue is pacing past the previous five years of sales combined.
- June revenue, year over year
- 4.05×
- $628K in June 2026, with July projected near $765K.
- chat-assisted revenue in 14 days
- $27.5K
- Orders matched to concierge conversations after auto-answer went live — chat volume roughly doubled, and matched revenue ran at a ~$60K/month pace.
How we count: We report the store's numbers as the store's numbers and assisted revenue as matched orders — never claimed lift from any single tool. The growth came from the whole operating stack working together: buying, marketing, catalog, concierge, and measurement. We'd rather under-claim and show you the methodology.
Read the full case study →Engagement
How retailers work with us
Discovery, cards, and enrichment are included in both options — the Self-Setup System and the Custom, done-for-you engagement; deeper feed and catalog work scales with the Custom engagement. Full pricing detail here.
Custom
Done for youfrom $75K setup
+ $15K/month
We build and run the whole operating stack for you — scoped per engagement, scaling up for multi-location and multi-brand operators.
Self-Setup System
You implement it$25K one-time
+ $500/month software
The same system we run in our own store, handed to your team to implement in logical order with our complete self-setup guide.
The 90-day launch guarantee
“If we do not launch your concierge, ingest your catalog and policies, train it on your top questions, and generate the agreed qualified sales conversations or showroom/design leads within 90 days, we work free until we do, up to two additional months.”
This is an implementation guarantee, not a revenue guarantee — nobody can honestly guarantee revenue in a seasonal, omnichannel business. What we can guarantee is that the system gets built, launched, and producing the agreed conversations and leads, or you stop paying the retainer while we finish the job.
The launch guarantee applies to Custom, done-for-you engagements. The Self-Setup System is a one-time purchase your team implements with the guide.
Questions
Frequently asked
How is this different from upgrading our site search (Algolia, Searchanise, etc.)?
Better keyword search still requires the shopper to speak keyword. Conversational discovery accepts the brief as humans give it — mixed constraints, vague style language, budget, timing — asks clarifying questions, and explains its results. Search upgrades help people who already know your catalog's vocabulary; this helps everyone else.
Our product data is a mess. Can this still work?
Yes — messy data is the normal starting state, and catalog enrichment is part of implementation, prioritized by what shoppers actually ask about. Dimensions, fabric attributes, and lead times usually come first. The enrichment also upgrades your PDPs, feeds, and ads, so the work compounds.
Does it handle style-language queries like 'japandi' or 'looks like Restoration Hardware'?
Within honesty limits, yes. Style descriptors map to your catalog's actual aesthetic attributes, and comparative references get translated into concrete traits — silhouette, materials, finish. What it won't do is claim a $1,200 sofa is equivalent to a $6,000 one; it presents the honest nearest fits.
What happens to shoppers who prefer normal browsing?
Nothing changes for them — your collections, filters, and search stay as they are. The concierge is an additional path, most valuable to exactly the shoppers your current tools fail: the brief-holders, the overwhelmed, and the ones about to leave.
Can it surface slow-moving inventory?
Within the shopper's constraints, yes — merchandising priorities like floor models and clearance pieces can be weighted so discovery helps move what you need moved, without ever recommending a piece that fails the brief.
Find out what your search is hiding
The teardown includes live brief-testing against your current discovery — you'll see the exact queries that die today and how the concierge would answer each one from your own catalog.
The teardown is free and delivered live on a 30-minute call by the operator who built the system. We onboard a small number of retailers at a time — each system is built from real catalog and policy data.