Pilot verified · July 2026

Every legacy furniture retailer in America. Qualified, verified, evidence-backed.

Built for Planned Furniture Promotions: a research pipeline that turns a raw industry mailing list into a living database of retailers matching PFP's exact criteria — 50+ years in business, 10,000+ sq ft, still operating — with a cited source behind every claim.

7,641
unique U.S. retailers on file
~1,410
projected age-qualified leads
100%
of findings carry cited evidence
Pilot records researched
200
stratified across 42 states
Confirmed still open
80.5%
9% verified closed — stale-list risk eliminated
Age-qualified (est. ≤ 1976)
37 18.5%
oldest: 1870 — Short Furniture, Litchfield IL
Verification accuracy
91%
independent adversarial re-check of findings
How it works

A pipeline, not a spreadsheet

Each stage is cheaper than the next and shrinks the work the next stage must do — so expensive research only ever runs on records that already passed. Every fact is cached and timestamped, making the list refreshable instead of disposable.

STAGE 0COMPLETE

Normalize & dedupe

9,012 raw rows → 7,641 unique retailers. Stable IDs keyed to street address + phone, never to name — same-name collisions are the #1 error in industry lists.

STAGE 1PILOT COMPLETE

Liveness check

Website, business listings, and social activity confirm each store still operates. Conflicting signals are flagged, never silently dropped.

STAGE 2PILOT COMPLETE

Founding year

The main filter. Reads each store's own history page, news coverage, and registries — capturing true continuous operating age, not just the "Since 19##" on the homepage.

STAGE 2BPILOT COMPLETE

Adversarial verification

A second, independent research pass tries to refute every positive finding before it reaches the list. Caught a false claim in the pilot — see Data Quality below.

STAGE 3NEXT

Square footage

Showroom size from the store's own claims, cross-checked against open building-footprint data — a defensible estimate for nearly every U.S. address before buying any data.

STAGE 4–5ROADMAP

Enrich, score & tier

Brands carried, buying groups, generational ownership, succession signals — rolled into dual rankings tuned to PFP's offer.

Live pilot data

200-record pilot: real results, not projections

A stratified sample spanning 42 states, run end-to-end through Stages 1–2B in July 2026. Hover any element for detail.

Qualification funnel

Pilot records advancing through each gate

Pilot outcomes

Where all 200 records landed

Qualified leads by founding decade

37 age-qualified stores — continuous operation since
The product

37 qualified leads — from just the first 200 records

Every row is a real, currently-operating U.S. furniture retailer verified to have been in continuous operation for 50+ years. Click any row to see the evidence behind the claim — the quoted source, and the liveness proof tied to the store's own address and phone. The full run projects ~1,410 of these.

RetailerCityStEst.YearsConfidenceSource
Why this data can be trusted

Built to catch the errors bought lists sell you

  • Identity by location, never by name. Facts only count when tied to the record's street address or phone. "Star Furniture" in West Virginia is an independent — its Houston namesake is a Berkshire Hathaway subsidiary. Name-matching merges them; we never do.
  • True operating age, not homepage age. Stores that changed hands say "Since 1981" while the location has traded continuously since 1973. We read the full history and record both dates.
  • Adversarial verification. An independent pass attempts to disprove every positive finding before it ships. Roughly 1 in 12 needs correction — which is exactly why the pass exists.
  • §
    Evidence on every claim. Each founding year and status carries its source and a quoted line of evidence — auditable, not asserted.

Caught in the pilot

The 1949 that wasn't. A retailer's site claimed heritage "since 1949." Verification traced that date to a predecessor business at a different — now closed — location; the current store actually dates to 2000. It was removed from the qualified list before delivery.

A keyword scraper keeps that lead. A list broker sells it to you. Our pipeline catches it.
How leads get ranked

One database, two lenses — because "50 years old" means two things

A store that's been family-run for half a century is either a rock-solid, well-capitalized operator — or an owner quietly approaching retirement. Those are opposite sales conversations. So every qualified lead gets scored through both lenses, producing two ranked call lists from the same underlying data. Draft weights below; final tuning happens against PFP's own best-client history.

Succession lens

"This owner may be approaching an exit" — prime for retirement & transition events

Stability lens

"Healthy, well-capitalized operator" — prime for high-impact promotional events

Each score runs 0–100 and is multiplied by a data-confidence factor, so a thin record can never outrank a well-documented one — leads with insufficient evidence go to a research queue instead of quietly sinking to the bottom of a list. Signals are collected during enrichment (Stage 4) from pages the pipeline is already reading, so scoring adds almost no marginal cost.

Where this goes

From qualified list to lead-intelligence engine

The pilot proves the method. Each phase compounds on the cached research before it — nothing is ever re-bought or re-researched.

NOWFull qualification run

  • Stages 1–2B across all 7,641 retailers, run in state-by-state tranches
  • ~1,410 age-qualified leads projected, each with cited evidence
  • Deep second pass on hard-to-research records (~400 more leads recoverable)

NEXTSize & enrich

  • Showroom square footage: stated claims + open building-footprint data
  • Brands carried, buying-group membership, e-commerce, multi-location mapping
  • Generational ownership & succession signals

LATERScore, tier & refresh

  • Dual rankings: succession-ready stores and promotion-ready stores — two call lists from one database
  • Quarterly liveness refresh — the list never goes stale
  • Self-serve filters as PFP's targeting gets more sophisticated