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Westchester County, NY — Clothing stores Saturation

How many clothing stores exist per person present — residents plus daytime workers — by ZIP code, compared with the U.S. average. Establishment data: Census ZBP 2023. Population: ACS 2024 5-year. 79 ZIP codes analyzed.

Includes: Family clothing stores · General apparel shops. Counted together because official statistics use one 448140 code.

Measured density: Range spans bands — 0.69× the U.S. rate (between 0.69× and 2.31× once withheld ZIP cells are counted)

Why a range: Census does not publish a ZIP-by-industry count when that ZIP has 0–2 businesses. 72 ZIP cells in this county are withheld, 67 of them with residents. Each could hold 0, 1, or 2 businesses: counting them all as 0 gives the low end, counting them all as 2 gives the high end — the data cannot say where the truth sits. The density range uses only the populated cells, since ZIPs without residents are excluded from per-person rates. How ranges work

Range spans the U.S. rate   Westchester County clothing stores — 69–231% of the U.S. rate

57 clothing stores are counted in Westchester County — 0.5 per 10,000 people present (residents + daytime workers), 69% of the U.S. rate of 0.7.

On the comparable ZIP set (ZIPs with a published count in every year), the total has fallen 21% between 2015 and 2023 (62 → 49). That set is smaller than today's county total. 2020–2021 were pandemic-distorted, and Census rounds counts, so small moves are within noise.

Measured supply density is highest in 10704 (Yonkers), 10710 (Yonkers), 10598 (Yorktown Heights) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 10550 (Mount Vernon), 10573 (Port Chester), 10549 (Mount Kisco).

Census County Business Patterns (2023) puts the county-wide count at 76 establishments, including locations in ZIP codes that do not map to a ZCTA — so it can run slightly above the sum of the ZIP rows on this page. It is annual, so it lags more than QCEW.

Measured density: Westchester County sits at 69% of the U.S. rate for clothing stores. 67 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 69% and 231% of the U.S. rate. Why. The highest measured density is in 10704 and 10710; the lowest measured density is in 10550 and 10573.

This is a supply-side read: it counts existing clothing stores and the people present, not foot traffic, income, rent, or whether locals want more. Treat low density as a question to check, not an answer.

Clothing stores
57–201
published count; upper bound counts each withheld ZIP cell as 2 (72 cells) (2023)
Per 10,000 present
0.5
residents + daytime workers
U.S. average
0.7
per 10,000 present
County index
0.69×
vs. U.S.
Latest year (CBP)
76
2023 — $64M annual payroll
Residents
997,782
74 ZIPs with data
Workers
391,628
jobs located in county

Is the area growing?

Population
1,006,447
Census PEP, July 1 2024
Change since 2020
+0.5%
+4,958 people
Net migration 2024
+6,269
international +10,427, domestic −4,158
Jobs located here
389,868
LODES 2022, −5.8% since 2019

Westchester County had an estimated 1,006,447 residents on July 1, 2024 — 0.5% more than in 2020 (+4,958). In the latest year it gained 9,521 people: births minus deaths +3,202, international migration +10,427, domestic migration −4,158. Components are published separately and may not sum exactly.

389,868 jobs were located in the county in 2022 (−5.8% since 2019), and 426,608 employed residents lived there (−1.5% since 2019). LODES counts wage and salary jobs covered by unemployment insurance plus federal jobs; it excludes the self-employed and military, and counts jobs rather than unique people. 2019→2022 spans the pandemic, so read it as one change, not a trend.

Population and migration say whether the customer base is growing. They do not say whether people want another business of this type. Definitions and limits →  ·  Full county detail →

ZIP gaining residents
2015–19 → 2020–24
Change
10701 Yonkers
+14.7%
10538 Larchmont
+8.9%
10706 Hastings On Hudson
+8.1%
ZIP losing residents
2015–19 → 2020–24
Change

No ZIP had a statistically significant decrease.

ACS 5-year estimates for 2015–2019 and 2020–2024. Only ZIPs with at least 2,000 residents in both windows and a change larger than the survey margin of error (90%) are listed — small ZIPs move a lot on paper without a real signal.

Nonemployer businesses

Not shown. Census now groups clothing with clothing accessories (NAICS 45811); a family-clothing-only nonemployer count is not published.

Census Nonemployer Statistics 2024 (NAICS 2022). We do not approximate this figure.

Saturation map

Each ZIP area is shaded by its density of this business type per person present (residents + workers) vs. the U.S. average. Click any ZIP to zoom to its boundary, see its numbers, and switch to aerial imagery. Individual mapped shops appear as dots at street level — Show locations zooms you in to them (scroll or double-click to zoom).

Basemap:
Under 50% 50–100% 100–150% 150–250% 250%+ 0–2 (not published) / no data ZIP total (dot size) Mapped shop (OpenStreetMap, street level)

Map data © OpenStreetMap contributors, tiles by OpenFreeMap.

White dots are ZIP totals from the official Census count — the bigger the dot, the more clothing stores in that ZIP. They are aggregated, not individual shops. Turquoise dots are individual locations mapped in OpenStreetMap, shown only at street level; they are crowd-sourced and indicative, may be incomplete, and do not equal the official counts. Only the official ZIP totals feed the saturation index.

Market trend — down 21% since 2015

Number of clothing stores in Westchester County across 2015–2023, on a consistent set of ZIP codes present in every year — so changes are real, not ZIP-boundary artifacts. 2015/2018 are pre-pandemic baselines; 2020/2021 are COVID-distorted.

62
2015
60
2018
60
2020
56
2021
49
2022
49
2023

Highest measured density

ZIP
vs. U.S. average
Index
10704 Yonkers
497%
10710 Yonkers
362%
10598 Yorktown Heights
216%
10549 Mount Kisco
184%
10573 Port Chester
153%
10550 Mount Vernon
95%

Lowest measured density

ZIP
vs. U.S. average
Index
10550 Mount Vernon
95%
10573 Port Chester
153%
10549 Mount Kisco
184%
10598 Yorktown Heights
216%
10710 Yonkers
362%
10704 Yonkers
497%
Low measured density is not evidence of opportunity. A ZIP with few clothing stores may simply lack foot traffic, retail space, or demand. We rank only residential and mixed ZIPs here; employment hubs and visitor destinations are listed separately below. ZIPs where Census did not publish a count (0–2 businesses) are not ranked: they may be the least served of all, but the data cannot tell 0 from 1 or 2. Verify those locally.

Employment hubs & destinations

These ZIPs have far more workers (or visitors) than residents, so their counts are driven by daytime and visitor demand — not a place to read "shortage" from resident numbers alone.

ZIPNeighborhoodType ResidentsWorkersClothing storesIndex
10601White Plains Employment hub 11,93031,532 20 1045%
10519Croton Falls Employment hub 99241 0–2 —
10535Jefferson Valley Employment hub 392907 0–2 —
10540Lincolndale Employment hub 108418 0–2 —
10545Maryknoll Employment hub 185461 0–2 —
10577Purchase Employment hub 5,94513,705 0–2 —

Scroll the table sideways to see all columns.

All ZIP codes

Click a column header to sort. Index = clothing stores per 10,000 people present (residents + 0.5×workers) ÷ the U.S. average. 100% = exactly average.

ZIPNeighborhood ResidentsWorkersClothing stores Per 10kIndexStatus
10601White Plains 11,93031,532 20 7.2 1045% Very high density
10704Yonkers 31,92111,758 13 3.4 497% Very high density
10710Yonkers 25,85512,232 8 2.5 362% Very high density
10598Yorktown Heights 28,8219,391 5 1.5 216% High density
10549Mount Kisco 16,13514,985 3 1.3 184% High density
10573Port Chester 40,78612,944 5 1.1 153% High density
10550Mount Vernon 38,97213,661 3 0.7 95% Below average
10501Amawalk 1,72746 0–2 — — Not published
10502Ardsley 6,1971,599 0–2 — — Not published
10503Ardsley On Hudson 13290 0–2 — — Not published
10504Armonk 7,66511,979 0–2 — — Not published
10505Baldwin Place 1,119532 0–2 — — Not published
10506Bedford 6,2441,404 0–2 — — Not published
10507Bedford Hills 6,1092,234 0–2 — — Not published
10510Briarcliff Manor 10,2262,973 0–2 — — Not published
10511Buchanan 2,397727 0–2 — — Not published
10514Chappaqua 11,7903,374 0–2 — — Not published
10517Crompond 58436 0–2 — — Not published
10518Cross River 992305 0–2 — — Not published
10519Croton Falls 99241 0–2 — — Not published
10520Croton On Hudson 12,3683,020 0–2 — — Not published
10522Dobbs Ferry 11,5026,597 0–2 — — Not published
10523Elmsford 9,45011,034 0–2 — — Not published
10526Goldens Bridge 2,128261 0–2 — — Not published
10527Granite Springs 418116 0–2 — — Not published
10528Harrison 14,0914,876 0–2 — — Not published
10530Hartsdale 13,8923,918 0–2 — — Not published
10532Hawthorne 5,3479,011 0–2 — — Not published
10533Irvington 7,3621,701 0–2 — — Not published
10535Jefferson Valley 392907 0–2 — — Not published
10536Katonah 10,6693,077 0–2 — — Not published
10538Larchmont 17,7604,138 0–2 — — Not published
10540Lincolndale 108418 0–2 — — Not published
10543Mamaroneck 20,9896,602 0–2 — — Not published
10545Maryknoll 185461 0–2 — — Not published
10546Millwood 1,392839 0–2 — — Not published
10547Mohegan Lake 7,2052,807 0–2 — — Not published
10548Montrose 4,2541,845 0–2 — — Not published
10552Mount Vernon 22,3412,307 0–2 — — Not published
10553Mount Vernon 11,0111,795 0–2 — — Not published
10560North Salem 4,9181,041 0–2 — — Not published
10562Ossining 33,7934,811 0–2 — — Not published
10566Peekskill 25,6255,527 0–2 — — Not published
10567Cortlandt Manor 19,9765,490 0–2 — — Not published
10570Pleasantville 13,2895,548 0–2 — — Not published
10576Pound Ridge 4,891840 0–2 — — Not published
10577Purchase 5,94513,705 0–2 — — Not published
10578Purdys 1,780466 0–2 — — Not published
10580Rye 18,3917,222 0–2 — — Not published
10583Scarsdale 40,20710,027 0–2 — — Not published
10587Shenorock —10 0–2 — — Not published
10588Shrub Oak 2,783396 0–2 — — Not published
10589Somers 7,6042,355 0–2 — — Not published
10590South Salem 6,989713 0–2 — — Not published
10591Tarrytown 23,92621,632 0–2 — — Not published
10594Thornwood 5,1101,497 0–2 — — Not published
10595Valhalla 7,24311,727 0–2 — — Not published
10596Verplanck 65090 0–2 — — Not published
10597Waccabuc 67979 0–2 — — Not published
10602White Plains —482 0–2 — — Not published
10603White Plains 18,9105,785 0–2 — — Not published
10604West Harrison 12,51710,831 0–2 — — Not published
10605White Plains 19,4938,356 0–2 — — Not published
10606White Plains 17,3415,128 0–2 — — Not published
10607White Plains 6,4663,292 0–2 — — Not published
10610White Plains —34 0–2 — — Not published
10701Yonkers 70,67618,791 0–2 — — Not published
10702Yonkers —534 0–2 — — Not published
10703Yonkers 22,5864,400 0–2 — — Not published
10705Yonkers 38,8874,627 0–2 — — Not published
10706Hastings On Hudson 9,1831,504 0–2 — — Not published
10707Tuckahoe 9,6882,233 0–2 — — Not published
10708Bronxville 22,4827,642 0–2 — — Not published
10709Eastchester 10,3522,195 0–2 — — Not published
10801New Rochelle 42,75415,053 0–2 — — Not published
10802New Rochelle —46 0–2 — — Not published
10803Pelham 13,0725,571 0–2 — — Not published
10804New Rochelle 16,1082,245 0–2 — — Not published
10805New Rochelle 20,9033,036 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in White Plains

The numbers above tell you how the market looks. To find a specific storefront, these marketplaces list available retail space for lease.

LoopNet
Largest commercial marketplace
Browse White Plains retail space →
Crexi
Free listings + market data
Browse White Plains retail space →
CityFeet
Retail space for lease
Browse White Plains retail space →

Open vacancy data (actual empty units) is only published by some cities; where it exists we show it directly. Listings above are third-party.

Census withholds some ZIP-by-industry cells to protect small businesses. 0–2 means the cell was not published (Census publishes industry counts only at 3+ per ZIP), so the ZIP is left unranked rather than counted as zero. ~ means the count is estimated from the broader industry group and can be off by a business or two.

Follow Westchester County and clothing stores

When a data vintage changes or a section of this report is revised, we post it to a public update feed. No email address, no account, no tracking — and nothing is sent unless something actually changed.

Subscribe to updates (RSS) How these numbers are built →

Methodology & sources

Establishments. U.S. Census ZIP Code Business Patterns (ZBP 2023), NAICS 448140 — family clothing stores. Counts establishments with paid employees. ZBP is published annually with a ~2-year lag.

Fresh county signal. This industry has no clean QCEW series, so the freshest county signal is Census County Business Patterns 2023: 76 establishments and $64M in annual payroll county-wide. This count includes locations in ZIP codes that do not map to a ZCTA, so it can be slightly higher than the sum of the ZIP rows. CBP is annual and slower than QCEW. It cannot be broken down by ZIP.

Population. U.S. Census American Community Survey 2024 5-year ZCTA population (table B01003). Workers are the ZIP's total employment from the same 2023 ZBP file.

Demand ("people present"). Demand comes from residents and daytime workers: residents + 0.5 × workers. This is the single documented assumption in the model and can be tuned.

Index. index = (ZIP establishments ÷ ZIP demand × 10,000) ÷ the U.S. average for this industry (0.69 per 10,000 present). It is a supply-side density measure; it does not capture income, rent, tourism, or whether locals actually want more.

Read the full methodology →  ·  Data sources & vintages →

BizGapMap — free, no-login small-business saturation reports for major U.S. counties. Built entirely from public U.S. Census, BLS, and IRS data (ZBP 2023, ACS 2024 5-year, PEP 2024, LODES, QCEW, IRS SOI). No forecasts, no revenue guesses — withheld cells are marked, and the few derived counts are labelled as estimates.