Home / Family clothing stores / Washington / King County, WA

King County, WA — Clothing stores Saturation

Name: Clothing stores density by ZIP code in King County, WA
Creator: BizGapMap

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. 113 ZIP codes analyzed.

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

Measured density: Range spans bands — 0.77× the U.S. rate (between 0.77× and 1.39× 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. 95 ZIP cells in this county are withheld, 64 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 King County clothing stores — 77–139% of the U.S. rate

156 clothing stores are counted in King County — 0.5 per 10,000 people present (residents + daytime workers), 77% 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 13% between 2015 and 2023 (156 → 136). 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 98188 (Seattle), 98045 (North Bend), 98001 (Auburn) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 98052 (Redmond), 98034 (Kirkland), 98033 (Kirkland).

Census County Business Patterns (2023) puts the county-wide count at 188 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: King County sits at 77% of the U.S. rate for clothing stores. 64 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 77% and 139% of the U.S. rate. Why. The highest measured density is in 98188 and 98045; the lowest measured density is in 98052 and 98034.

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

156–346

published count; upper bound counts each withheld ZIP cell as 2 (95 cells) (2023)

Per 10,000 present

0.5

residents + daytime workers

U.S. average

0.7

per 10,000 present

County index

0.77×

vs. U.S.

Latest year (CBP)

188

2023 — $191M annual payroll

Residents

2,298,524

82 ZIPs with data

Workers

1,295,866

jobs located in county

Is the area growing?

Population

2,340,211

Census PEP, July 1 2024

Change since 2020

+2.9%

+65,862 people

Net migration 2024

+35,932

international +48,433, domestic −12,501

Jobs located here

1,462,772

LODES 2022, +6.0% since 2019

King County had an estimated 2,340,211 residents on July 1, 2024 — 2.9% more than in 2020 (+65,862). In the latest year it gained 43,398 people: births minus deaths +7,415, international migration +48,433, domestic migration −12,501. Components are published separately and may not sum exactly.

1,462,772 jobs were located in the county in 2022 (+6.0% since 2019), and 1,114,772 employed residents lived there (+4.5% 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

98101 Seattle

+27.1%

98010 Black Diamond

+22.4%

98034 Kirkland

+20.8%

ZIP losing residents

2015–19 → 2020–24

Change

98024 Fall City

−43.3%

98148 Seattle

−20.0%

98011 Bothell

−14.4%

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 13% since 2015

Number of clothing stores in King 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.

156

2015

148

2018

142

2020

138

2021

129

2022

136

2023

Highest measured density

ZIP

vs. U.S. average

Index

98188 Seattle

823%

98045 North Bend

683%

98001 Auburn

582%

98004 Bellevue

470%

98105 Seattle

407%

98003 Federal Way

162%

98072 Woodinville

161%

98122 Seattle

127%

98107 Seattle

120%

98027 Issaquah

108%

98006 Bellevue

91%

98125 Seattle

88%

98033 Kirkland

80%

98034 Kirkland

68%

98052 Redmond

54%

Lowest measured density

ZIP

vs. U.S. average

Index

98052 Redmond

54%

98034 Kirkland

68%

98033 Kirkland

80%

98125 Seattle

88%

98006 Bellevue

91%

98027 Issaquah

108%

98107 Seattle

120%

98122 Seattle

127%

98072 Woodinville

161%

98003 Federal Way

162%

98105 Seattle

407%

98004 Bellevue

470%

98001 Auburn

582%

98045 North Bend

683%

98188 Seattle

823%

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.

ZIP	Neighborhood	Type	Residents	Workers	Clothing stores	Index
98101	Seattle	Employment hub	17,153	96,469	12	265%
98057	Renton	Employment hub	12,705	41,810	3	129%
98104	Seattle	Employment hub	16,542	63,710	3	90%
98050	Preston	Employment hub	108	1,014	0–2	—
98134	Seattle	Destination	645	39,386	0–2	—
98164	Seattle	Employment hub	292	2,891	0–2	—
98195	Seattle	Employment hub	2,757	8,614	0–2	—
98288	Skykomish	Employment hub	169	477	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.

ZIP	Neighborhood	Residents	Workers	Clothing stores	Per 10k	Index	Status
98188	Seattle	27,311	43,850	28	5.7	823%	Very high density
98045	North Bend	15,289	3,325	8	4.7	683%	Very high density
98001	Auburn	37,460	29,403	21	4.0	582%	Very high density
98004	Bellevue	39,897	74,258	25	3.2	470%	Very high density
98105	Seattle	49,767	21,275	17	2.8	407%	Very high density
98101	Seattle	17,153	96,469	12	1.8	265%	Very high density
98003	Federal Way	51,619	21,771	7	1.1	162%	High density
98072	Woodinville	24,446	23,071	4	1.1	161%	High density
98057	Renton	12,705	41,810	3	0.9	129%	Above average
98122	Seattle	43,234	27,645	5	0.9	127%	Above average
98107	Seattle	28,776	14,757	3	0.8	120%	Above average
98027	Issaquah	28,955	22,093	3	0.7	108%	Above average
98006	Bellevue	40,009	15,660	3	0.6	91%	Below average
98104	Seattle	16,542	63,710	3	0.6	90%	Below average
98125	Seattle	44,520	9,397	3	0.6	88%	Below average
98033	Kirkland	40,982	26,821	3	0.6	80%	Below average
98034	Kirkland	52,531	22,274	3	0.5	68%	Below average
98052	Redmond	80,717	106,441	5	0.4	54%	Below average
98002	Auburn	37,509	15,645	0–2	—	—	Not published
98005	Bellevue	21,846	27,375	0–2	—	—	Not published
98007	Bellevue	27,692	15,738	0–2	—	—	Not published
98008	Bellevue	27,242	6,622	0–2	—	—	Not published
98009	Bellevue	—	289	0–2	—	—	Not published
98010	Black Diamond	6,857	1,045	0–2	—	—	Not published
98011	Bothell	28,963	13,644	0–2	—	—	Not published
98013	Burton	—	2	0–2	—	—	Not published
98014	Carnation	8,264	1,148	0–2	—	—	Not published
98015	Bellevue	—	29	0–2	—	—	Not published
98019	Duvall	12,242	1,647	0–2	—	—	Not published
98022	Enumclaw	22,418	6,856	0–2	—	—	Not published
98023	Federal Way	50,448	3,990	0–2	—	—	Not published
98024	Fall City	3,908	546	0–2	—	—	Not published
98025	Hobart	52	3	0–2	—	—	Not published
98028	Kenmore	23,741	3,227	0–2	—	—	Not published
98029	Issaquah	30,586	8,592	0–2	—	—	Not published
98030	Kent	38,523	4,672	0–2	—	—	Not published
98031	Kent	40,094	8,748	0–2	—	—	Not published
98032	Kent	40,862	59,428	0–2	—	—	Not published
98035	Kent	—	236	0–2	—	—	Not published
98038	Maple Valley	37,324	6,029	0–2	—	—	Not published
98039	Medina	2,928	408	0–2	—	—	Not published
98040	Mercer Island	25,307	7,524	0–2	—	—	Not published
98041	Bothell	—	867	0–2	—	—	Not published
98042	Kent	50,216	7,063	0–2	—	—	Not published
98047	Pacific	6,817	4,522	0–2	—	—	Not published
98050	Preston	108	1,014	0–2	—	—	Not published
98051	Ravensdale	3,442	461	0–2	—	—	Not published
98053	Redmond	22,765	5,764	0–2	—	—	Not published
98055	Renton	24,660	23,311	0–2	—	—	Not published
98056	Renton	35,849	4,257	0–2	—	—	Not published
98058	Renton	42,980	3,663	0–2	—	—	Not published
98059	Renton	42,406	4,262	0–2	—	—	Not published
98062	Seahurst	—	13	0–2	—	—	Not published
98063	Federal Way	—	229	0–2	—	—	Not published
98064	Kent	—	77	0–2	—	—	Not published
98065	Snoqualmie	15,944	5,392	0–2	—	—	Not published
98070	Vashon	9,934	2,416	0–2	—	—	Not published
98071	Auburn	—	635	0–2	—	—	Not published
98073	Redmond	—	1,109	0–2	—	—	Not published
98074	Sammamish	30,761	2,868	0–2	—	—	Not published
98075	Sammamish	25,498	2,019	0–2	—	—	Not published
98077	Woodinville	14,109	1,191	0–2	—	—	Not published
98083	Kirkland	—	235	0–2	—	—	Not published
98092	Auburn	50,224	3,898	0–2	—	—	Not published
98093	Federal Way	—	20	0–2	—	—	Not published
98102	Seattle	27,333	10,504	0–2	—	—	Not published
98103	Seattle	52,671	25,838	0–2	—	—	Not published
98106	Seattle	28,690	6,209	0–2	—	—	Not published
98108	Seattle	25,529	29,689	0–2	—	—	Not published
98109	Seattle	34,328	68,378	0–2	—	—	Not published
98111	Seattle	—	376	0–2	—	—	Not published
98112	Seattle	23,921	6,614	0–2	—	—	Not published
98113	Seattle	—	49	0–2	—	—	Not published
98114	Seattle	—	92	0–2	—	—	Not published
98115	Seattle	54,349	11,038	0–2	—	—	Not published
98116	Seattle	28,711	6,402	0–2	—	—	Not published
98117	Seattle	35,711	4,293	0–2	—	—	Not published
98118	Seattle	50,500	8,751	0–2	—	—	Not published
98119	Seattle	26,879	20,382	0–2	—	—	Not published
98121	Seattle	21,166	34,570	0–2	—	—	Not published
98124	Seattle	—	367	0–2	—	—	Not published
98126	Seattle	22,975	4,021	0–2	—	—	Not published
98127	Seattle	—	22	0–2	—	—	Not published
98133	Seattle	53,249	15,774	0–2	—	—	Not published
98134	Seattle	645	39,386	0–2	—	—	Not published
98136	Seattle	17,252	2,026	0–2	—	—	Not published
98138	Seattle	—	77	0–2	—	—	Not published
98139	Seattle	—	30	0–2	—	—	Not published
98144	Seattle	33,787	11,888	0–2	—	—	Not published
98145	Seattle	—	36	0–2	—	—	Not published
98146	Seattle	28,573	2,223	0–2	—	—	Not published
98148	Seattle	9,715	3,818	0–2	—	—	Not published
98154	Seattle	0	2,163	0–2	—	—	Not published
98155	Seattle	36,511	4,619	0–2	—	—	Not published
98158	Seattle	0	11,629	0–2	—	—	Not published
98160	Seattle	—	34	0–2	—	—	Not published
98161	Seattle	—	546	0–2	—	—	Not published
98164	Seattle	292	2,891	0–2	—	—	Not published
98165	Seattle	—	26	0–2	—	—	Not published
98166	Seattle	22,082	6,025	0–2	—	—	Not published
98168	Seattle	35,528	16,934	0–2	—	—	Not published
98170	Seattle	—	19	0–2	—	—	Not published
98174	Seattle	0	22	0–2	—	—	Not published
98175	Seattle	—	8	0–2	—	—	Not published
98177	Seattle	21,090	1,698	0–2	—	—	Not published
98178	Seattle	26,748	1,850	0–2	—	—	Not published
98181	Seattle	—	23	0–2	—	—	Not published
98191	Seattle	—	693	0–2	—	—	Not published
98194	Seattle	—	4	0–2	—	—	Not published
98195	Seattle	2,757	8,614	0–2	—	—	Not published
98198	Seattle	40,463	6,976	0–2	—	—	Not published
98199	Seattle	22,468	4,960	0–2	—	—	Not published
98288	Skykomish	169	477	0–2	—	—	Not published

Scroll the table sideways to see all columns.

Find an actual space in Redmond

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 Redmond retail space →

Crexi

Free listings + market data

Browse Redmond retail space →

CityFeet

Retail space for lease

Browse Redmond 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 King 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.

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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: 188 establishments and $191M 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 →

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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.