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Alameda County, CA — 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. 58 ZIP codes analyzed.

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

Measured density: Range spans bands — 0.99× the U.S. rate (between 0.99× and 1.46× 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. 42 ZIP cells in this county are withheld, 33 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   Alameda County clothing stores — 99–146% of the U.S. rate

139 clothing stores are counted in Alameda County — 0.7 per 10,000 people present (residents + daytime workers), 99% of the U.S. rate of 0.7.

On the comparable ZIP set (ZIPs with a published count in every year), the total has risen 14% between 2015 and 2023 (111 → 126). 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 94551 (Livermore), 94588 (Pleasanton), 94608 (Emeryville) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 94550 (Livermore), 94538 (Fremont), 94578 (San Leandro).

Census County Business Patterns (2023) puts the county-wide count at 158 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: Alameda County sits at 99% of the U.S. rate for clothing stores. 33 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 99% and 146% of the U.S. rate. Why. The highest measured density is in 94551 and 94588; the lowest measured density is in 94550 and 94538.

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
139–223
published count; upper bound counts each withheld ZIP cell as 2 (42 cells) (2023)
Per 10,000 present
0.7
residents + daytime workers
U.S. average
0.7
per 10,000 present
County index
0.99×
vs. U.S.
Latest year (CBP)
158
2023 — $110M annual payroll
Residents
1,655,008
49 ZIPs with data
Workers
750,285
jobs located in county

Is the area growing?

Population
1,649,060
Census PEP, July 1 2024
Change since 2020
−1.9%
−31,554 people
Net migration 2024
+5,422
international +27,563, domestic −22,141
Jobs located here
819,506
LODES 2022, +1.5% since 2019

Alameda County had an estimated 1,649,060 residents on July 1, 2024 — 1.9% fewer than in 2020 (−31,554). In the latest year it gained 10,918 people: births minus deaths +5,479, international migration +27,563, domestic migration −22,141. Components are published separately and may not sum exactly.

819,506 jobs were located in the county in 2022 (+1.5% since 2019), and 801,997 employed residents lived there (−1.9% 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
94720 Berkeley
+102.6%
94568 Dublin
+27.3%
94608 Emeryville
+10.9%
ZIP losing residents
2015–19 → 2020–24
Change
94551 Livermore
−19.8%
94704 Berkeley
−19.6%
94587 Union City
−9.7%

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 — up 14% since 2015

Number of clothing stores in Alameda 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.

111
2015
131
2018
138
2020
134
2021
123
2022
126
2023

Highest measured density

ZIP
vs. U.S. average
Index
94551 Livermore
1036%
94588 Pleasanton
379%
94608 Emeryville
364%
94560 Newark
262%
94577 San Leandro
177%
94704 Berkeley
147%
94545 Hayward
145%
94609 Oakland
144%
94607 Oakland
134%
94601 Oakland
124%
94568 Dublin
123%
94501 Alameda
97%
94578 San Leandro
92%
94538 Fremont
76%
94550 Livermore
69%

Lowest measured density

ZIP
vs. U.S. average
Index
94550 Livermore
69%
94538 Fremont
76%
94578 San Leandro
92%
94501 Alameda
97%
94568 Dublin
123%
94601 Oakland
124%
94607 Oakland
134%
94609 Oakland
144%
94545 Hayward
145%
94704 Berkeley
147%
94577 San Leandro
177%
94560 Newark
262%
94608 Emeryville
364%
94588 Pleasanton
379%
94551 Livermore
1036%
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
94710Berkeley Employment hub 8,38018,030 8 665%
94612Oakland Employment hub 18,17543,353 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
94551Livermore 37,88530,354 38 7.2 1036% Very high density
94710Berkeley 8,38018,030 8 4.6 665% Very high density
94588Pleasanton 34,32861,022 17 2.6 379% Very high density
94608Emeryville 34,39534,469 13 2.5 364% Very high density
94560Newark 46,90327,577 11 1.8 262% Very high density
94577San Leandro 46,31738,477 8 1.2 177% High density
94704Berkeley 23,78811,484 3 1.0 147% Above average
94545Hayward 32,84333,827 5 1.0 145% Above average
94609Oakland 23,92812,431 3 1.0 144% Above average
94607Oakland 28,80428,767 4 0.9 134% Above average
94601Oakland 53,25910,209 5 0.9 124% Above average
94568Dublin 70,80322,730 7 0.9 123% Above average
94501Alameda 63,80820,851 5 0.7 97% Below average
94578San Leandro 41,76910,428 3 0.6 92% Below average
94538Fremont 67,78193,523 6 0.5 76% Below average
94550Livermore 49,87325,430 3 0.5 69% Below average
94502Alameda 13,43011,737 0–2 — — Not published
94536Fremont 70,6196,845 0–2 — — Not published
94537Fremont —278 0–2 — — Not published
94539Fremont 52,39619,562 0–2 — — Not published
94540Hayward —90 0–2 — — Not published
94541Hayward 67,13912,202 0–2 — — Not published
94542Hayward 14,8712,216 0–2 — — Not published
94544Hayward 76,94718,767 0–2 — — Not published
94546Castro Valley 44,8558,763 0–2 — — Not published
94552Castro Valley 14,506960 0–2 — — Not published
94555Fremont 37,5015,458 0–2 — — Not published
94557Hayward —67 0–2 — — Not published
94566Pleasanton 44,22216,027 0–2 — — Not published
94579San Leandro 20,0172,224 0–2 — — Not published
94580San Lorenzo 29,4203,718 0–2 — — Not published
94586Sunol 971686 0–2 — — Not published
94587Union City 67,46422,663 0–2 — — Not published
94602Oakland 31,7593,611 0–2 — — Not published
94603Oakland 35,7424,003 0–2 — — Not published
94604Oakland —11 0–2 — — Not published
94605Oakland 44,1033,593 0–2 — — Not published
94606Oakland 39,9665,139 0–2 — — Not published
94610Oakland 32,6285,572 0–2 — — Not published
94611Oakland 40,11613,527 0–2 — — Not published
94612Oakland 18,17543,353 0–2 — — Not published
94613Oakland 472359 0–2 — — Not published
94615Oakland —7 0–2 — — Not published
94618Oakland 16,9586,243 0–2 — — Not published
94619Oakland 26,8314,635 0–2 — — Not published
94620Piedmont —40 0–2 — — Not published
94621Oakland 33,84026,435 0–2 — — Not published
94624Oakland —34 0–2 — — Not published
94662Emeryville —12 0–2 — — Not published
94701Berkeley —35 0–2 — — Not published
94702Berkeley 17,6353,735 0–2 — — Not published
94703Berkeley 20,9342,484 0–2 — — Not published
94705Berkeley 13,9915,823 0–2 — — Not published
94706Albany 19,9693,852 0–2 — — Not published
94707Berkeley 12,8111,987 0–2 — — Not published
94708Berkeley 11,947739 0–2 — — Not published
94709Berkeley 12,1462,891 0–2 — — Not published
94720Berkeley 5,763867 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in Fremont

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 Fremont retail space →
Crexi
Free listings + market data
Browse Fremont retail space →
CityFeet
Retail space for lease
Browse Fremont 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 Alameda 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: 158 establishments and $110M 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.