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Montgomery County, TX — Car washes Saturation

How many car washes 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. 25 ZIP codes analyzed.

Includes: Car wash tunnels & bays · Self-serve & automatic washes · Detailing (wash-attached). Counted together because official statistics use one 811192 code.

Measured density: Range spans bands — 0.53× the U.S. rate (between 0.53× and 1.38× 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. 20 ZIP cells in this county are withheld, 16 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   Montgomery County car washes — 53–138% of the U.S. rate

20 car washes are counted in Montgomery County — 0.3 per 10,000 people present (residents + daytime workers), 53% of the U.S. rate of 0.5.

On the comparable ZIP set (ZIPs with a published count in every year), the total has risen 40% between 2015 and 2023 (5 → 7). 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 77304 (Conroe), 77356 (Montgomery), 77354 (Magnolia) — well above the national rate. On measured density alone, the lowest-density residential ZIPs with a published count are 77357 (New Caney), 77354 (Magnolia), 77356 (Montgomery).

Census County Business Patterns (2023) puts the county-wide count at 40 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: Montgomery County sits at 53% of the U.S. rate for car washes. 16 ZIPs with population have no published count (each 0–2 businesses), so the true per-capita rate is between 53% and 138% of the U.S. rate. Why. The highest measured density is in 77304 and 77356; the lowest measured density is in 77357 and 77354.

This is a supply-side read: it counts existing car washes 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.

Car washes
20–60
published count; upper bound counts each withheld ZIP cell as 2 (20 cells) (2023)
Per 10,000 present
0.3
residents + daytime workers
U.S. average
0.5
per 10,000 present
County index
0.53×
vs. U.S.
Latest year (CBP)
40
2023 — $15M annual payroll
Residents
671,730
21 ZIPs with data
Workers
197,300
jobs located in county

Is the area growing?

Population
749,613
Census PEP, July 1 2024
Change since 2020
+19.9%
+124,193 people
Net migration 2024
+30,399
international +6,480, domestic +23,919
Jobs located here
220,765
LODES 2022, +12.4% since 2019

Montgomery County had an estimated 749,613 residents on July 1, 2024 — 19.9% more than in 2020 (+124,193). In the latest year it gained 34,268 people: births minus deaths +3,956, international migration +6,480, domestic migration +23,919. Components are published separately and may not sum exactly.

220,765 jobs were located in the county in 2022 (+12.4% since 2019), and 293,572 employed residents lived there (+16.1% 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
77303 Conroe
+39.7%
77384 Conroe
+37.6%
77357 New Caney
+35.6%
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 publishes only a broader group that also includes oil-change and other auto service shops, so a car-wash-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.

Basemap:
Under 50% 50–100% 100–150% 150–250% 250%+ 0–2 (not published) / no data ZIP total (dot size)

Map data © OpenStreetMap contributors, tiles by OpenFreeMap.

White dots are ZIP totals from the official Census count — the bigger the dot, the more car washes in that ZIP.

Market trend — up 40% since 2015

Number of car washes in Montgomery 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.

5
2015
4
2018
4
2020
3
2021
4
2022
7
2023

Highest measured density

ZIP
vs. U.S. average
Index
77304 Conroe
276%
77356 Montgomery
223%
77354 Magnolia
161%
77357 New Caney
151%

Lowest measured density

ZIP
vs. U.S. average
Index
77357 New Caney
151%
77354 Magnolia
161%
77356 Montgomery
223%
77304 Conroe
276%
Low measured density is not evidence of opportunity. A ZIP with few car washes 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.

All ZIP codes

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

ZIPNeighborhood ResidentsWorkersCar washes Per 10kIndexStatus
77304Conroe 44,22515,102 7 1.4 276% Very high density
77356Montgomery 32,5838,288 4 1.1 223% High density
77354Magnolia 44,90011,696 4 0.8 161% High density
77357New Caney 37,5926,174 3 0.7 151% High density
77301Conroe 37,76913,487 ~2 0.4 92% Below average
77302Conroe 21,5461,178 0–2 — — Not published
77303Conroe 28,8547,721 0–2 — — Not published
77305Conroe —679 0–2 — — Not published
77306Conroe 18,0861,664 0–2 — — Not published
77316Montgomery 34,6943,494 0–2 — — Not published
77318Willis 20,7922,833 0–2 — — Not published
77353Magnolia —86 0–2 — — Not published
77355Magnolia 32,8473,476 0–2 — — Not published
77362Pinehurst 8,0171,198 0–2 — — Not published
77365Porter 46,4186,023 0–2 — — Not published
77372Splendora 14,3671,201 0–2 — — Not published
77378Willis 17,6293,061 0–2 — — Not published
77380Spring 31,36954,843 0–2 — — Not published
77381Spring 36,13914,930 0–2 — — Not published
77382Spring 38,9865,675 0–2 — — Not published
77384Conroe 26,78110,005 0–2 — — Not published
77385Conroe 28,15614,095 0–2 — — Not published
77386Spring 69,98011,156 0–2 — — Not published
77387Spring —166 0–2 — — Not published
77393Spring —208 0–2 — — Not published

Scroll the table sideways to see all columns.

Find an actual space in Spring

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 Spring retail space →
Crexi
Free listings + market data
Browse Spring retail space →
CityFeet
Retail space for lease
Browse Spring 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 Montgomery County and car washes

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 811192 — car washes. 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: 40 establishments and $15M 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 (0.49 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.