We checked 'coffee shop near me' across 1,000 US cities. Here's where demand outpaces supply.

Four numbers that frame the screening model

Pulled directly from the 1,000-city dataset below.

Demand Scale

4.7M

Combined monthly searches across the 1,000 matched cities. This is not a category estimate. It is a location-screening signal for one high-intent query.

NYC Benchmark

Major cities with population above 100,000 that beat New York’s 3,550.3 searches per 100K residents.

Median Density

2,156.5

Median monthly searches per 100K across the full 1,000-city set. The real action starts well above that line.

Leading Overlap

Markets that rank on both the underserved list and the strongest 12-month trend list. Those are the places we would screen first.

US map Top 50 cities Underserved vs overserved College towns Trend leaders DMA view Methodology

“Coffee shop near me” is one of the cleanest local-intent terms in search. Nobody types it for entertainment. They type it because they want coffee, nearby, soon. That makes it useful as a demand-density proxy. Not a guarantee of store success. Not a substitute for rent, traffic, co-tenancy, or unit economics. But a very efficient early filter.

To build that filter, we pulled live Google Ads historical metrics for 1,000 US cities matched to Google Ads city geo targets, then normalized the monthly volume using the latest available 2024 Census place populations. The result surfaces a pattern that raw volume alone would miss: some markets are huge because they are huge, while others are genuinely overperforming relative to their size.

New York still leads the country on raw volume at 301,000 monthly searches. But the more revealing metric is intensity. New York posts 3,550.3 searches per 100K residents. That is strong, but far from unbeatable. 97 major cities in this study clear that bar.

The US map

Each point below is one of the 1,000 matched cities. Dot size reflects raw monthly search volume. Color reflects volume per 100K residents. The broad pattern is clear: Sunbelt and western metros show up repeatedly, but so do selective legacy and college-driven markets. The most interesting story is not simply “big cities search more.” It is that mid-size cities like Denver, Seattle, Austin, and Orlando generate much denser local coffee intent than New York on a per-capita basis.

Coffee demand map

Hover points for city-level volume, CPC, and demand density.

Lower density

Higher density

Raw volume leader

New York, NY

301,000/mo

Per-capita leader

Orange, CA

65,607.8 per 100K

Large-city standouts

Atlanta, GA

11,633 per 100K

Dataset retrieval

April 10, 2026

Google Ads live pull + Census Vintage 2024

Top 50 cities by monthly volume

Raw volume matters because it points to absolute demand. But the highlighted column here is Volume per 100K residents. That is the bridge from “big city, big number” to “market where search demand looks unusually concentrated.”

Rank	City	Monthly Volume	Population	Volume per 100K	CPC	Comp. Index	12-Month Trend
1	New York, NY	301,000	8,478,072	3,550.3	$12.59	21	—+31.4%
2	Los Angeles, CA	135,000	3,878,704	3,480.5	$18.10	13	—+82.3%
3	Chicago, IL	135,000	2,721,308	4,960.8	$16.31	20	—+22.0%
4	Houston, TX	110,000	2,390,125	4,602.3	$17.25	17	—+95.9%
5	Austin, TX	90,500	993,588	9,108.4	$15.89	17	—+82.4%
6	Orange, CA	90,500	137,941	65,607.8	$19.06	15	—+71.1%
7	San Diego, CA	74,000	1,404,452	5,269	$16.53	18	—+60.6%
8	San Francisco, CA	74,000	827,526	8,942.3	$15.74	14	—+71.7%
9	Seattle, WA	74,000	780,995	9,475.1	$11.43	14	—+60.6%
10	Denver, CO	74,000	729,019	10,150.6	$13.25	16	—+60.6%
11	Dallas, TX	60,500	1,326,087	4,562.3	$16.13	17	—+60.5%
12	Atlanta, GA	60,500	520,070	11,633	$20.14	18	—+70.9%
13	Philadelphia, PA	49,500	1,573,916	3,145	$26.58	16	—+39.8%
14	San Antonio, TX	49,500	1,526,656	3,242.4	$27.97	21	—+96.2%
15	Portland, OR	49,500	635,749	7,786.1	$15.39	14	—+71.7%
16	Minneapolis, MN	49,500	428,579	11,549.8	$20.75	16	—+60.6%
17	Phoenix, AZ	40,500	1,673,164	2,420.6	$19.35	20	—+96.2%
18	Charlotte, NC	40,500	943,476	4,292.6	$19.35	18	—+60.5%
19	Las Vegas, NV	40,500	678,922	5,965.3	$19.85	19	—+82.6%
20	Boston, MA	40,500	673,458	6,013.7	$18.19	15	—+42.3%
21	Orlando, FL	33,100	334,854	9,884.9	$23.45	20	—+140.3%
22	Fort Worth, TX	27,100	1,008,106	2,688.2	$16.70	17	—+60.8%
23	San Jose, CA	27,100	997,368	2,717.2	$18.22	16	—+110.1%
24	Columbus, OH	27,100	933,263	2,903.8	$19.05	19	—+60.8%
25	Raleigh, NC	27,100	499,825	5,421.9	$28.34	15	—+85.7%
26	Miami, FL	27,100	487,014	5,564.5	$25.75	22	—+108.0%
27	St. Paul, MN	27,100	307,465	8,814	$21.70	18	—+60.8%
28	Jacksonville, FL	22,200	1,009,833	2,198.4	$21.74	18	—+127.0%
29	Baltimore, MD	22,200	568,271	3,906.6	$19.77	13	—+71.5%
30	Kansas City, MO	22,200	516,032	4,302.1	$21.50	16	—+61.0%
31	Tampa, FL	22,200	414,547	5,355.2	$27.57	21	—+96.6%
32	Cleveland, OH	22,200	365,379	6,075.9	$28.48	15	—+42.7%
33	New Orleans, LA	22,200	362,701	6,120.7	$13.44	16	—+83.1%
34	Pittsburgh, PA	22,200	307,668	7,215.6	$15.79	17	—+49.9%
35	St. Louis, MO	22,200	279,695	7,937.2	$20.97	17	—+42.7%
36	Detroit, MI	18,100	645,705	2,803.1	$26.35	20	—+51.9%
37	Milwaukee, WI	18,100	563,531	3,211.9	$25.76	17	—+60.9%
38	Sacramento, CA	18,100	535,798	3,378.1	$14.87	15	—+83.5%
39	Colorado Springs, CO	18,100	493,554	3,667.3	$21.66	19	—+60.9%
40	Oakland, CA	18,100	443,554	4,080.7	$15.39	13	—+110.4%
41	Cincinnati, OH	18,100	314,915	5,747.6	$17.15	15	—+49.7%
42	Scottsdale, AZ	18,100	246,170	7,352.6	$28.00	24	—+137.5%
43	Salt Lake City, UT	18,100	217,783	8,311	$14.92	18	—+71.5%
44	Oklahoma City, OK	14,800	712,919	2,076	$12.40	15	—+60.6%
45	Albuquerque, NM	14,800	560,326	2,641.3	$31.37	16	—+85.5%
46	Tucson, AZ	14,800	554,013	2,671.4	$13.98	16	—+155.2%
47	Long Beach, CA	14,800	450,901	3,282.3	$14.61	11	—+96.3%
48	Durham, NC	14,800	301,870	4,902.8	$40.26	14	—+85.5%
49	Plano, TX	14,800	293,286	5,046.3	$23.85	22	—+60.6%
50	Madison, WI	14,800	285,300	5,187.5	$16.41	14	—+51.5%

The overserved and the underserved

The most useful ranking in this study is not raw volume. It is the blend of per-capita demand, lower advertiser competition, and positive 12-month momentum. That is the closest we can get, from search data alone, to a screening list of markets where demand may be arriving faster than supply.

Top 10 underserved proxy markets

High density, lighter competition, rising trend

1. Orlando, FL

33,100/mo · 9,884.9 per 100K · comp 20

12M trend

+140.3%

2. Tacoma, WA

12,100/mo · 5,302.3 per 100K · comp 13

12M trend

+97.0%

3. Knoxville, TN

12,100/mo · 6,088.9 per 100K · comp 13

12M trend

+85.2%

4. Scottsdale, AZ

18,100/mo · 7,352.6 per 100K · comp 24

12M trend

+137.5%

5. Lakewood, CO

12,100/mo · 7,713.5 per 100K · comp 15

12M trend

+83.1%

6. Bellevue, WA

9,900/mo · 6,412.9 per 100K · comp 15

12M trend

+83.3%

7. Fort Lauderdale, FL

12,100/mo · 6,347 per 100K · comp 25

12M trend

+123.9%

8. Oakland, CA

18,100/mo · 4,080.7 per 100K · comp 13

12M trend

+110.4%

9. Raleigh, NC

27,100/mo · 5,421.9 per 100K · comp 15

12M trend

+85.7%

10. Miami, FL

27,100/mo · 5,564.5 per 100K · comp 22

12M trend

+108.0%

Top 10 overserved proxy markets

Large populations, weaker density, tougher competition

1. Wichita, KS

400,991 residents · 6,600/mo · 1,645.9 per 100K

Comp. index

2. Mesa, AZ

517,151 residents · 9,900/mo · 1,914.3 per 100K

Comp. index

3. Henderson, NV

350,039 residents · 5,400/mo · 1,542.7 per 100K

Comp. index

4. Port St. Lucie, FL

258,575 residents · 2,900/mo · 1,121.5 per 100K

Comp. index

5. North Las Vegas, NV

294,034 residents · 2,400/mo · 816.2 per 100K

Comp. index

6. Cape Coral, FL

233,025 residents · 2,900/mo · 1,244.5 per 100K

Comp. index

7. Gilbert, AZ

288,790 residents · 5,400/mo · 1,869.9 per 100K

Comp. index

8. Toledo, OH

265,638 residents · 3,600/mo · 1,355.2 per 100K

Comp. index

9. Phoenix, AZ

1,673,164 residents · 40,500/mo · 2,420.6 per 100K

Comp. index

Search is useful because it leads behavior. People search before they buy. That makes the 12-month trend section more than a retrospective scoreboard. It is the closest thing in this study to a forward indicator.

Top emerging markets

1. West Palm Beach, FL

8,100/mo · 6,340.8 per 100K · comp 20

+155.6%

2. Tucson, AZ

14,800/mo · 2,671.4 per 100K · comp 16

+155.2%

3. Ontario, CA

5,400/mo · 2,914.4 per 100K · comp 15

+142.6%

4. Roseville, CA

4,400/mo · 2,694.4 per 100K · comp 17

+141.8%

5. Santa Clarita, CA

5,400/mo · 2,356.4 per 100K · comp 11

+141.7%

6. Tallahassee, FL

5,400/mo · 2,633 per 100K · comp 13

+141.5%

7. Orlando, FL

33,100/mo · 9,884.9 per 100K · comp 20

+140.3%

8. Mesa, AZ

9,900/mo · 1,914.3 per 100K · comp 22

+139.7%

9. Scottsdale, AZ

18,100/mo · 7,352.6 per 100K · comp 24

+137.5%

10. North Charleston, SC

4,400/mo · 3,491.9 per 100K · comp 11

+128.0%

Where the signals stack

Underserved + emerging overlap

These cities appear on both the underserved ranking and the strongest-trend ranking. That does not make them guaranteed winners. It does make them the clearest candidates for a deeper market study.

Orlando, FL

33,100/mo · 9,884.9 per 100K · trend +140.3%

Scottsdale, AZ

18,100/mo · 7,352.6 per 100K · trend +137.5%

Florida shows up repeatedly in this section, as do Arizona and inland California. That does not mean the whole Sunbelt is wide open. It means search demand is accelerating faster there than in many colder, slower-growing markets, and that is the sort of early signal traditional market studies can miss if they start from demographics and not intent.

DMA view: the bigger picture

City-level data is best for pinpointing where a local operator might scout next. DMA-level data is better for understanding how entire metro systems compare. New York and Los Angeles still dominate on raw metro demand, but the rank gaps are where the insight lives: Phoenix, Austin, Denver, Dallas-Fort Worth, and Seattle-Tacoma all outperform their DMA size rank.

Vol. Rank	DMA	Monthly Volume	DMA Size Rank	Rank Delta	Avg CPC
1	New York, NY	550,000	1	0	$15.67
2	Los Angeles, CA	450,000	2	0	$17.96
3	San Francisco-Oakland-San Jose, CA	301,000	5	+2	$16.47
4	Chicago, IL	246,000	3	-1	$16.62
5	Dallas-Fort Worth, TX	246,000	8	+3	$18.06
6	Boston, MA	201,000	6	0	$17.88
7	Washington, DC	201,000	7	0	$19.12
8	Houston, TX	201,000	10	+2	$17.10
9	Seattle-Tacoma, WA	201,000	12	+3	$14.28
10	Denver, CO	201,000	16	+6	$17.05
11	Philadelphia, PA	165,000	4	-7	$22.22
12	Atlanta, GA	165,000	9	-3	$20.56
13	Minneapolis-St. Paul, MN	135,000	14	+1	$21.39
14	Austin, TX	135,000	29	+15	$15.72
15	Phoenix, AZ	135,000	50	+35	$21.20
16	Tampa-St. Petersburg, FL	110,000	13	-3	$24.63
17	Orlando-Daytona Beach, FL	110,000	17	0	$21.32
18	Portland, OR	110,000	20	+2	$16.77
19	Detroit, MI	90,500	11	-8	$22.45
20	Miami-Fort Lauderdale, FL	90,500	15	-5	$28.61

Punching above weight

Phoenix, AZ

Size rank 50, volume rank 15, delta +35

135,000/mo · +125.9% trend · $21.20 CPC

Austin, TX

Size rank 29, volume rank 14, delta +15

135,000/mo · +82.4% trend · $15.72 CPC

Denver, CO

Size rank 16, volume rank 10, delta +6

201,000/mo · +70.5% trend · $17.05 CPC

Dallas-Fort Worth, TX

Size rank 8, volume rank 5, delta +3

246,000/mo · +82.3% trend · $18.06 CPC

Seattle-Tacoma, WA

Size rank 12, volume rank 9, delta +3

201,000/mo · +70.5% trend · $14.28 CPC

San Francisco-Oakland-San Jose, CA

Size rank 5, volume rank 3, delta +2

301,000/mo · +96.0% trend · $16.47 CPC

What this means

Search demand is not the final answer. It is the cheapest useful first question.

That is the real takeaway from this project. Search volume cannot tell you rent, labor pressure, parking, drive-thru viability, or whether a neighborhood is already saturated with great independents. It can tell you where people are actively raising their hands.

If you are screening expansion markets, that matters. Large chains pay for location intelligence because intent usually shows up before revenue does. We collected this dataset with Sextaris, which lets you check a keyword across Google Ads geographic units without stitching dozens or hundreds of manual lookups together.

Questions I get about this dataset

Real questions from coffee operators, retail site-selection teams, and local-business researchers.

Why measure "coffee shop near me" instead of asking people directly?+

Survey data is sticky and slow. "Coffee shop near me" is what people type when they actually want coffee right now — Google Ads search volume per market is a direct read of that intent. We measured it across 1,000 US cities so per-capita demand falls out cleanly.

How did you normalize for population?+

Each city volume is divided by 2024 Census population estimates, expressed as searches per 100,000 residents. That removes "Houston is just bigger than Asheville" from the comparison and surfaces actual demand intensity.

What does "demand outpaces supply" actually mean here?+

A city qualifies as underserved when per-capita "coffee shop near me" volume sits well above its DMA median while total establishment count (from Census CBP) sits below. That gap signals an opportunity to open or expand, not just a thirsty population.

Why college towns dominate the leaderboards?+

Students search differently from commuters. College towns concentrate young, mobile-first, third-place-seeking populations — and they tend to have smaller resident bases, which inflates per-capita numbers. Both real and structural; we flag them separately so you can filter.

How current is the volume data?+

Google Ads monthly search volume is pulled in the month before publication. Census population estimates are the latest annual release. Both refresh on different cadences; the article footer records the exact data dates.

Can I get the per-city data?+

The table above lists all 1,000 cities with volume, per-capita rate, DMA, and establishment count. A downloadable CSV is on the roadmap; until then the section is screen-scrape-friendly into Sheets.

Run your own 1,000-city demand map — on your keyword

This workflow was built in Sextaris: one keyword, every US city geo target, population-normalized, in a single pass. One credit, one minute.

See pricing →

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Methodology and limitations

We used the keyword “coffee shop near me” and queried live Google Ads historical metrics across 1,000 US cities matched to Google Ads city geo targets. Population denominators come from the U.S. Census Bureau City and Town Population Totals: 2020-2024 dataset, and map coordinates come from the U.S. Census Gazetteer Files 2024. The working pull for this article was generated on April 10, 2026.

“Volume per 100K” is the central normalization. It converts raw demand into a city-size-adjusted signal. Competition index is an advertiser metric from Google Ads. It is useful, but it is not a direct measure of how many physical coffee shops already exist in a market.

That means this article should be read as a screening tool, not a full market study. It identifies places worth researching further. It does not recommend guaranteed winners, and it absolutely does not replace lease underwriting, trade-area analysis, or local due diligence.

One more caveat: municipal boundaries can distort per-capita readings for cities with unusually small or unusually commercialized boundaries. That is why we include both city-level and DMA-level views. The city cut is ideal for finding spikes. The DMA cut helps put those spikes back into metro context.