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๐ถ 37-year old
๐ณ๏ธโ๐ Progressive
๐ซ Not religious
๐ Single
โ๐ป White
๐ Heterosexual
๐จ โ Man
๐
with a
Bachelor's
๐ป
works as a
Software Dev
๐ก
from
a Home office
๐ฐ
makes
$85,000 / y
โ๏ธ
loves
Coffee
๐ฅฉ eats meat
๐ฅพ
works out by
Hiking
๐ฏ๐ต
loves
Tokyo most
๐
is vaccinated
๐
produces 72% less COโ
4๏ธโฃ
and stays for
4 months
Remote work is now on an exponential trajectory and growing fast. With its growth, hundreds of millions of people who are now newly working remotely from home, a cafe, or coworking space, will realize they've become location independent and travel or move to new places. In this report, we try to figure out who these people are, what work do they do, and how they spend their life based on data from tens of thousands of Nomads.com members.
This page is built LIVE with data pulled straight from the database every day, so it's always up-to-date. Conclusions you can derive from this are always limited and merely indicative but possibly interesting. Nomads.com is a paid membership community, which means there's a selection bias as people who do not or cannot pay are not in the dataset. On the other hand, free digital nomad communities, like on Facebook, require no commitment to join, therefore it's not clear if these people are merely aspirational or active nomads or not. On Nomads.com we can confirm they are active based on their travel logs.
The title of this report is inspired by Buffer's amazing annual remote work report (and used with permission).
You can freely use this page's data, as long as you reference us as "Nomads.com" (with space in between) and use our logo and link back on every data mention! Thanks!. If you like this, also see the live network graph of all travels on Nomads.com and the fastest growing remote work hubs of 2026.
Last updated: 57 minutes ago
๐ถ Nomads by age |
||||
| Age | % | |||
| 21 |
0.1%
|
|||
| 22 |
0.3%
|
|||
| 23 |
0.2%
|
|||
| 24 |
0.4%
|
|||
| 25 |
1%
|
|||
| 26 |
1%
|
|||
| 27 |
1%
|
|||
| 28 |
2%
|
|||
| 29 |
2%
|
|||
| 30 |
2%
|
|||
| 31 |
3%
|
|||
| 32 |
6%
|
|||
| 33 |
7%
|
|||
| 34 |
8%
|
|||
| 35 |
5%
|
|||
| 36 |
6%
|
|||
| 37 |
8%
|
|||
| 38 |
6%
|
|||
| 39 |
5%
|
|||
| 40 |
5%
|
|||
| 41 |
5%
|
|||
| 42 |
4%
|
|||
| 43 |
3%
|
|||
| 44 |
3%
|
|||
| 45 |
2%
|
active last 365d, n=1,011 | ||
โณ๏ธ Nomads by nationality |
||||
| # | Country | People | % | |
| 1 | ๐บ๐ธ United States | 53,104,801 | 43% | |
| 2 | ๐ฌ๐ง United Kingdom | 8,630,448 | 7% | |
| 3 | ๐จ๐ฆ Canada | 5,752,102 | 5% | |
| 4 | ๐ท๐บ Russia | 5,531,750 | 4% | |
| 5 | ๐ฉ๐ช Germany | 5,155,316 | 4% | |
| 6 | ๐ซ๐ท France | 4,351,949 | 3% | |
| 7 | ๐ง๐ท Brazil | 3,319,050 | 3% | |
| 8 | ๐ฆ๐บ Australia | 2,928,844 | 2% | |
| 9 | ๐ณ๐ฑ Netherlands | 2,295,332 | 2% | |
| 10 | ๐ช๐ธ Spain | 2,258,607 | 2% | |
| 11 | ๐ฎ๐ณ India | 2,074,980 | 2% | |
| 12 | ๐ฎ๐น Italy | 1,785,768 | 1% | |
| 13 | ๐บ๐ฆ Ukraine | 1,785,768 | 1% | |
| 14 | ๐ต๐ฑ Poland | 1,501,147 | 1% | |
| 15 | ๐จ๐ญ Switzerland | 1,289,977 | 1% | |
| 16 | ๐ฆ๐น Austria | 950,267 | 1% | |
| 17 | ๐ฏ๐ต Japan | 890,589 | 1% | |
| 18 | ๐ธ๐ช Sweden | 885,998 | 1% | |
| 19 | ๐น๐ท Turkey | 876,817 | 1% | |
| 20 | ๐ฎ๐ช Ireland | 858,454 | 1% | |
| 21 | ๐ฎ๐ฑ Israel | 775,822 | 1% | |
| 22 | ๐ง๐ช Belgium | 743,688 | 1% | |
| 23 | ๐ฐ๐ท South Korea | 720,734 | 1% | |
| 24 | ๐จ๐ฟ Czechia | 706,962 | 1% | |
| 25 | ๐ฟ๐ฆ South Africa | 656,465 | 1% | |
| 26 | ๐ฆ๐ท Argentina | 656,465 | 1% | |
| 27 | ๐ฒ๐ฝ Mexico | 656,465 | 1% | |
| 28 | ๐ต๐น Portugal | 651,874 | 1% | |
| 29 | ๐ท๐ด Romania | 601,377 | 0% | |
| 30 | ๐จ๐ณ China | 569,242 | 0% | n=27,110 |
๐ถ Nomads by gender |
||||
| Gender | % | |||
| ๐จโ Men |
71%
|
|||
| ๐ฑโโ๏ธ Women |
29%
|
|||
| ๐ง Other |
0%
|
active last 365d, n=10,374 | ||
๐ Nomads by sexuality |
||||
| Sexuality | % | |||
| ๐ Heterosexual |
87%
|
|||
| ๐ฆ Bisexual |
8%
|
|||
| ๐ณ๏ธโ๐ Gay or lesbian |
5%
|
n=16,637 | ||
๐ Nomads by beliefs |
||||
| Religion | % | |||
| ๐ซ Not religious |
52%
|
|||
| ๐ Spirituality |
28%
|
|||
| โช๏ธ Christianity |
10%
|
|||
| ๐ Buddhism |
3%
|
|||
| โจ Astrology |
2%
|
|||
| ๐ Islam |
2%
|
|||
| ๐ Judaism |
2%
|
|||
| ๐ Hinduism |
1%
|
|||
| ๐ณ Sikhism |
0%
|
n=8,776 | ||
โ Nomads by ethnicity |
||||
| Ethnicity | % | |||
| โ๐ป White |
59%
|
|||
| โ๐พ Non-white |
41%
|
|||
| ↱โ๐ผ Asian |
14%
|
|||
| ↱โ๐ฝ Latin |
12%
|
|||
| ↱โ๐ฟ Black |
7%
|
|||
| ↱โ๐ฝ Indian |
5%
|
|||
| ↱โ๐พ Middle Eastern |
3%
|
|||
| ↱โ๐ฝ Pacific |
1%
|
n=7,956 | ||
๐ Education |
||||
| Education | % | |||
| ๐ High School |
9%
|
|||
| ๐ Higher education |
91%
|
|||
| ↱๐ Bachelor's |
53%
|
|||
| ↱๐ Master's |
34%
|
|||
| ↱๐ฉโ๐ซ PhD |
3%
|
n=18,231 | ||
โค๏ธ Nomads by relationship |
||||
| Relationship | % | |||
| ๐ Single |
67%
|
|||
| ๐ In a relationship |
33%
|
n=10,104 | ||
๐ Nomads looking for |
||||
| Looking for | % | |||
| ๐ค Friends |
35%
|
|||
| ๐ Travel buddies |
32%
|
|||
| ๐น Casual dating |
15%
|
|||
| โค๏ธ Relationship |
13%
|
|||
| ๐ Poly dating |
4%
|
n=61,208 | ||
๐ฐ Nomads by income |
||||
| Income | % | |||
| < $25k / y |
6%
|
|||
| $25k - $50k / y |
15%
|
|||
| $50k - $100k / y |
33%
|
|||
| $100k - $250k / y |
35%
|
|||
| > $250k - $1M / y |
8%
|
|||
| > $1M / y |
2%
|
|||
| Average | $124,202 / y | |||
| Median | $85,000 / y | n=5,473 | ||
๐ฐ Nomads by employment |
||||
| Employment type | % | |||
| Full time |
37%
|
|||
| Freelance |
18%
|
|||
| Startup founder |
18%
|
|||
| Full time contractor |
9%
|
|||
| Agency |
8%
|
|||
| Other |
6%
|
|||
| Part time |
2%
|
|||
| Part time contractor |
1%
|
n=6,893 | ||
๐ก Where do nomads work from |
||||
| Place | % | |||
| ๐ก Home office |
59%
|
|||
| ๐ฌ Coworking |
15%
|
|||
| โ๏ธ Cafe |
8%
|
|||
| ๐ข Office |
7%
|
|||
| ๐ Couch |
3%
|
|||
| ๐ฝ Dining table |
3%
|
|||
| ๐ Bed |
2%
|
|||
| ๐ช Balcony |
1%
|
|||
| ๐ Van |
1%
|
|||
| ๐ช Kitchen |
0%
|
|||
| ๐ชด Garden |
0%
|
|||
| ๐ฆ Pool |
0%
|
|||
| ๐ฅ Boat |
0%
|
|||
| ๐ Library |
0%
|
n=5,747 | ||
๐ฌ What messaging apps nomads use? |
||||
| Messaging app | % | |||
| Telegram |
50%
|
|||
|
44%
|
||||
| Snapchat |
3%
|
|||
|
2%
|
||||
| LINE |
0%
|
|||
|
0%
|
||||
| Slack |
0%
|
n=5,660 | ||
โ๏ธ Nomad men by politics |
||||
| Politics | % | |||
| ๐ณ๏ธโ๐ Progressive |
45%
|
|||
| โ๏ธ Non-progressive |
55%
|
|||
| ↱๐ฝ Libertarian |
27%
|
|||
| ↱โ๏ธ Centrist |
21%
|
|||
| ↱๐ด Conservative |
7%
|
n=3,632 | ||
โ๏ธ Nomad women by politics |
||||
| Politics | % | |||
| ๐ณ๏ธโ๐ Progressive |
71%
|
|||
| โ๏ธ Non-progressive |
29%
|
|||
| ↱๐ฝ Libertarian |
13%
|
|||
| ↱โ๏ธ Centrist |
12%
|
|||
| ↱๐ด Conservative |
3%
|
n=879 | ||
๐ฅฉ 77% of ๐จโ men eat meat
๐ฅฉ 58% of ๐ฑโโ๏ธwomen eat meat
๐ซ 38% of nomads don't eat meat
๐ฅ 11% are vegetarian
๐ฅ 11% are vegan
๐ 5% are pescetarian
๐ Nomad men by diet |
||||
| Diet | % | |||
| ๐ฅฉ Eats meat |
77%
|
|||
| ๐ซ Does not eat meat |
23%
|
|||
| ↱๐ฅ Vegan |
10%
|
|||
| ↱๐ฅ Vegetarian |
10%
|
|||
| ↱๐ Pescetarian |
4%
|
n=5,724 | ||
๐ Nomad women by diet |
||||
| Diet | % | |||
| ๐ฅฉ Eats meat |
58%
|
|||
| ๐ซ Does not eat meat |
42%
|
|||
| ↱๐ฅ Vegetarian |
18%
|
|||
| ↱๐ฅ Vegan |
14%
|
|||
| ↱๐ Pescetarian |
10%
|
n=1,284 | ||
๐ฅพ Hiking
๐ช Fitness
๐ Running
๐คธโโ๏ธ Yoga
๐ Swimming
๐ด Cycling
๐ Nomad men by sports |
||||
| Sport | % | |||
| ๐ช Fitness |
49%
|
|||
| ๐ฅพ Hiking |
48%
|
|||
| ๐ Running |
29%
|
|||
| ๐ด Cycling |
24%
|
|||
| ๐ Swimming |
23%
|
|||
| ๐คธโโ๏ธ Yoga |
20%
|
|||
| ๐ Surfing |
18%
|
|||
| โฐ Climbing |
15%
|
|||
| ๐ Diving |
15%
|
|||
| ๐ Snowboarding |
15%
|
|||
| โท Skiing |
15%
|
|||
| ๐พ Tennis |
14%
|
|||
| ๐ Motorcycling |
13%
|
|||
| ๐ช Fight sports |
11%
|
|||
| ๐ Table tennis |
9%
|
n=11,046 | ||
๐ Nomad women by sports |
||||
| Sport | % | |||
| ๐ฅพ Hiking |
51%
|
|||
| ๐คธโโ๏ธ Yoga |
44%
|
|||
| ๐ช Fitness |
40%
|
|||
| ๐ Swimming |
24%
|
|||
| ๐ Running |
21%
|
|||
| ๐ด Cycling |
17%
|
|||
| ๐ Diving |
15%
|
|||
| ๐ Surfing |
14%
|
|||
| โฐ Climbing |
13%
|
|||
| โท Skiing |
12%
|
|||
| ๐พ Tennis |
11%
|
|||
| ๐ Snowboarding |
9%
|
|||
| ๐ช Crossfit |
6%
|
|||
| ๐ Motorcycling |
5%
|
|||
| ๐ช Fight sports |
5%
|
n=2,692 | ||
๐ฏ๐ต Tokyo
๐ต๐น Ericeira
๐บ๐ธ Chicago
๐ต๐น Portimรฃo
๐ง๐ฌ Varna
๐ญ๐ท Dubrovnik
๐ Most liked cities by men |
||||
| # | City | Rating | ||
| 1 | ๐ญ๐บ Budapest | 4.55 | ||
| 2 | ๐ฏ๐ต Tokyo | 4.50 | ||
| 3 | ๐ฒ๐ฝ Mexico City | 4.44 | ||
| 4 | ๐บ๐ธ New York City | 4.29 | ||
| 5 | ๐ช๐ธ Madrid | 4.29 | ||
| 6 | ๐จ๐ฟ Prague | 4.29 | ||
| 7 | ๐ฒ๐พ Kuala Lumpur | 4.23 | ||
| 8 | ๐น๐ญ Chiang Mai | 4.23 | ||
| 9 | ๐ฏ๐ต Osaka | 4.17 | ||
| 10 | ๐ฆ๐ช Dubai | 4.17 | ||
| 11 | ๐ธ๐ฌ Singapore | 4.17 | ||
| 12 | ๐ณ๐ฑ Amsterdam | 4.17 | ||
| 13 | ๐ฌ๐น Antigua | 4.17 | ||
| 14 | ๐ง๐ฌ Bansko | 4.17 | ||
| 15 | ๐ฎ๐ฉ Canggu | 4.09 | n=6,802 | |
๐ Most liked cities by women |
||||
| # | City | Rating | ||
| 1 | ๐ฒ๐ฝ Mexico City | 3.33 | n=6,802 | |
๐ Most visited cities |
||||
| # | City | % visited | ||
| 1 | ๐น๐ญ Bangkok | 2.22% | ||
| 2 | ๐ฌ๐ง London | 2.19% | ||
| 3 | ๐บ๐ธ New York City | 1.48% | ||
| 4 | ๐ช๐ธ Barcelona | 1.48% | ||
| 5 | ๐ซ๐ท Paris | 1.46% | ||
| 6 | ๐ฉ๐ช Berlin | 1.44% | ||
| 7 | ๐ต๐น Lisbon | 1.44% | ||
| 8 | ๐ณ๐ฑ Amsterdam | 1.19% | ||
| 9 | ๐บ๐ธ San Francisco | 1.14% | ||
| 10 | ๐น๐ญ Chiang Mai | 1.08% | ||
| 11 | ๐ฒ๐ฝ Mexico City | 0.99% | ||
| 12 | ๐ฏ๐ต Tokyo | 0.92% | ||
| 13 | ๐ฎ๐ฉ Canggu | 0.91% | ||
| 14 | ๐ธ๐ฌ Singapore | 0.9% | ||
| 15 | ๐น๐ท Istanbul | 0.86% | ||
| 16 | ๐ช๐ธ Madrid | 0.83% | ||
| 17 | ๐ฒ๐พ Kuala Lumpur | 0.82% | ||
| 18 | ๐บ๐ธ Los Angeles | 0.81% | ||
| 19 | ๐ฆ๐ช Dubai | 0.79% | ||
| 20 | ๐ญ๐บ Budapest | 0.77% | ||
| 21 | ๐จ๐ฟ Prague | 0.71% | ||
| 22 | ๐ฆ๐ท Buenos Aires | 0.7% | ||
| 23 | ๐จ๐ด Medellรญn | 0.63% | ||
| 24 | ๐ฎ๐น Rome | 0.6% | ||
| 25 | ๐ท๐บ Moscow | 0.6% | ||
| 26 | ๐ฆ๐น Vienna | 0.58% | ||
| 27 | ๐ฐ๐ท Seoul | 0.55% | ||
| 28 | ๐ป๐ณ Ho Chi Minh City | 0.55% | ||
| 29 | ๐ญ๐ฐ Hong Kong | 0.54% | ||
| 30 | ๐น๐ญ Phuket | 0.53% | n=413,256 | |
๐ Most visited countries |
||||
| # | Country | % visited | ||
| 1 | ๐บ๐ธ United States | 13% | ||
| 2 | ๐น๐ญ Thailand | 5% | ||
| 3 | ๐ช๐ธ Spain | 5% | ||
| 4 | ๐ฌ๐ง United Kingdom | 4% | ||
| 5 | ๐ฉ๐ช Germany | 4% | ||
| 6 | ๐ฒ๐ฝ Mexico | 3% | ||
| 7 | ๐ซ๐ท France | 3% | ||
| 8 | ๐ฎ๐น Italy | 3% | ||
| 9 | ๐ต๐น Portugal | 3% | ||
| 10 | ๐ฎ๐ฉ Indonesia | 2% | ||
| 11 | ๐ง๐ท Brazil | 2% | ||
| 12 | ๐ฏ๐ต Japan | 2% | ||
| 13 | ๐จ๐ฆ Canada | 2% | ||
| 14 | ๐ณ๐ฑ Netherlands | 2% | ||
| 15 | ๐ป๐ณ Vietnam | 2% | ||
| 16 | ๐ท๐บ Russia | 2% | ||
| 17 | ๐น๐ท Turkey | 2% | ||
| 18 | ๐จ๐ด Colombia | 1% | ||
| 19 | ๐ต๐ฑ Poland | 1% | ||
| 20 | ๐ฒ๐พ Malaysia | 1% | ||
| 21 | ๐ฆ๐บ Australia | 1% | ||
| 22 | ๐ฎ๐ณ India | 1% | ||
| 23 | ๐ฌ๐ท Greece | 1% | ||
| 24 | ๐ฆ๐ท Argentina | 1% | ||
| 25 | ๐จ๐ญ Switzerland | 1% | ||
| 26 | ๐ฆ๐น Austria | 1% | ||
| 27 | ๐จ๐ณ China | 1% | ||
| 28 | ๐ฆ๐ช United Arab Emirates | 1% | ||
| 29 | ๐ธ๐ฌ Singapore | 1% | ||
| 30 | ๐ญ๐ท Croatia | 1% | n=413,256 | |
๐ Avg. COโ by member traveling |
||||
| Year | COโ | |||
| 2013 |
694 kg/y
|
|||
| 2014 |
986 kg/y
|
|||
| 2015 |
1,080 kg/y
|
|||
| 2016 |
1,288 kg/y
|
|||
| 2017 |
1,472 kg/y
|
|||
| 2018 |
1,551 kg/y
|
|||
| 2019 |
1,587 kg/y
|
|||
| 2020 |
1,004 kg/y
|
|||
| 2021 |
1,004 kg/y
|
|||
| 2022 |
1,575 kg/y
|
|||
| 2023 |
1,746 kg/y
|
|||
| 2024 |
1,717 kg/y
|
|||
| 2025 |
1,596 kg/y
|
|||
| 2026 |
2,515 kg/y
|
|||
| Average | 1,290 kg/y | |||
| Median | 1,379 kg/y |
Based on 413,256 trips by 15,781 members @ 115g/km COโ emitted. An average American spends ~5,000kg/y on commuting by car and flying. We'd assume nomads travel more internationally but on the other hand they don't commute to work since they work 100% remotely. Many walk to work or work from their home, hotel or Airbnb. That means on average nomads generate 1,379 kg/y, or 72% less COโ than the average American on travel and commuting. |
||
๐จ Where men go most |
||||
| # | Tag | vs. ๐ฑโโ๏ธ | ||
| 1 | ๐น๐ญ Bangkok | +22% | ||
| 2 | ๐ต๐น Lisbon | -16% | ||
| 3 | ๐ช๐ธ Barcelona | -10% | ||
| 4 | ๐ฌ๐ง London | -22% | ||
| 5 | ๐ซ๐ท Paris | -22% | ||
| 6 | ๐น๐ญ Chiang Mai | -3% | ||
| 7 | ๐ณ๐ฑ Amsterdam | +4% | ||
| 8 | ๐ฉ๐ช Berlin | -3% | ||
| 9 | ๐ฎ๐ฉ Canggu | 0% | ||
| 10 | ๐ฏ๐ต Tokyo | +14% | ||
| 11 | ๐น๐ท Istanbul | +7% | ||
| 12 | ๐ธ๐ฌ Singapore | +13% | ||
| 13 | ๐ฒ๐พ Kuala Lumpur | +27% | ||
| 14 | ๐ฒ๐ฝ Mexico City | -20% | ||
| 15 | ๐ญ๐บ Budapest | +18% | median temp=18°C; n=413,256 | |
๐ฑโโ๏ธ Where women go most |
||||
| # | Tag | vs. ๐จ | ||
| 1 | ๐ต๐น Lisbon | +19% | ||
| 2 | ๐ฌ๐ง London | +28% | ||
| 3 | ๐น๐ญ Bangkok | -18% | ||
| 4 | ๐ช๐ธ Barcelona | +12% | ||
| 5 | ๐ซ๐ท Paris | +28% | ||
| 6 | ๐น๐ญ Chiang Mai | +3% | ||
| 7 | ๐ฒ๐ฝ Mexico City | +25% | ||
| 8 | ๐ฉ๐ช Berlin | +3% | ||
| 9 | ๐ณ๐ฑ Amsterdam | -4% | ||
| 10 | ๐ฎ๐ฉ Canggu | +0% | ||
| 11 | ๐ฎ๐น Rome | +27% | ||
| 12 | ๐น๐ท Istanbul | -7% | ||
| 13 | ๐ฏ๐ต Tokyo | -12% | ||
| 14 | ๐ธ๐ฌ Singapore | -11% | ||
| 15 | ๐ฎ๐ฉ Ubud | +28% | median temp=18°C; n=413,256 | |
๐จ Where men go more |
||||
| # | Tag | vs. women | ||
| 1 | ๐ท๐บ Russia | +79% | ||
| 2 | ๐ต๐ฑ Poland | +69% | ||
| 3 | ๐ท๐ด Romania | +59% | ||
| 4 | ๐ฌ๐ช Georgia | +41% | ||
| 5 | ๐ญ๐ฐ Hong Kong | +32% | ||
| 6 | ๐ต๐ญ Philippines | +28% | ||
| 7 | ๐จ๐ณ China | +27% | ||
| 8 | ๐ท๐ธ Serbia | +26% | ||
| 9 | ๐ฆ๐ช United Arab Emirates | +26% | ||
| 10 | ๐จ๐ฟ Czechia | +23% | ||
| 11 | ๐ฏ๐ต Japan | +20% | ||
| 12 | ๐ป๐ณ Vietnam | +19% | ||
| 13 | ๐ญ๐บ Hungary | +19% | ||
| 14 | ๐ณ๐ด Norway | +18% | ||
| 15 | ๐ฒ๐พ Malaysia | +17% | median temp=13°C; n=413,256 | |
๐ฑโโ๏ธ Where women go more |
||||
| # | Tag | vs. men | ||
| 1 | ๐ฟ๐ฆ South Africa | +50% | ||
| 2 | ๐จ๐ท Costa Rica | +46% | ||
| 3 | ๐ฒ๐ฝ Mexico | +38% | ||
| 4 | ๐ฌ๐ง United Kingdom | +29% | ||
| 5 | ๐ญ๐ท Croatia | +23% | ||
| 6 | ๐ซ๐ท France | +21% | ||
| 7 | ๐จ๐ฑ Chile | +20% | ||
| 8 | ๐ฎ๐น Italy | +20% | ||
| 9 | ๐ฌ๐ท Greece | +14% | ||
| 10 | ๐ต๐น Portugal | +12% | ||
| 11 | ๐ฆ๐บ Australia | +10% | ||
| 12 | ๐ฎ๐ช Ireland | +10% | ||
| 13 | ๐ช๐ธ Spain | +8% | ||
| 14 | ๐บ๐ธ United States | +8% | ||
| 15 | ๐ต๐ช Peru | +7% | median temp=18°C; n=413,256 | |
๐ Most liked countries |
||||
| # | Country | Rating | ||
| 1 | ๐ฏ๐ต Japan | 4.8 | ||
| 2 | ๐ญ๐บ Hungary | 4.7 | ||
| 3 | ๐ญ๐ท Croatia | 4.6 | ||
| 4 | ๐จ๐ฟ Czechia | 4.55 | ||
| 5 | ๐ฑ๐ป Latvia | 4.5 | ||
| 6 | ๐ต๐ฑ Poland | 4.45 | ||
| 7 | ๐ฐ๐ท South Korea | 4.4 | ||
| 8 | ๐จ๐ญ Switzerland | 4.35 | ||
| 9 | ๐ญ๐ฐ Hong Kong | 4.3 | ||
| 10 | ๐ฐ๐ฟ Kazakhstan | 4.3 | ||
| 11 | ๐ฌ๐น Guatemala | 4.3 | ||
| 12 | ๐ฟ๐ฆ South Africa | 4.25 | ||
| 13 | ๐ช๐ช Estonia | 4.25 | ||
| 14 | ๐ฑ๐น Lithuania | 4.25 | ||
| 15 | ๐ฌ๐ท Greece | 4.2 | n=4,044 | |
๐คฎ Least liked countries |
||||
| # | Country | Rating | ||
| 1 | ๐จ๐บ Cuba | 1 | ||
| 2 | ๐ฎ๐ท Iran | 1.65 | ||
| 3 | ๐ฌ๐ฎ Gibraltar | 1.65 | ||
| 4 | ๐ญ๐ณ Honduras | 1.65 | ||
| 5 | ๐จ๐พ Cyprus | 1.65 | ||
| 6 | ๐ฒ๐น Malta | 2.15 | ||
| 7 | ๐จ๐ฑ Chile | 2.25 | ||
| 8 | ๐ฑ๐ฐ Sri Lanka | 2.35 | ||
| 9 | ๐ธ๐ด Somalia | 2.5 | ||
| 10 | ๐ช๐น Ethiopia | 2.5 | ||
| 11 | ๐น๐ฟ Tanzania | 2.5 | ||
| 12 | ๐ง๐ง Barbados | 2.5 | ||
| 13 | ๐ฒ๐ณ Mongolia | 2.5 | ||
| 14 | ๐ธ๐ณ Senegal | 2.5 | ||
| 15 | ๐ป๐ช Venezuela | 2.5 | n=4,044 | |
โฐ How long do nomads stay in one city? |
||||
| Duration | % | |||
| < 7 days |
47%
|
|||
| 7 - 30 days |
33%
|
|||
| 30 - 90 days |
14%
|
|||
| 90+ days |
6%
|
|||
| Average | 63 days (2 months) | |||
| Median | 7 days | n=402,778 | ||
๐ก How long do nomads stay in one country? |
||||
| Duration | % | |||
| < 7 days |
0%
|
|||
| 7 - 30 days |
59%
|
|||
| 30 - 90 days |
28%
|
|||
| 90+ days |
14%
|
|||
| Average | 130 days (4 months) | n=402,778 | ||
๐ป Software Dev
๐ Startup Founder
๐ธ Web Dev
๐ Marketing
๐ฉโ๐จ Creative
๐ SaaS
๐จ Nomad men work as |
||||
| # | Work | % | vs. women | |
| 1 | ๐ป Software Dev | 34% | +305% | |
| 2 | ๐ธ Web Dev | 27% | +326% | |
| 3 | ๐ Startup Founder | 27% | +164% | |
| 4 | ๐ Marketing | 15% | +14% | |
| 5 | ๐ SaaS | 13% | +241% | |
| 6 | ๐ฉโ๐จ Creative | 12% | -6% | |
| 7 | ๐จ UI/UX Design | 11% | +60% | |
| 8 | ๐ค Product Manager | 11% | +100% | |
| 9 | ๐ฑ Mobile Dev | 10% | +418% | |
| 10 | ๐ฐ Crypto | 10% | +324% | |
| 11 | ๐ Data | 10% | +133% | |
| 12 | ๐ฐ Finance | 10% | +159% | |
| 13 | ๐ Ecommerce | 8% | +141% | |
| 14 | ๐ค Sales | 7% | +107% | |
| 15 | ๐จโ๐ซ Education | 6% | -2% | n=21,906 |
๐ฑโโ๏ธ Nomad women work as |
||||
| # | Work | % | vs. men | |
| 1 | ๐ Marketing | 13% | -12% | |
| 2 | ๐ฉโ๐จ Creative | 13% | +6% | |
| 3 | ๐ Startup Founder | 10% | -62% | |
| 4 | ๐ป Software Dev | 8% | -75% | |
| 5 | ๐จ UI/UX Design | 7% | -37% | |
| 6 | ๐ค Community | 7% | +10% | |
| 7 | ๐ธ Web Dev | 6% | -77% | |
| 8 | ๐จโ๐ซ Education | 6% | +2% | |
| 9 | ๐ Blogging | 6% | +5% | |
| 10 | ๐ Coach | 6% | +6% | |
| 11 | ๐ค Product Manager | 5% | -50% | |
| 12 | ๐ Data | 4% | -57% | |
| 13 | ๐ SaaS | 4% | -71% | |
| 14 | ๐ฐ Finance | 4% | -61% | |
| 15 | ๐ค Sales | 4% | -52% | n=7,772 |
๐จ Nomad men vs. women |
||||
| # | Tag | vs. women | ||
| 1 | ๐ก Sysadmin | +452% | ||
| 2 | ๐ Dev Ops | +429% | ||
| 3 | ๐ฑ Mobile Dev | +418% | ||
| 4 | ๐พ Game Dev | +386% | ||
| 5 | ๐ค AI model | +385% | ||
| 6 | ๐ธ Web Dev | +326% | ||
| 7 | ๐ฐ Crypto | +324% | ||
| 8 | ๐ป Software Dev | +305% | ||
| 9 | ๐ก๏ธ InfoSec | +285% | ||
| 10 | ๐ OF | +273% | ||
| 11 | ๐ Engineering | +243% | ||
| 12 | ๐ SaaS | +241% | ||
| 13 | ๐ VR Dev | +229% | ||
| 14 | ๐ Investor | +213% | ||
| 15 | ๐ Sports | +174% | n=27,841 | |
๐ฑโโ๏ธ Nomad women vs. men |
||||
| # | Tag | vs. men | ||
| 1 | ๐ธ House wife | +182% | ||
| 2 | ๐ Tradwife | +182% | ||
| 3 | ๐จ Artist | +59% | ||
| 4 | ๐งโ๐ผ Human resources | +55% | ||
| 5 | ๐น Content Creator | +48% | ||
| 6 | ๐ Student | +41% | ||
| 7 | โ๏ธ Aviation | +41% | ||
| 8 | ๐ง Psychologist | +32% | ||
| 9 | ๐ฐ Journalism | +31% | ||
| 10 | ๐ Support | +23% | ||
| 11 | ๐จโโ๏ธ Medical | +18% | ||
| 12 | ๐ Hospitality | +15% | ||
| 13 | ๐ณ Chef | +13% | ||
| 14 | ๐ค Community | +10% | ||
| 15 | ๐ฉโ๐จ Creative | +6% | n=27,841 | |
โ๏ธ Coffee
๐ฌ๐ง Speaks English
๐ Optimist
โฐ Outdoors
๐ COVID vaccinated
๐ฅพ Hiking
๐จโ Nomad men |
||||
| # | Tag | % | vs. ๐ฑโโ๏ธ | |
| 1 | โ๏ธ Coffee | 38% | +49% | |
| 2 | ๐ฌ๐ง Speaks English | 32% | +43% | |
| 3 | ๐ Optimist | 31% | +52% | |
| 4 | ๐ช Fitness | 26% | +75% | |
| 5 | ๐ COVID vaccinated | 26% | +41% | |
| 6 | โฐ Outdoors | 25% | +25% | |
| 7 | ๐ฅพ Hiking | 25% | +37% | |
| 8 | ๐ถ Dogs | 25% | +27% | |
| 9 | โ๏ธ Waking up early | 24% | +49% | |
| 10 | ๐ง Open-minded | 24% | +42% | |
| 11 | ๐บ Beer | 23% | +165% | |
| 12 | ๐ Single | 23% | +55% | |
| 13 | ๐ Staying up late | 23% | +81% | |
| 14 | ๐ Reading | 22% | +28% | |
| 15 | ๐ท Wine | 22% | +18% | n=21,906 |
๐ฑโโ๏ธ Nomad women |
||||
| # | Tag | % | vs. ๐จโ | |
| 1 | โ๏ธ Coffee | 26% | -33% | |
| 2 | ๐ฌ๐ง Speaks English | 22% | -30% | |
| 3 | โฐ Outdoors | 20% | -20% | |
| 4 | ๐ Optimist | 20% | -34% | |
| 5 | ๐ถ Dogs | 20% | -21% | |
| 6 | ๐ท Wine | 18% | -16% | |
| 7 | ๐ฅพ Hiking | 18% | -27% | |
| 8 | ๐ COVID vaccinated | 18% | -29% | |
| 9 | ๐ Reading | 18% | -22% | |
| 10 | ๐ต Tea | 17% | -15% | |
| 11 | ๐ง Open-minded | 17% | -30% | |
| 12 | ๐คธโโ๏ธ Yoga | 16% | +48% | |
| 13 | โ๏ธ Waking up early | 16% | -33% | |
| 14 | ๐ Single | 15% | -36% | |
| 15 | ๐ช Fitness | 15% | -43% | n=7,772 |
๐จ Nomad men vs. women |
||||
| # | Tag | vs. ๐ฑโโ๏ธ | ||
| 1 | ๐ง Have a beard | +1,925% | ||
| 2 | ๐จ No beard | +484% | ||
| 3 | โฝ๏ธ Football | +428% | ||
| 4 | ๐งโ Short hair | +336% | ||
| 5 | ๐ Ice hockey | +321% | ||
| 6 | ๐ช Dropout | +284% | ||
| 7 | ๐ Motorcycling | +274% | ||
| 8 | ๐ Race sports | +264% | ||
| 9 | ๐ Basketball | +255% | ||
| 10 | ๐ Table tennis | +237% | ||
| 11 | โ๏ธ Chess | +237% | ||
| 12 | ๐ช Fight sports | +235% | ||
| 13 | ๐ Hindu | +227% | ||
| 14 | ๐ด Conservative politics | +222% | ||
| 15 | ๐ง Hardstyle music | +216% | n=27,841 | |
๐ฑโโ๏ธ Nomad women vs. men |
||||
| # | Tag | vs. ๐จ | ||
| 1 | ๐ Makeup | +2,901% | ||
| 2 | ๐ฑโโ๏ธ Long hair | +256% | ||
| 3 | ๐ Dress up | +185% | ||
| 4 | โจ Astrology | +176% | ||
| 5 | ๐ช Feminism | +158% | ||
| 6 | ๐ฆพ Disabled | +123% | ||
| 7 | ๐งโ๐จ Interior design | +119% | ||
| 8 | โจ Believe in astrology | +106% | ||
| 9 | ๐จ Drawing | +75% | ||
| 10 | ๐ฅ Red hair | +72% | ||
| 11 | ๐ Dancing | +62% | ||
| 12 | ๐ถ Pottery | +61% | ||
| 13 | ๐ Shopping | +59% | ||
| 14 | ๐ป Gardening | +54% | ||
| 15 | ๐คธโโ๏ธ Yoga | +48% | n=27,841 | |
๐ Nomads by vaccination |
||||
| Vaccinated | % | |||
| ๐ COVID vaccinated |
92%
|
|||
| ๐ Not COVID vaccinated |
8%
|
n=8,298 | ||
โค๏ธ Nomads by family |
||||
| Relationship | % | |||
| โค๏ธ Close to parents |
82%
|
|||
| ๐ Not close to parents |
18%
|
n=2,398 | ||
๐ถ Nomads by childhood |
||||
| Childhood | % | |||
| ๐ Happy childhood |
89%
|
|||
| ๐ Unhappy childhood |
11%
|
n=2,582 | ||
๐ก Homeownership amongst nomads |
||||
| Homeownership | % | |||
| ๐ก Homeowner |
55%
|
|||
| ๐ก Not a homeowner |
45%
|
n=2,763 | ||
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. It does not show any of these traits in their profile when they rate them. People who are rated as attractive based on their photo are more likely to have these traits. TL;DR hot people have specific traits, but those specific traits don't necessarily make you hot (you could always try though).
๐ My parents separated
๐ง Only child
๐ In a relationship
๐ Volleyball
๐ Running
๐จโ Most attractive men's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ In a relationship | +130% | ||
| 2 | ๐ธ Padel | +80% | ||
| 3 | ๐ก Homeowner | +64% | ||
| 4 | โจ Believe in astrology | +63% | ||
| 5 | ๐ Not COVID vaccinated | +59% | ||
| 6 | ๐ฅ Soft boiled eggs | +59% | ||
| 7 | ๐ง Hiphop music | +58% | ||
| 8 | ๐ถ Parent | +58% | ||
| 9 | ๐ฌ ๐ | +53% | ||
| 10 | ๐ Basketball | +53% | ||
| 11 | ๐ Rugby | +53% | ||
| 12 | ๐ Skateboarding | +49% | ||
| 13 | ๐ Free diving | +48% | ||
| 14 | ๐ฑโโ๏ธ Long hair | +46% | ||
| 15 | ๐ฅ Messy | +45% | ||
| 16 | ๐ก Not a homeowner | +44% | ||
| 17 | ๐ฌ Slack | +44% | ||
| 18 | ๐ฏ๐ฒ Reggae music | +41% | ||
| 19 | ๐ช Crossfit | +41% | ||
| 20 | ๐ COVID vaccinated | +41% | ||
| 21 | ๐ Massage | +41% | ||
| 22 | ๐ง Dubstep music | +40% | ||
| 23 | ๐ Kitesurfing | +39% | ||
| 24 | โค๏ธ Happy childhood | +39% | ||
| 25 | ๐ง House music | +38% | ||
| 26 | ๐งโ Short hair | +38% | ||
| 27 | ๐ Carnivore | +37% | ||
| 28 | ๐ iPhone | +37% | ||
| 29 | โฝ๏ธ Football | +37% | ||
| 30 | ๐ธ Badminton | +36% | n=27,841 | |
๐ฑโโ๏ธ Most attractive women's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ My parents separated | +348% | ||
| 2 | ๐ง Only child | +311% | ||
| 3 | ๐ Volleyball | +297% | ||
| 4 | ๐ Shopping | +254% | ||
| 5 | ๐งผ Clean freak | +235% | ||
| 6 | ๐ Running | +235% | ||
| 7 | ๐พ Tennis | +226% | ||
| 8 | ๐ Table tennis | +214% | ||
| 9 | ๐ In a relationship | +208% | ||
| 10 | โท Skiing | +203% | ||
| 11 | ๐ฌ Social smoker | +199% | ||
| 12 | ๐ Surfing | +185% | ||
| 13 | ๐จโ๐ค Partying | +184% | ||
| 14 | ๐ด Cycling | +183% | ||
| 15 | ๐ Pescetarian | +183% | ||
| 16 | ๐ Makeup | +165% | ||
| 17 | ๐ Motorcycling | +164% | ||
| 18 | ๐บ Beer | +164% | ||
| 19 | ๐ฅ Hard boiled eggs | +163% | ||
| 20 | ๐ Swimming | +155% | ||
| 21 | ๐ฅ Vegan | +151% | ||
| 22 | โฑ Beach | +151% | ||
| 23 | ๐ฑโโ๏ธ Long hair | +151% | ||
| 24 | โจ Astrology | +150% | ||
| 25 | โฐ Climbing | +150% | ||
| 26 | โฝ๏ธ Football | +149% | ||
| 27 | ๐ Staying up late | +147% | ||
| 28 | ๐ Film making | +145% | ||
| 29 | ๐ซ Not religious | +145% | ||
| 30 | ๐ท Blues music | +141% | n=27,841 | |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific traits. It's that people who are rated as unattractive are more likely to have selected these traits on their profile. TL;DR unattractive people have specific traits, but those specific traits don't necessarily make you unattractive.
๐ FetLife
๐ฒ Board games
๐ฆ Sparkling water
๐งฌ Longevity
๐ Creatine
๐ณ Bowling
๐จโ Most unattractive men's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ FetLife | -2,501% | ||
| 2 | ๐ฒ Board games | -1,239% | ||
| 3 | ๐งฌ Longevity | -1,009% | ||
| 4 | ๐ฆ Sparkling water | -971% | ||
| 5 | ๐ Creatine | -894% | ||
| 6 | ๐ณ Bowling | -891% | ||
| 7 | ๐ฌ TikTok | -741% | ||
| 8 | ๐ณ๏ธโ๐ LGBTQ+ | -665% | ||
| 9 | ๐๏ธ Live in the mountains | -627% | ||
| 10 | ๐ Makeup | -550% | ||
| 11 | ๐ช Skydiving | -246% | ||
| 12 | ๐งโ๐จ Interior design | -244% | ||
| 13 | ๐ญ Acting | -244% | ||
| 14 | ๐ถ Pottery | -168% | ||
| 15 | ๐ช Paragliding | -141% | ||
| 16 | ๐ก Architecture | -137% | ||
| 17 | ๐ฐ๐ท K-pop music | -129% | ||
| 18 | ๐คฟ Snorkeling | -119% | ||
| 19 | ๐ง Garage music | -112% | ||
| 20 | ๐๏ธ Live near the beach | -76% | ||
| 21 | ๐ง Trance music | -73% | ||
| 22 | ๐ถโ๐ซ๏ธ Hang gliding | -72% | ||
| 23 | ๐ Single | -61% | ||
| 24 | ๐ Urbex | -56% | ||
| 25 | ๐ Cricket | -53% | ||
| 26 | ๐ฑ Pool | -52% | ||
| 27 | ๐ธ Anime | -43% | ||
| 28 | ๐ Religious | -42% | ||
| 29 | ๐ฆ Still water | -42% | ||
| 30 | โพ๏ธ Baseball | -40% | n=27,841 | |
๐ฑโโ๏ธ Most unattractive women's traits |
||||
| # | Tag | Diff | ||
| 1 | ๐ฅ Messy | -1,712% | ||
| 2 | ๐ง Pessimist | -806% | ||
| 3 | ๐ฌ Daily smoker | -762% | ||
| 4 | ๐ง Bouldering | -541% | ||
| 5 | ๐ด Conservative politics | -497% | ||
| 6 | ๐ฌ Snapchat | -298% | ||
| 7 | ๐ถโ๐ซ๏ธ Hang gliding | -165% | ||
| 8 | ๐๏ธ Live near the beach | -165% | ||
| 9 | ๐ฆ Still water | -121% | ||
| 10 | ๐คธโโ๏ธ Pilates | -121% | ||
| 11 | ๐ณ๏ธโ๐ LGBTQ+ | -121% | ||
| 12 | ๐ FetLife | -99% | ||
| 13 | ๐ฆ Sparkling water | -99% | ||
| 14 | ๐ฒ Board games | -77% | ||
| 15 | โจ Believe in astrology | -63% | ||
| 16 | ๐ก Not a homeowner | -56% | ||
| 17 | ๐ Bodyboarding | -55% | ||
| 18 | ๐ค Podcast | -55% | ||
| 19 | ๐ Kitesurfing | -22% | ||
| 20 | ๐ Carnivore | -20% | ||
| 21 | โค๏ธ Happy childhood | -12% | ||
| 22 | ๐ธ Anime | -8% | ||
| 23 | ๐ง Garage music | -6% | ||
| 24 | ๐ธ Badminton | -2% | n=27,841 | |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific jobs. It's that people who are rated as attractive are more likely to work in speciifc industries. TL;DR hot people work in specific industries, but those specific industries don't necessarily make you hot (you could always try though).
๐ Recruitment
๐ฑ Mobile Dev
๐ Coach
๐ค Community
๐ SaaS
๐จ UI/UX Design
๐จโ Attractive men's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐จโโ๏ธ Medical | +69% | ||
| 2 | ๐ Recruitment | +50% | ||
| 3 | ๐จ UI/UX Design | +40% | ||
| 4 | ๐ SaaS | +40% | ||
| 5 | ๐ Coach | +40% | ||
| 6 | ๐ค Product Manager | +39% | ||
| 7 | ๐ Logistics | +34% | ||
| 8 | ๐ Ecommerce | +29% | ||
| 9 | ๐ Dev Ops | +29% | ||
| 10 | ๐ง Psychologist | +28% | ||
| 11 | ๐ฑ Mobile Dev | +25% | ||
| 12 | ๐ Startup Founder | +24% | ||
| 13 | ๐ Marketing | +23% | ||
| 14 | ๐ Data | +20% | ||
| 15 | ๐ธ Model | +17% | ||
| 16 | ๐ค Sales | +17% | ||
| 17 | ๐ป Software Dev | +17% | ||
| 18 | ๐พ Game Dev | +15% | ||
| 19 | ๐ช Fitness | +12% | ||
| 20 | ๐ VR Dev | +9% | ||
| 21 | ๐ธ Web Dev | +8% | ||
| 22 | ๐ Blogging | +7% | ||
| 23 | ๐ก Sysadmin | +7% | ||
| 24 | ๐จโ๐ซ Education | +6% | ||
| 25 | ๐ค Community | +6% | ||
| 26 | ๐ฐ Finance | +5% | n=27,841 | |
๐ฑโโ๏ธ Attractive women's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ Recruitment | +183% | ||
| 2 | ๐ฑ Mobile Dev | +177% | ||
| 3 | ๐ค Community | +133% | ||
| 4 | ๐ Coach | +110% | ||
| 5 | ๐ฐ Journalism | +106% | ||
| 6 | ๐ฉโ๐จ Creative | +100% | ||
| 7 | ๐ Blogging | +99% | ||
| 8 | ๐ SaaS | +89% | ||
| 9 | ๐ฐ Finance | +80% | ||
| 10 | ๐จ UI/UX Design | +77% | ||
| 11 | ๐ป Software Dev | +75% | ||
| 12 | ๐ Startup Founder | +73% | ||
| 13 | ๐จโ๐ซ Education | +67% | ||
| 14 | ๐ Marketing | +61% | ||
| 15 | ๐ Ecommerce | +57% | ||
| 16 | ๐ค Product Manager | +47% | ||
| 17 | ๐ธ Web Dev | +13% | ||
| 18 | ๐ Data | +9% | n=27,841 | |
Attractiveness is based on the proportion of people liking or disliking a person based on their photo on Nomads.com's dating app. That does NOT mean people like or dislike specific jobs. It's that people who are rated as unattractive are more likely to have selected these jobs on their profile. TL;DR unattractive people have specific jobs, but those specific jobs don't necessarily make you unattractive.
๐ฉ Politics
๐ Real estate
๐จ Artist
๐ฌ Science
๐ฅ Healthcare
๐น Content Creator
๐จโ Most unattractive men's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ Real estate | -1,047% | ||
| 2 | ๐จ Artist | -780% | ||
| 3 | ๐ฌ Science | -512% | ||
| 4 | ๐ฅ Healthcare | -474% | ||
| 5 | ๐ Student | -359% | ||
| 6 | ๐พ Farm life | -168% | ||
| 7 | ๐ฉ Politics | -167% | ||
| 8 | ๐ฉโ๐ผ Law | -143% | ||
| 9 | ๐ฐ Journalism | -64% | ||
| 10 | ๐ค AI model | -53% | ||
| 11 | ๐น Content Creator | -42% | ||
| 12 | ๐ก Architecture | -37% | ||
| 13 | ๐ถ Adult | -36% | ||
| 14 | ๐ Hospitality | -22% | ||
| 15 | ๐ Support | -15% | ||
| 16 | ๐บ Geo | -15% | ||
| 17 | ๐ฉโ๐จ Creative | -5% | ||
| 18 | ๐ Sports | -4% | n=27,841 | |
๐ฑโโ๏ธ Most unattractive women's jobs |
||||
| # | Tag | Diff | ||
| 1 | ๐ฉ Politics | -1,093% | ||
| 2 | ๐ VR Dev | -497% | ||
| 3 | ๐ค Consulting | -497% | ||
| 4 | ๐น Content Creator | -342% | ||
| 5 | ๐จ Artist | -187% | ||
| 6 | ๐ Hospitality | -90% | ||
| 7 | ๐ Real estate | -77% | ||
| 8 | ๐ก๏ธ InfoSec | -55% | ||
| 9 | ๐ Support | -6% | ||
| 10 | ๐ฐ Crypto | -2% | n=27,841 | |
๐จโ Where attractive men travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐ฌ๐ท Mykonos | 5 | ||
| 2 | ๐ฎ๐ฉ Uluwatu | 4.97 | ||
| 3 | ๐ต๐น Ericeira | 4.97 | ||
| 4 | ๐ฆ๐บ Brisbane | 4.97 | ||
| 5 | ๐ธ๐ช Malmรถ | 4.97 | ||
| 6 | ๐ณ๐ฟ Christchurch | 4.91 | ||
| 7 | ๐ช๐ธ Ibiza | 4.9 | ||
| 8 | ๐จ๐ท Tamarindo | 4.89 | ||
| 9 | ๐ฒ๐ฝ Cabo San Lucas | 4.84 | ||
| 10 | ๐บ๐ธ Boston | 4.79 | ||
| 11 | ๐ฉ๐ช Stuttgart | 4.78 | ||
| 12 | ๐ณ๐ฟ Queenstown | 4.75 | ||
| 13 | ๐ณ๐ด Bergen | 4.75 | ||
| 14 | ๐ญ๐ท Zadar | 4.73 | ||
| 15 | ๐ช๐ธ Mallorca | 4.7 | ||
| 16 | ๐ต๐น Portimรฃo | 4.7 | ||
| 17 | ๐ฆ๐บ Melbourne | 4.69 | ||
| 18 | ๐ง๐ช Antwerp | 4.69 | ||
| 19 | ๐ต๐น Faro | 4.68 | ||
| 20 | ๐ณ๐ฟ Auckland | 4.68 | ||
| 21 | ๐น๐ญ Ko Lanta | 4.66 | ||
| 22 | ๐ฒ๐ฆ Marrakesh | 4.66 | ||
| 23 | ๐ฎ๐ธ Reykjavik | 4.66 | ||
| 24 | ๐ง๐ฆ Sarajevo | 4.66 | ||
| 25 | ๐ฒ๐น Sliema | 4.66 | ||
| 26 | ๐ฒ๐ฆ Fes | 4.63 | ||
| 27 | ๐ง๐ช Bruges | 4.62 | ||
| 28 | ๐ฌ๐ง Manchester | 4.61 | ||
| 29 | ๐ฎ๐น Catania | 4.61 | ||
| 30 | ๐ง๐ท Rio de Janeiro | 4.6 | Based on attractiveness of visitors n=413,256 | |
๐ฑโโ๏ธ Where attractive women travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐น๐ญ Ko Phi Phi | 5 | ||
| 2 | ๐ซ๐ท Cannes | 4.97 | ||
| 3 | ๐ญ๐ท Zadar | 4.78 | ||
| 4 | ๐ฎ๐น Genoa | 4.73 | ||
| 5 | ๐ช๐ธ Ibiza | 4.66 | ||
| 6 | ๐ฉ๐ช Dresden | 4.62 | ||
| 7 | ๐บ๐ธ Orlando | 4.62 | ||
| 8 | ๐ต๐ฑ Gdansk | 4.62 | ||
| 9 | ๐ต๐ฑ Wrocลaw | 4.61 | ||
| 10 | ๐ป๐ณ Nha Trang | 4.58 | ||
| 11 | ๐ณ๐ฑ Rotterdam | 4.54 | ||
| 12 | ๐บ๐ฆ Kyiv | 4.54 | ||
| 13 | ๐ท๐บ Moscow | 4.54 | ||
| 14 | ๐ฑ๐ฐ Galle | 4.53 | ||
| 15 | ๐น๐ญ Ko Samui | 4.53 | ||
| 16 | ๐ง๐ช Bruges | 4.51 | ||
| 17 | ๐ฒ๐ช Budva | 4.51 | ||
| 18 | ๐ฌ๐ท Rhodes | 4.51 | ||
| 19 | ๐ฎ๐น Amalfi | 4.51 | ||
| 20 | ๐ฉ๐ด Punta Cana | 4.51 | ||
| 21 | ๐น๐ญ Ko Pha Ngan | 4.51 | ||
| 22 | ๐ฆ๐บ Cairns | 4.5 | ||
| 23 | ๐ฎ๐ฉ Uluwatu | 4.5 | ||
| 24 | ๐ฌ๐ช Batumi | 4.49 | ||
| 25 | ๐จ๐ฑ Valparaรญso | 4.49 | ||
| 26 | ๐ช๐ธ Fuerteventura | 4.49 | ||
| 27 | ๐ป๐ณ Da Lat | 4.49 | ||
| 28 | ๐ต๐น Faro | 4.49 | ||
| 29 | ๐ฌ๐ท Mykonos | 4.48 | ||
| 30 | ๐ต๐น Portimรฃo | 4.48 | Based on attractiveness of visitors n=413,256 | |
๐จโ Where unattractive men travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐น๐ญ Pattaya | 3.41 | ||
| 2 | ๐ฎ๐ณ Goa | 3.64 | ||
| 3 | ๐ฒ๐ฝ Cozumel | 3.72 | ||
| 4 | ๐ฎ๐ณ Bengaluru | 3.72 | ||
| 5 | ๐ช๐ธ Alicante | 3.78 | ||
| 6 | ๐ฐ๐ฟ Almaty | 3.78 | ||
| 7 | ๐บ๐ธ Houston | 3.78 | ||
| 8 | ๐ณ๐ต Kathmandu | 3.82 | ||
| 9 | ๐ฎ๐ฑ Jerusalem | 3.82 | ||
| 10 | ๐น๐ญ Hua Hin | 3.84 | ||
| 11 | ๐ฑ๐ฆ Vientiane | 3.85 | ||
| 12 | ๐ต๐พ Asuncion | 3.85 | ||
| 13 | ๐ฒ๐ช Podgorica | 3.86 | ||
| 14 | ๐ต๐ท San Juan | 3.88 | ||
| 15 | ๐ฏ๐ต Fukuoka | 3.88 | ||
| 16 | ๐ด๐ฒ Muscat | 3.89 | ||
| 17 | ๐ฎ๐ณ Mumbai | 3.89 | ||
| 18 | ๐ฐ๐ญ Phnom Penh | 3.89 | ||
| 19 | ๐ช๐ฌ Cairo | 3.92 | ||
| 20 | ๐ป๐ณ Nha Trang | 3.93 | ||
| 21 | ๐ต๐ฆ Panama City | 3.94 | ||
| 22 | ๐ท๐บ Moscow | 3.94 | ||
| 23 | ๐ฎ๐ฉ Kuta | 3.94 | ||
| 24 | ๐ณ๐ฑ Rotterdam | 3.97 | ||
| 25 | ๐ฌ๐ช Batumi | 3.97 | ||
| 26 | ๐ฏ๐ต Hiroshima | 3.97 | ||
| 27 | ๐ฉ๐ด Santo Domingo | 3.98 | ||
| 28 | ๐ต๐ฑ Gdansk | 3.98 | ||
| 29 | ๐ฆ๐ฒ Yerevan | 3.99 | ||
| 30 | ๐บ๐ฆ Lviv | 4 | Based on unattractiveness of visitors n=413,256 | |
๐ฑโโ๏ธ Where unattractive women travel to |
||||
| # | City | Attractiveness | ||
| 1 | ๐ต๐พ Asuncion | 3.07 | ||
| 2 | ๐ช๐จ Quito | 3.1 | ||
| 3 | ๐ณ๐ฟ Wellington | 3.22 | ||
| 4 | ๐ฐ๐ช Nairobi | 3.24 | ||
| 5 | ๐ช๐จ Cuenca | 3.28 | ||
| 6 | ๐ฑ๐ฐ Weligama | 3.31 | ||
| 7 | ๐จ๐ณ Macau | 3.32 | ||
| 8 | ๐จ๐ฆ Quebec City | 3.34 | ||
| 9 | ๐ฏ๐ต Fukuoka | 3.35 | ||
| 10 | ๐ณ๐ฟ Queenstown | 3.38 | ||
| 11 | ๐ฆ๐บ Perth | 3.39 | ||
| 12 | ๐ต๐ท San Juan | 3.42 | ||
| 13 | ๐บ๐ธ Atlanta | 3.43 | ||
| 14 | ๐ฏ๐ด Amman | 3.45 | ||
| 15 | ๐ง๐ฆ Sarajevo | 3.47 | ||
| 16 | ๐จ๐ด Bogota | 3.48 | ||
| 17 | ๐ฑ๐ฆ Vientiane | 3.48 | ||
| 18 | ๐ฒ๐ฝ Merida | 3.48 | ||
| 19 | ๐ฌ๐ง Liverpool | 3.52 | ||
| 20 | ๐บ๐ธ New Orleans | 3.53 | ||
| 21 | ๐ฏ๐ฒ Montego Bay | 3.54 | ||
| 22 | ๐ต๐ฆ Panama City | 3.54 | ||
| 23 | ๐ฐ๐ท Jeju Island | 3.55 | ||
| 24 | ๐จ๐ณ Guangzhou | 3.56 | ||
| 25 | ๐ฒ๐ฝ Guadalajara | 3.59 | ||
| 26 | ๐ฉ๐ด Santo Domingo | 3.6 | ||
| 27 | ๐ฐ๐ญ Phnom Penh | 3.61 | ||
| 28 | ๐ฑ๐ฐ Colombo | 3.62 | ||
| 29 | ๐ฒ๐ฆ Essaouira | 3.62 | ||
| 30 | ๐ฉ๐ช Dusseldorf | 3.62 | Based on unattractiveness of visitors n=413,256 | |
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