Understanding Where the Internet Isn’t Good Enough Yet

Since March 2020, the Internet has been the trusty sidekick that’s helped us through the pandemic. Or so it seems to those of us lucky enough to have fast, reliable (and often cheap) Internet access.

With a good connection you could keep working (if you were fortunate enough to have a job that could be done online), go to school or university, enjoy online entertainment like streaming movies and TV, games, keep up with the latest news, find out vital healthcare information, schedule a vaccination and stay in contact with loved ones and friends with whom you’d normally be spending time in person.

Without a good connection though, all those things were hard or impossible.

Sadly, access to the Internet is not uniformly distributed. Some have cheap, fast, low latency, reliable connections, others have some combination of expensive, slow, high latency and unreliable connections, still others have no connection at all. Close to 60% of the world have Internet access leaving a huge 40% without it at all.

This inequality of access to the Internet has real-world consequences. Without good access it is so much harder to communicate, to get vital information, to work and to study. Inequality of access isn’t a technical problem, it’s a societal problem.

This week, Cloudflare is announcing Project Pangea with the goal of helping reduce this inequality. We’re helping community networks get onto the Internet cheaply, securely and with good bandwidth and latency. We can't solve all the challenges of bringing fast, cheap broadband access to everyone (yet) but we can give fast, reliable transit to ISPs in underserved communities to help move in that direction. Please refer to our Pangea announcement for more details.

To understand why Project Pangea is important, you need to understand how different the experience of accessing the Internet is around the world. From a distance, the world looks blue and green. But we all know that our planet varies wildly from place to place: deserts and rainforests, urban jungles and placid rural landscapes, mountains, valleys and canyons, volcanos, salt flats, tundra, and verdant, rolling hills.

Cloudflare is in a unique position to measure the performance and reach of the Internet over this vast landscape. We have servers in more than 200 cities in over 100 countries, we process 10s of trillions of Internet requests every month. Our network and customers and their users span the globe, every country in every network.

Zoom out to the level of a city, county, state, or country, and average Internet performance can look good — or, at least, acceptable. Zoom in, however, and the inequalities start to show. Perhaps part of a county has great performance, and another limps along at barely dial-up speeds — or worse. Or perhaps a city has some neighborhoods with fantastic fiber service, and others that are underserved and struggling with spotty access.

Inequality of Internet access isn’t a distant problem, it’s not limited to developing countries, it exists in the richest countries in the world as well as the poorest. There are still many parts of the world  where a Zoom call is hard or impossible to make. And if you’re reading this on a good Internet connection, you may be surprised to learn that places with poor or no Internet are not far from you at all.

For Impact Week, we’ve analyzed Internet data in the United States, Brazil, United Kingdom, Germany, France, South Africa, Japan, and Australia to build a picture of Internet performance.

Below, you’ll find detailed maps of where the Internet is fast and slow (focusing on available bandwidth) and far away from the end user (at least in terms of the latency between the client and server). We’d have loved to have used a single metric, however, it’s hard for a single number to capture the distribution of good, bad, and non-existent Internet traffic in a region. It’s for that reason that we’ve used two metrics to represent performance: latency and bandwidth (otherwise known as throughput). The maps below are colored to show the differences in bandwidth and latency and answer part of the question: “How good is the Internet in different places around the world?”

As we like to say, we’re just getting started with this — we intend to make more of this data and analysis available in the near future. In the meantime, if you’re a local official who wants to better understand their community’s relative performance, please reach out — we’d love to connect with you. Or, if you’re interested in your own Internet performance, you can visit speed.cloudflare.com to run a personalized test on your connection.

Before we begin, a quick reminder: latency (usually measured in milliseconds or ms) is the time it takes for communications to go to an Internet destination from your device and back, whereas bandwidth is the amount of data that can be transferred in a second (it’s usually measured in megabits per second or Mbps).

Both latency and bandwidth affect the performance of an Internet connection. High latency particularly affects things like online gaming where quick responses from servers are needed, but also shows up by slowing down the loading of complex web pages, and even interrupting some streaming video. Low bandwidth makes downloading anything slow: be it images on a webpage, the new app you want to try out on your phone, or the latest movie.

Blinking your eyes takes about 100ms; but you’ll begin to notice performance changes around 60ms of latency and below 30ms is gold class performance, seeing little to no delay in video streaming or gaming.

United StatesUnited States median throughput: 50.27MbpsUS median latency: 46.69ms

The US government has long recognized the importance of improving the Internet for underserved communities, but the Federal Communications Commission (FCC), the US agency responsible for determining where investment is most needed, has struggled to accurately map Internet access across the country.  Although the FCC has embarked on a new data collection effort to improve the accuracy of existing maps, the US government still lacks a comprehensive understanding of the areas that would most benefit from broadband investment.

Cloudflare’s data confirms the overall concerns with inconsistent access to the Internet and helps fill in some of the current gaps.  A glance at the two maps of the US below will show that, even zoomed out to county level, there is inequality across the country. High latency and low bandwidth stand out as red areas.

US locations with the lowest latency (best) and highest latency (worst) are as follows.

Best performing geographies by latency

Worst performing geographies by latency

La Habra, California

Parrottsville, Tennessee

Midlothian, Texas

Loganville, Wisconsin

Los Alamitos, California

Mackinaw City, Michigan

St Louis, Missouri

Reno, Nevada

Fort Worth, Texas

Eva, Tennessee

Sugar Grove, North Carolina

Milwaukee, Wisconsin

Rockwall, Texas

Grove City, Minnesota

Justin, Texas

Sacred Heart, Minnesota

Denton, Texas

Scottsboro, Alabama

Hampton, Georgia

Vesta, Minnesota

When thinking about bandwidth, 5 to 10Mbps are generally good enough for video conferencing, but ultra-HD TV watching might consume up to 20Mbps easily. For context, the Federal Communications Commission (FCC) defines the minimum bandwidth for “Advanced Service” at 25 Mbps.

The best performing (i.e., the highest bandwidth) in the US tells an interesting story. New York City comes out on top, but if you were to zoom in on the city you’d find pockets of inequality. You can read more about our partnership with NYC Mesh in the Project Pangea post and how they are helping bring better Internet to underserved parts of the Big Apple. Notice how the tyranny of averages can disguise a problem.

Best performing geographies by throughput

Worst performing geographies by throughput

New York, New York

Ozark, Missouri

Hartford, Connecticut

Stanly, North Carolina

Avery, North Carolina

Ellis, Kansas

Red Willow, Nebraska

Marion, West Virginia

McLean, Kentucky

Sedgwick, Kansas

Franklin, Alabama

Calhoun, West Virginia

Montgomery, Pennsylvania

Jasper, Georgia

Cook, Illinois

Buchanan, Missouri

Montgomery, Maryland

Wetzel, West Virginia

Monroe, Pennsylvania

North Slope, Alaska

Contrary to popular discourse about access to the Internet as a product of the rural-urban divide, we found that poor performance was not unique to rural areas. Los Angeles, Milwaukee, Florida’s Orange County, Fairfax, San Bernardino, Knox County, and even San Francisco have pockets of uniformly poor performance, often while adjoining ZIP codes have stronger performance.

Even in areas with excellent Internet connectivity, the same connectivity to the same resources can cost wildly different amounts. Internet prices for end-users correlates with the number of ISPs in an area, i.e. the greater the consumer choice, the better the price. President Biden's recent competition Executive Order, called out the lack of choice for broadband, noting “More than 200 million U.S. residents live in an area with only one or two reliable high-speed internet providers, leading to prices as much as five times higher in these markets than in markets with more options.”

The following cities have the greatest choice of Internet providers:

Geography

New York, New York

Los Angeles, California

Chicago, Illinois

Dallas, Texas

Washington, District of Columbia

Jersey City, New Jersey

Newark, New Jersey

Secaucus, New Jersey

Columbus, Ohio

One might expect less populated areas to have uniformly slower performance. There are, however, pockets of poor performance even in densely populated areas such as Los Angeles (California), Milwaukee (Wisconsin), Orange County (Florida), Fairfax (Virginia),  San Bernardino (California), Knox County (Tennessee), and even San Francisco (California).

In as many as 9% of ZIP codes, average latency exceeds 150ms, the acceptable threshold of performance to run a videoconferencing service such as Zoom.

AustraliaAustralia median throughput: 33.34MbpsAustralia median latency: 42.04ms

In general, Australia seems to suffer very poor broadband speeds, with speeds that are not capable of sustaining households watching video streaming, and possibly struggling with multiple video calls. The problem isn’t just a rural one either, while the inner cities showed good broadband speed, often with fiber-to-the-building Internet access, suburban areas suffered. Larger suburban areas like the Illawarra had similar speeds to more rural centers like Wagga Wagga, showing this is more than just an urban divide.

Best performing geographies by throughput

Worst performing geographies by throughput

Inner West Sydney, New South Wales

West Tamar, Tasmania

Port Phillip, Victoria

Bassendean, Western Australia

Woollahra, New South Wales

Alexandrina, South Australia

Brimbank, Victoria

Bayswater, Western Australia

Lake Macquarie, New South Wales

Augusta-Margaret River, Western Australia

Hawkesbury, New South Wales

Goulburn Mulwaree, New South Wales

Sydney, New South Wales

Goyder, South Australia

Wentworth, New South Wales

Kingborough, Tasmania

Hunters Hill, New South Wales

Cottesloe, Western Australia

Blacktown, New South Wales

Lithgow, New South Wales

The irony is that, from a latency perspective, Australia actually performs quite well.

Best performing geographies by latency

Worst performing geographies by latency

Port Phillip, Victoria

Narromine, New South Wales

Mornington Peninsula, Victoria

North Sydney, New South Wales

Whittlesea, Victoria

Northern Midlands, Tasmania

Penrith, New South Wales

Swan, Western Australia

Mid-Coast, New South Wales

Wanneroo, Western Australia

Campbelltown, New South Wales

Snowy Valleys, New South Wales

Northern Beaches, New South Wales

Parkes, New South Wales

Strathfield, New South Wales

Broome, Western Australia

Latrobe, Victoria

Griffith, New South Wales

Surf Coast, Victoria

Busselton, Western Australia

JapanJapan median throughput: 61.4MbpsJapan median latency: 31.89ms

Japan’s Internet has consistently low latency, including in distant areas such as Okinawa prefecture, 1,000 miles away from Tokyo.

Best performing geographies by latency

Worst performing geographies by latency

Nara

Yamagata

Osaka

Okinawa

Shiga

Miyazaki

Kōchi

Nagasaki

Kyoto

Ōita

Tochigi

Kagoshima

Tokushima

Yamaguchi

Wakayama

Tottori

Kanagawa

Saga

Aichi

Ehime

However, it's a different story when it comes to bandwidth. Several prefectures in Kyushu Island, Okinawa Prefecture, and Western Honshu have performance falling behind the rest of the country. Unsurprisingly, the best Internet performance is seen in Tokyo, with the highest concentration of people and data centers.

Best performing geographies by throughput

Worst performing geographies by throughput

Osaka

Tottori

Tokyo

Shimane

Kanagawa

Yamaguchi

Nara

Okinawa

Chiba

Saga

Aomori

Miyazaki

Hyōgo

Kagoshima

Kyoto

Yamagata

Tokushima

Nagasaki

Kōchi

Fukui

United KingdomUnited Kingdom median throughput: 53.8MbpsUnited Kingdom median latency: 34.12ms

The United Kingdom has good latency throughout most of the country, however bandwidth is a different story. The best performance is seen in inner London as well as some other larger cities like Manchester. London and Manchester are also the homes of the UK's largest Internet exchange points. More effort to localize data into other cities, like Edinburgh, would be an important step to improving performance for those regions.

Best performing geographies by latency

Worst performing geographies by latency

Sutton

Brent

Milton Keynes

Ceredigion

Lambeth

Westminster

Cardiff

Scottish Borders

Harrow

Shetland Islands

Hackney

Middlesbrough

Islington

Fermanagh and Omagh

Kensington and Chelsea

Slough

Thurrock

Highland

Kingston upon Thames

Denbighshire

Best performing geographies by throughput

Worst performing geographies by throughput

City of London

Orkney Islands

Slough

Shetland Islands

Lambeth

Blaenau Gwent

Surrey

Ceredigion

Tower Hamlets

Isle of Anglesey

Coventry

Fermanagh and Omagh

Wrexham

Scottish Borders

Islington

Denbighshire

Vale of Glamorgan

Midlothian

Leicester

Rutland

GermanyGermany median throughput: 48.79MbpsGermany median latency: 42.1ms

Germany has some of the best performance centered on Frankfurt am Main, which is one of the major Internet hubs of the world, however what was formerly East Germany, has higher latency, and slower speeds, leaning to a poorer Internet performance.

Best performing geographies by latency

Worst performing geographies by latency

Erlangen

Harz

Coesfeld

Nordwestmecklenburg

Weißenburg-Gunzenhausen

Saale-Holzland-Kreis

Heinsberg

Elbe-Elster

Main-Taunus-Kreis

Vorpommern-Greifswald

Main-Kinzig-Kreis

Vorpommern-Rügen

Darmstadt

Kyffhäuserkreis

Peine

Barnim

Herzogtum Lauenburg

Rostock

Segeberg

Meißen

Best performing geographies by throughput

Worst performing geographies by throughput

Weißenburg-Gunzenhausen

Saale-Holzland-Kreis

Frankfurt am Main

Weimarer Land

Kassel

Vulkaneifel

Cochem-Zell

Kusel

Dingolfing-Landau

Spree-Neiße

Bodenseekreis

Eisenach

Sankt Wendel

Unstrut-Hainich-Kreis

Landshut

Saale-Orla-Kreis

Ludwigsburg

Weimar

Speyer

Südliche Weinstraße

FranceFrance median throughput: 48.51MbpsFrance median latency: 54.2ms

Paris has long been the Internet hub in France. Marseille has started to grow as a hub, especially with the large number of submarine cables landing. Other interconnection hubs in Lyon and Bordeaux are where we’ll start to see growth as Internet hubs. These four cities are where we also see the best performance, with the highest speeds and lowest latencies, giving the best Internet performance.

Best performing geographies by latency

Worst performing geographies by latency

Antony

Clamecy

Boulogne-Billancourt

Beaune

Lyon

Ambert

Lille

Commercy

Versailles

Vitry-le-François

Nogent-sur-Marne

Villefranche-de-Rouergue

Bobigny

Lure

Marseille

Avranches

Saint-Germain-en-Laye

Oloron-Sainte-Marie

Créteil

Privas

Best performing geographies by throughput

Worst performing geographies by throughput

Boulogne-Billancourt

Clamecy

Antony

Bellac

Marseille

Issoudun

Lille

Vitry-le-François

Nanterre

Sarlat-la-Canéda

Paris

Segré

Lyon

Rethel

Bobigny

Avallon

Versailles

Privas

Saverne

Sartène

BrazilBrazil median throughput: 26.28MbpsBrazil median latency: 49.25ms

Much of Brazil has good, low latency Internet performance, given geographic proximity to the major Internet hubs in São Paulo and Rio de Janeiro. Much of the Amazon has low speeds and high latency, for those parts that are actually connected to the Internet.

Campinas is one stand out, with some of the best performing Internet across Brazil, and is also the site of a recent Cloudflare data center launch.

Best performing geographies by latency

Worst performing geographies by latency

Vale do Paraiba Paulista

Vale do Acre

Assis

Sul Amazonense

Sudoeste Amazonense

Marajo

Litoral Sul Paulista

Vale do Jurua

Baixadas

Sul de Roraima

Centro Fluminense

Centro Amazonense

Sul Catarinense

Madeira-Guapore

Vale do Paraiba Paulista

Sul do Amapa

Noroeste Fluminense

Metropolitana de Belem

Bauru

Baixo Amazonas

Best performing geographies by throughput

Worst performing geographies by throughput

Metropolitana do Rio de Janeiro

Sudoeste Amazonense

Campinas

Marajo

Metropolitana de São Paulo

Norte Amazonense

Oeste Catarinense

Baixo Amazonas

Marilia

Sudeste Rio-Grandense

Vale do Itajaí

Sul Amazonense

Sul Catarinense

Centro-Sul Cearense

Sudoeste Paranaense

Sudoeste Paraense

Grande Florianópolis

Sertão Sergipano

Norte Catarinense

Sertoes Cearenses

South AfricaSouth Africa median throughput: 6.4MbpsSouth Africa median latency: 59.78ms

Johannesburg has been the historical hub for South Africa’s Internet. This is where many Internet giants have built data centers, and it shows in latency as distance from Johannesburg. South Africa has grown to have two more Internet hubs in Cape Town and Durban. Internet performance also follows these three cities. However, much of South Africa’s Internet performance lacks the ability for video streaming and video conferencing in high definition.

Best performing geographies by latency

Worst performing geographies by latency

Siyancuma

Dr Beyers Naude

uMshwathi

Mogalakwena

City of Tshwane

Ulundi

Breede Valley

Modimolle/Mookgophong

City of Cape Town

Maluti a Phofung

Overstrand

Moqhaka

Local Municipality of Madibeng

Thulamela

Metsimaholo

Walter Sisulu

Stellenbosch

Dawid Kruiper

Ekurhuleni

Ga-Segonyana

Best performing geographies by throughput

Worst performing geographies by throughput

Siyancuma

Dr Beyers Naude

City of Cape Town

Walter Sisulu

City of Johannesburg

Lekwa-Teemane

Ekurhuleni

Dr Nkosazana Dlamini Zuma

Drakenstein

Emthanjeni

eThekwini

Dawid Kruiper

Buffalo City

Swellendam

uMhlathuze

Merafong City

City of Tshwane

Blue Crane Route

City of Matlosana

Modimolle/Mookgophong

One question we had as we went through a lot of this data: does ISP concentration impact Internet performance?

On one hand, there’s a case to be made that more ISP competition results in no one vendor being able to invest sufficient resources to build out a fast network. On the other hand, well, classical economics would suggest that monopolies are bad, right?

To investigate the question further, we did a deep dive into Alabama in the United States, the 24th most populous state in the US. We tracked two key metrics across 65 counties: Internet performance as defined by average download speed, and ISP concentration, as measured by the largest ISP’s traffic share.

Here is the raw data:

County

Avg. Download Speed

Largest ISP's Traffic Share

County

Avg. Download Speed

Largest ISP's Traffic Share

Marion

53.77

41%

Franklin

32.01

83%

Escambia

29.14

43%

Coosa

82.15

83%

Etowah

56.07

49%

Crenshaw

44.49

84%

Jackson

37.77

52%

Randolph

21.4

86%

Winston

59.25

56%

Lamar

33.94

86%

Montgomery

79.5

58%

Autuaga

65.55

86%

Baldwin

49.06

58%

Choctaw

23.97

87%

Houston

73.73

61%

Butler

29.86

90%

Dallas

86.92

62%

Pike

50.54

92%

Marshall

59.93

62%

Sumter

38.52

91%

Chambers

72.05

63%

Pickens

43.76

92%

Jefferson

99.84

64%

Marengo

42.89

92%

Elmore

71.05

66%

Macon

12.69

92%

Fayette

41.7

68%

Lawrence

62.87

92%

Lauderdale

62.87

69%

Bullock

23.89

92%

Colbert

47.91

70%

Chilton

17.13

95%

DeKalb

58.55

70%

Wilcox

62.12

93%

Morgan

61.78

71%

Monroe

20.74

96%

Washington

5.14

72%

Dale

55.46

97%

Geneva

32.01

73%

Coffee

58.18

97%

Lee

78.1

73%

Conecuh

34.94

97%

Tuscaloosa

58.85

76%

Cleburne

38.25

97%

Cullman

61.03

77%

Clarke

38.14

97%

Covington

35.48

78%

Calhoun

64.19

97%

Shelby

69.66

79%

Lowndes

9.91

98%

St. Clair

33.05

79%

Russell

49.48

98%

Blount

40.58

80%

Henry

4.69

98%

Mobile

68.77

80%

Limestone

71.6

98%

Walker

39.36

81%

Bibb

70.14

98%

Barbour

51.48

82%

Cherokee

17.13

99%

Tallapoosa

60

82%

Greene

4.76

99%

Madison

99

83%

Clay

3.42

100%

Across most of Alabama, we see very high ISP concentration. For the majority of counties, the largest ISP has 80% (or higher) share of traffic, while all the other ISPs combined operate at considerably smaller scale. In only three counties (Marion, Escambia and Etowah) does each ISP carry less than 50% of user traffic. Interestingly, Etowah is one of the best performing in the state, while Henry, a county where 98% of Internet traffic is concentrated behind a single ISP is the worst performing.

Where it gets interesting is when you plot the data, tracking the non-dominant ISP by traffic share (which is simply 100% less the traffic share of the dominant ISP) against the performance (as measured by download speed) and then use a linear line of best fit to find the relationship. Here’s what you get:

As you can see, there is a strong positive relationship between the non-dominant ISP’s traffic share and the average download speed. As the non-dominant ISP increases its traffic share, Internet speeds tend to improve. The conclusion is clear: if you want to improve Internet performance in a region, foster more competition between multiple Internet service providers.

There is more to the story, however, than just concentration. Alabama, like a lot of other regions that aren’t served well by ISPs, faces another performance challenge: poor routing, also sometimes known as “tromboning”.

Consider Tuskegee in Alabama, home to a local university.

In Tuskegee, choice is limited. Consumers only have a single choice for high-speed broadband. But even once an off-campus student has local access to the Internet, it isn’t truly local: Tuskegee students on a different ISP than their university will likely see their traffic detour all the way through Atlanta (two hours northeast by car!) before making its way back to school.

This doesn’t happen in isolation: today, the largest ISPs only exchange traffic with other networks in a handful of cities, notably Seattle, San Jose, Los Angeles, Dallas, Chicago, Atlanta, Miami, Ashburn, and New York City.

If you’re in one of these big cities, you’re unlikely to suffer from tromboning. But if you’re not? Your Internet traffic can often have to travel further away before looping back, similar to the shape of a trombone, reducing your Internet performance. Tromboning contributes to inefficiency and drives up the cost of Internet access. An increasing amount of traffic is wastefully carried to cities far away, instead of keeping the data local.

You can visualize how your Internet traffic is flowing, by using tools like traceroute.

As an example, we ran tests using RIPE Atlas probes to Facebook from Alabama, and unfortunately found extremes where traffic can sometimes take a highly circuitous route — traffic going to Atlanta, then Ashburn, Paris, Amsterdam, before making its way back to Alabama. The path begins on AT&T's network and goes to Atlanta where it enters the network for Telia (an IP transit provider), crosses the Atlantic, meets Facebook, and then comes back.

Traceroute to 157.240.201.35 (157.240.201.35), 48 byte packets
1- 192.168.6.1 1.435ms 0.912ms 0.636ms
2-  99.22.36.1 99-22-36-1.lightspeed.dctral.sbcglobal.net AS7018 1.26ms 1.134ms 1.107ms
3-  99.173.216.214 AS7018 3.185ms 3.173ms 3.099ms
4-  12.122.140.70 cr84.attga.ip.att.net AS7018 11.572ms 13.552ms 15.038ms
5 - * * *
6- 192.205.33.42 AS7018 8.695ms 9.185ms 8.703ms
7-  62.115.125.129 ash-bb2-link.ip.twelve99.net AS1299 23.53ms 22.738ms 23.012ms
8-  62.115.112.243 prs-bb1-link.ip.twelve99.net AS1299 115.516ms 115.52ms 115.211ms
9-  62.115.134.96 adm-bb3-link.ip.twelve99.net AS1299 113.487ms 113.405ms 113.25ms
10-  62.115.136.195 adm-b1-link.ip.twelve99.net AS1299 115.443ms 115.703ms 115.45ms
11- 62.115.148.231 facebook-ic331939-adm-b1.ip.twelve99-cust.net AS1299 134.149ms 113.885ms 114.246ms
12- 129.134.51.84 po151.asw02.ams2.tfbnw.net AS32934 113.27ms 113.078ms 113.149ms
13-  129.134.48.101 po226.psw04.ams4.tfbnw.net AS32934 114.529ms 114.439ms 117.257ms
14-  157.240.38.227 AS32934 113.281ms 113.365ms 113.448ms
15- 157.240.201.35 edge-star-mini-shv-01-ams4.facebook.com AS32934 115.013ms 115.223ms 115.112ms

The intent here isn’t to shame AT&T, Telia, or Facebook — nor is this challenge unique to them. Facebook's content is undoubtedly cached in Atlanta and the request from Alabama should go no further than that. While many possible conditions within and between these three networks could have caused this tromboning, in the end, the consumer suffers.

The solution? Have more major ISPs exchange in more cities and with more networks. Of course, there’d be an upfront cost involved in doing so, even if it would reduce cost more over the long run.

As William Gibson famously observed: the future is here, but it’s just not evenly distributed.

One of the clearest takeaways from the data and analysis presented here is that Internet access varies tremendously across geographies. But it’s not just a case of the developed world vs the developing, or even rural vs urban. There are underserved urban communities and regions of the developed world that do not score as highly as you might expect.

Furthermore, our case study of Alabama shows that the structure of the ISP market is incredibly important to promoting performance. We found a strong positive correlation between more competition and faster performance. Similarly, there’s a lot of opportunity for more networks to interconnect in more places, to avoid bad routing.

Finally, if we want to get the other 40% of the world online, we are going to need more initiatives that drive up access and drive down cost. There’s plenty of scope to help — and we’re excited to be launching Project Pangea to help.