Isla McKetta | October 22, 2020

ICYMI: Ookla Data and Research from September 2020

Highlights from the Speedtest Global Index^TM

Global-Index-Tweet-Image-Sept-2020
These are the top stories from September 2020:

Croatia is back up to 11th place on mobile after a two-month slump.
Denmark’s relatively steady increase in fixed broadband speeds over the last 13 months has them ranked seventh.
There was no change in the rankings of the top four countries on mobile and the top three on fixed broadband from August.

New Market Analyses

Canada

TELUS showed the fastest Speed Score^™ on mobile during Q3 2020 while Rogers was fastest on fixed broadband. Québec City had the fastest mean mobile download speed while London was fastest for fixed broadband.

Malaysia

Maxis had the fastest Speed Score on mobile during Q1-Q2 2020 while TIME was fastest for fixed broadband. Nusajaya had the fastest mean download speed over mobile while Shah Alam was fastest for fixed broadband.

Taiwan

Chunghwa Telecom showed the highest 4G Availability in Taiwan during Q1-Q2 2020.

Turkey

Turkcell was the fastest mobile provider in Turkey during Q3 2020 while Turksat Kablo was the fastest ISP.

United Kingdom

EE had the fastest Speed Score on mobile during Q3 2020 while Virgin Media was fastest on fixed broadband. Three showed the fastest median download speed on 5G. Cardiff had the fastest mean download speed on mobile while Edinburgh was fastest for fixed broadband. Read our latest article debunking misleading claims in the U.K.

United States

AT&T was the fastest mobile operator in the U.S. during Q3 2020 while Verizon was the fastest fixed broadband ISP. Fort Wayne, Indiana had the fastest mobile download speed on our list and Austin, Texas was the fastest city for fixed broadband.

Articles worth a second look

Announcing Ookla Open Datasets

This is your chance to crunch Ookla’s data on global network performance. Use our new open dataset to create a project that illustrates internet performance where you live.

How Georgia is Leveraging Cell Analytics^™ to Enable Virtual Classrooms

classroom
Ookla helped the Georgia Department of Education to find the best locations to deploy school buses with mobile Wi-Fi hotspots to bridge the connectivity gap for remote learning.

Read our latest white paper

How to Improve In-Building Network Performance and Coverage with Crowdsourced Data

buildings
This guide for RAN engineering teams will show you how to use crowdsourced data to analyze in-building network performance and coverage — and how to prioritize the network improvements that have the most impact on your customers.

Ookla retains ownership of this article including all of the intellectual property rights, data, content graphs and analysis. This article may not be quoted, reproduced, distributed or published for any commercial purpose without prior consent. Members of the press and others using the findings in this article for non-commercial purposes are welcome to publicly share and link to report information with attribution to Ookla.

About the Author

Isla McKetta

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Mark Giles | May 17, 2023

ISPs Need to Do More to Improve Wi-Fi Performance in the Home

Key messages

Wi-Fi woes continue. Ookla® Speedtest Intelligence® data shows Wi-Fi performance continues to lag behind ethernet performance within home networks in many advanced fixed broadband markets, with Wi-Fi speeds typically ranging from between 30-40% of ethernet speeds during Q1 2023.
Developed Asian and North American markets lead the charge to Wi-Fi 6/6E. Wi-Fi 4 and 5 remain the dominant Wi-Fi access technologies globally, accounting for a combined 89% of Speedtest® samples during Q1 2023. However, a number of advanced fixed broadband markets are rapidly migrating to Wi-Fi 6 and 6E, with China, Hong Kong (SAR), Singapore, Canada, and the U.S. leading the charge.
Growing Wi-Fi 6/6E adoption helps narrow the gap in Wi-Fi performance. In markets such as Canada, France, Germany, Singapore, Sweden, and the U.S., where the transition to fiber is more advanced, and where ISPs are actively driving adoption of Wi-Fi 6/6E routers, we see Wi-Fi performance closing the gap to ethernet. However, more needs to be done in other markets, where migration to more advanced fixed access networks is exposing the limitations of the installed base of Wi-Fi routers.
Router vendors pushing the envelope with Wi-Fi 7 capable launches. ASUS leads the market for Wi-Fi 6/6E routers among Speedtest samples, and both ASUS and other leading router vendors have been quick to launch Wi-Fi 7 capable routers. Despite this, Wi-Fi 6 and 6E remain the growing component of their installed bases. ASUS leads the market according to Speedtest Intelligence with 39% of its routers we sampled supporting Wi-Fi 6/6E during Q1 2023, well ahead of second placed NETGEAR with 26%.
Smartphone device support indicates Wi-Fi 6/6E should remain the immediate focus for ISPs. With the two largest smartphone vendors globally, Samsung and Apple, currently shunning Wi-Fi 7, ISPs waiting to see if they can leapfrog Wi-Fi 6E to Wi-Fi 7 should stay their hands. The fact that China still needs to allocate the 6 GHz spectrum band — key for Wi-Fi 6E and 7 — for unlicensed use is also significant, and appears to have weighed on the Wi-Fi 6E adoption among China’s leading Android smartphone manufacturers.

Wi-Fi performance continues to lag ethernet within the home

ISPs in advanced fixed broadband markets are increasingly looking to offer more advanced Wi-Fi routers and solutions such as mesh networks, which are designed to improve Wi-Fi coverage and performance. However, Speedtest Intelligence data shows that more needs to be done to improve Wi-Fi performance, which typically ranged from between 30-40% of ethernet speeds. Median Wi-Fi performance as measured by Speedtest will tend to lag behind median ethernet performance, depending on distance of the end-user device from the router, including any obstacles and signal interference the Wi-Fi signal needs to traverse to reach the device.

Our analysis of Speedtest Intelligence data reveals that driving greater adoption of more advanced Wi-Fi routers can help ISPs narrow the gap between Wi-Fi and ethernet performance, with ISPs in Canada, France, Germany, Singapore, Sweden, and the U.S. already successfully doing so over the past year.

Despite this, the results are not always positive, with the gap between Wi-Fi and ethernet performance widening, in particular in the U.K. and Taiwan. Where markets are rapidly migrating from more legacy fixed broadband technology to advanced cable and fiber connections, Wi-Fi performance can lag relative to ethernet, indicating a need to accelerate the adoption of more advanced Wi-Fi technologies.

Older generations of Wi-Fi 4 and Wi-Fi 5 remain dominant globally

While much of the focus of the device ecosystem is on spurring adoption of the latest Wi-Fi standards, there is a long way to go before even Wi-Fi 6 becomes a dominant standard globally. Based on Speedtest Intelligence data, the proportion of Wi-Fi tests by generation (a good proxy for adoption) shows that Wi-Fi 4 and Wi-Fi 5 remain the dominant router technology, with Wi-Fi 6 representing just under 10% as of February 2023, and Wi-Fi 7 showing very few samples. The share of samples from Wi-Fi 4 routers has fallen by 6 ppts year-over-year, while Wi-Fi 5’s share of samples has marginally increased.

Asian and North American ISPs lead the charge to Wi-Fi 6 and beyond

ISPs are the main driver behind the adoption of new Wi-Fi standards, as highlighted by a 2022 study by Parks Associates, which found that 52% of U.S. consumers acquired their router from their ISP. Rolling out more advanced routers to their customer bases enables them to take advantage of the increased performance of newer generations of Wi-Fi technology, and helps to ensure ISPs deliver faster speeds, particularly over fiber access networks.

Adoption of Wi-Fi 6 varies by market, even among the most developed fixed broadband markets globally. ISPs in a number of advanced fixed markets have already begun offering Wi-Fi 6E routers to their customer bases, with ISPs in North America in particular moving in this direction, including Bell Canada, Rogers, Telus, Verizon, XFINITY, Charter, and Frontier, as well as leading ISPs in advanced Asian and European markets.

Markets in Asia led the way on Wi-Fi 6 adoption, with China and Hong Kong both recording 42% adoption, followed by Singapore with 37%. Outside of Asia, North America showed the next highest level of adoption, with the U.S. and Canada recording 32% and 30%, respectively. European fixed markets lagged behind, with adoption ranging from 13% in the U.K., to 24% in Sweden. For markets such as Chile, which placed towards the top of the Ookla Speedtest Global Index™ for median fixed broadband speeds, a relatively low-level of Wi-Fi 6 adoption (8% in Q4 2022) signals further opportunity for ISPs in the market to boost performance.

The fastest growing markets, in terms of increasing share of Wi-Fi 6 of Speedtest samples year-over-year in Q1 2023, were Canada and Malaysia (+15 ppts), Singapore (+14 ppts), and Hong Kong (+12 ppts). While there was considerable variance between ISPs within each market, leading ISPs such as SmarTone (Hong Kong), DiGi (Malaysia), and ViewQwest (Singapore), are prompting a competitive response so that even ISPs with lower levels of Wi-Fi 6 adoption are prioritizing the technology and seeing adoption grow steadily.

Country	ISP	Wi-Fi 6 %, Q1 2023
Hong Kong (SAR)	SmarTone	62.4%
Canada	Bell pure fibre	57.3%
Singapore	ViewQwest	53.7%
Singapore	MyRepublic	50.3%
Malaysia	Digi	50.2%
Malaysia	Maxis	49.0%
Hong Kong (SAR)	NETVIGATOR	44.2%
Canada	Rogers	43.4%
Singapore	M1	41.7%
Singapore	SingTel	41.4%
Canada	Telus PureFibre	41.0%
Hong Kong (SAR)	HKBN	41.0%
Canada	Shaw	39.0%
Singapore	StarHub	35.6%
Hong Kong (SAR)	HGC	30.0%
Malaysia	TIME	28.8%
Malaysia	TM	21.5%

In addition to providing newer routers, ISPs are increasingly positioned to help consumers solve Wi-Fi performance issues in the home, such as offering mesh Wi-Fi solutions. For some ISPs, this has even taken precedence over offering newer Wi-Fi 6E routers, as they look to improved coverage within the home as a faster route to improving Wi-Fi performance.

In the U.K., BT has prioritized whole-home coverage over Wi-Fi 6E with its BT Complete Wi-Fi (mesh) offer, despite the U.K. regulator Ofcom having released the lower portion of the 6 GHz band for unlicensed use in 2020. In Canada, Telus, while having recently released a Wi-Fi 6E router for its broadband users, also offers its WiFi Plus package, which includes professional installation and “wall-to-wall coverage” throughout the home. Rogers also offers guaranteed Wi-Fi coverage throughout the home, as well as Wi-Fi 6E routers. Plume offers a subscription-based service, HomePass, across a number of markets, which allows users to add additional access points to help eradicate not-spots or poor Wi-Fi signal within the home and also offers solutions for ISPs looking to improve their Wi-Fi offerings. In Hong Kong, China Mobile Hong Kong (CMHK) was the first ISP in the market to offer a fiber-to-the-room service, while it and other ISPs such as NETVIGATOR offer consumers the option to subscribe to multiple channels over fiber with separate IP addresses, allowing them to divide their activities across channels and thereby help avoid congestion.

To capture the full performance benefits of Wi-Fi 6E and Wi-Fi 7, countries must allocate 6 GHz spectrum for unlicensed use, therefore allowing Wi-Fi devices to access this higher frequency, higher capacity spectrum, and utilize wider channels. At present, according to the Wi-Fi Alliance, allocation of the lower portion of the 6 GHz spectrum band (5,925 MHz to 6,425 MHz) is common among developed economies, with some notable exceptions in some developed markets in Asia and Asia Pacific, in particular China, while allocation of the full 6 GHz band is more limited, available across North America and some Latin American markets, as well as Saudi Arabia and South Korea.

Wi-Fi 7 on the horizon as router vendors continue to push the envelope on performance

Wi-Fi performance continues to scale, and with Wi-Fi 7 routers and smartphones having launched in the second half of 2022, that trend is set to continue. In addition to higher throughput, successive Wi-Fi generations also support lower latency, helping to better support higher quality video streaming, cloud gaming, and future use cases linked to concepts such as the Metaverse and other uses of extended reality (XR).

The major silicon vendors, Broadcom, Qualcomm, and Mediatek, were quick to update their solutions to support the emerging Wi-Fi 7 standard, and hardware vendors have followed suit. Chinese vendor H3C was the first to launch with its H3C Magic BE18000 Wi-Fi 7 router in July 2022, and it has since been followed by other major vendors including tp-link, ASUS, and more recently NETGEAR. However, the prices of early Wi-Fi 7 routers that take advantage of Wi-Fi 7’s range of enhanced performance capabilities will be a barrier to entry for many, with tp-link’s flagship Archer BE900 currently retailing at a cost of $699.99.

Speedtest Intelligence data shows minimal Wi-Fi 7 adoption as of March 2023, however we are likely to see the same vendors drive Wi-Fi 7 adoption that are currently leading on Wi-Fi 6. Based on global Speedtest Intelligence samples, we see ASUS leading the market in Wi-Fi 6 penetration, with 39% of samples recorded using Wi-Fi 6 compatible routers. NETGEAR and Belkin followed, but for the remaining major router vendors, Wi-Fi 6 penetration currently stands at close to 10% or below. Wi-Fi 6E remains a small but growing subset of Wi-Fi 6 certified devices, currently standing at 7.7% of products based on the latest Wi-Fi Alliance data. Of these, a majority are either routers or smartphones, with an almost even split between the two.

Smartphone support indicates ISPs should focus on Wi-Fi 6E for now

With Samsung releasing its Galaxy S23 range in February 2023 without Wi-Fi 7 support, and Apple’s latest iPhone 14 smartphones limited to Wi-Fi 6, it’s clear that, for now, ISPs should prioritize the rollout of Wi-Fi 6/6E among their customer bases rather than consider leapfrogging to Wi-Fi 7. The Xiaomi Mi13 Pro was the first Wi-Fi 7 capable smartphone to hit the market, launching in December 2022, although it was limited to Wi-Fi 6E initially, requiring a software update to enable Wi-Fi 7. The availability of Wi-Fi 7 supporting Android smartphones will grow through 2023, enabled by SoCs from leading vendor Qualcomm with its flagship Snapdragon 8 Gen 2, and MediaTek with its Dimensity 9200. Apple, on the other hand, lags on the latest Wi-Fi standard support, with the iPhone 14 series featuring Wi-Fi 6, and with its fall 2023 models rumored to be adding Wi-Fi 6E to their feature list.

Samsung, as the leading Android smartphone vendor globally, has the largest installed base of smartphones supporting Wi-Fi 6 and Wi-Fi 6E, and has stolen a march on its main rivals Xiaomi, OPPO, and Vivo. While the major Chinese smartphone vendors have launched Wi-Fi 7 compatible devices, the lack of assignment of 6 GHz spectrum for unlicensed use in China does appear to have held them back relative to brands such as Samsung and ASUS.

The outlook for Wi-Fi in the home

It’s clear from the gap between Wi-Fi and ethernet performance that ISPs need to do more to improve the customer experience for Wi-Fi users within the home. Part of the solution lies in rolling out more advanced generations of Wi-Fi technology, given Wi-Fi 4 and 5 remain the dominant technologies deployed globally. However, evidence linking increased adoption of Wi-Fi 6 to overall Wi-Fi closing the gap to ethernet performance is mixed, and validates the approach of ISPs looking to also offer mesh networking Wi-Fi solutions. Contact us to find out more about how Ookla Research can help you monitor the performance of your networks, and stay ahead of the competition.

About the Author

Mark Giles

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Sylwia Kechiche | November 23, 2023

Empowering Europe's Digital Ascent: Insights from Ookla's Gigabit Revolution Webinar

Ookla® has recently hosted a webinar on “Accelerating Europe’s Gigabit Revolution: The importance of high-speed internet in the digital era.” We gathered representatives from three European fiber providers, vertically integrated UK Internet Service Provider (ISP) Hyperoptic, Polish open-access fiber network provider, Fiberhost, and Spanish wholesale provider Onvia, to discuss their strategies and challenges related to fiber roll out and adoption. Industry experts from the European Competitive Telecommunications Association (ecta) and two research houses, Assembly Research and Omdia, also joined us.

European Commission’s Digital Decade 2030 Strategy

The European Commission’s Digital Decade 2030 strategy, also known as the Digital Compass, is an ambitious roadmap to speed up the digital transformation of Member States by 2030. One of its primary objectives is to enhance digital connectivity, with specific targets such as 100 Mbps services by 2025 and gigabit coverage for all EU households by 2030. We recently published an article to provide a reality check on the progress towards a Gigabit society. Our data suggests a wide gap between advertised and actual speeds for gigabit services, with speeds approaching 100 Mbps commonly seen by users. Despite this gap, our webinar participants were optimistic about achieving the Gigabit Society goal, with 71% supporting that view.

Chart of Percentage of Households Subscribing to Fixed Broadband of at Least 1 Gbps

The EU goal predominantly focuses on the availability aspect. However, it is important to note that having fiber networks available does not automatically equate to actual penetration or adoption rates, although it is a necessary prerequisite. Having physical accessibility to network services is, of course, a vital first step before actual usage, which is influenced by multiple factors such as affordability, awareness, and the perceived need for the service.

The European fiber network landscape

Stephen Wilson, Senior Principal Analyst from Omdia, provided an analyst’s perspective on how the fiber networks’ competitive landscape is evolving for alternative operators and incumbents. He stated that there has been a substantial increase in Fiber-To-The-Premises (FTTP) coverage, and the investment case for fiber has been spurred by the pandemic. Leading countries, including those in Iberia and Eastern Europe, are pushing coverage to 90% of premises or more, driven by a positive business case. While FTTH (Fiber to the Home) subscriber penetration is generally experiencing steady growth, country-level variations exist, with factors like digital literacy, existing broadband penetration, and competition playing crucial roles in the observed trends. Countries such as Spain and Romania have achieved significant FTTH penetration rates, while others like France have outperformed predictions, emphasizing the diverse dynamics influencing fiber adoption across Europe.

Importance of supportive regulatory framework

James Robinson, Senior Analyst from Assembly Research, highlighted three measures the European Commission is taking as it seeks to deliver against the Digital Decade’s connectivity targets: the draft Gigabit Recommendation, the proposed Gigabit Infrastructure Act, and a plan for a Digital Networks Act. Although broad industry support exists for the Gigabit Infrastructure Act (GIA), the draft Gigabit Recommendation has proven to be the most controversial. Both measures are still nevertheless expected to be finalized by the end of the year. The Digital Networks Act (DNA) will take longer to materialize, with a white paper not due until H1 2024. Despite its catchy title, the ‘DNA’ is unlikely to represent the urgent concrete action many operators had hoped to see from the Commission following the launch of the exploratory consultation back in February of this year.

Luc Hindryckx, Director General at ecta, expressed doubt about an investment gap that could endanger the 2030 targets. He suggested that some proposed legislation had been developed to support only a few operators rather than to promote competition. Hindryckx stressed the importance of bringing the Gigabit Infrastructure Act to “a good end” and ensuring the reduction of the timing for obtaining permits to deploy networks. He also pointed out that the GIA is complementary to the European Electronic Communication Code (ECCC), and its key elements include asymmetrical regulation and the Significant Market Power (SMP) regime. Overall, ecta emphasizes the importance of regulatory measures that foster competition, encourage investment, and create a level playing field, ultimately contributing to the successful deployment of gigabit connectivity and the Digital Decade 2030 objectives.

Succeeding in Rural Areas

Marta Wojciechowska, Chief Executive Officer at Fiberhost, has reported that the company has already met its goal of extending its fiber-optic network to over 1.3 million households by the end of the year. The company primarily focuses on underserved areas, where deployment costs tend to be higher and less predictable. While there are uncertainties regarding demand and fiber service uptake, there are unique benefits, including the low risk of overbuilding. However, the investment process varies significantly between urban and rural areas. In cities, one kilometer of infrastructure can connect one hundred to two hundred households, depending on the city’s size. In rural areas, connectivity extends to just seventeen households per kilometer.

Furthermore, up to 19 formal approvals may be required for infrastructure deployment, which extends the time to connect premises in rural areas to an impractical 24 months. The cost of connecting one household in these secluded “white spots” is over five hundred percent higher than in cities. Overcoming these challenges requires expertise, experience, and a collaborative approach, emphasizing the importance of partnerships with multiple stakeholders. These include local governments and subcontractors to achieve common goals in fiber network expansion.

Strategies for Expansion

Icíar Martínez, Markets and Product Director at Onivia, acknowledged they face similar challenges to Fiberhost but noted that their strategies for expanding the FTTH footprint might differ. Spain boasts close to 90% fiber optic coverage, thanks to private initiatives and government support. Their selective deployment focuses on rural and ultra-rural areas, addressing high customer interest. However, the cherry-picking strategy becomes expensive, impacting profitability, especially in densely competitive areas. Onivia aims to maximize capital returns by identifying key players, adopting XGPON technology for speeds up to 10 Gbps, and strategically balancing deployments in large cities and rural regions to optimize network utilization based on market demands.

On the other hand, Howard Jones, Head of Communications at Hyperoptic, noted that the Hyperoptic approach is distinct, focusing on urban areas with densely populated regions. The key lies in a granular business case approach, evaluating each deployment building by building and street by street. Hyperoptic’s philosophy centers on understanding that the network’s value lies in retaining customers, emphasizing a customer-centric business model. With a customer experience-oriented strategy, the ISP addresses challenges in the UK broadband market, historically marked by lower speeds and inadequate competition. By delivering a high-quality network, reliable service, and fair pricing policies, Jones highlighted that the company aims to set new standards in customer experience, achieving a 40% penetration rate within approximately a year of network deployment.

Addressing take-up challenges

Marta shared that Fiberhost’s network would not be deployed in white spot areas without EU funds. Fiberhost is the largest beneficiary of EU-funded grants, but this is just the beginning of the investment process. They need to “earn money, and for that, we need to have a good take-up rate.” She added that they must work hard to encourage people to join the fiber network. Their analysis showed that there is a slowdown in activations after ~40 %. While early adopters (47%) are willing to pay a premium for fiber internet, a substantial portion of potential users remain hesitant, contributing to the overall challenge of achieving a high take-up rate. The remaining 53% of households exhibit characteristics of an older demographic (above fifty-five) with limited internet usage, often for undemanding tasks. Their price sensitivity and lower discretionary income present a formidable barrier to higher adoption rates. As a result, Fiberhost adopts a multifaceted strategy, encompassing high-level engagement with Internet Service Providers (ISPs), targeted sales promotions, and educational initiatives. This strategic flexibility recognizes the absence of a one-size-fits-all solution and emphasizes the need for nuanced approaches tailored to the diverse challenges within each territory.

Iciar echoed this sentiment but also highlighted a need to implement a connectivity plan, not just deploy fiber, but also to digitalize rural areas. Access to a broadband network in rural households is essential, and so is educating people on the benefits of accessing new technologies. Onivia is exploring synergies with other technologies like 5G or satellite to extend broadband connectivity into areas that are difficult to reach. Iciar mentioned that working with local authorities is key to reusing existing infrastructure and avoiding building and disturbing neighborhoods with work.

Demand Aggregation and Competition

Stephen pointed out that the most successful operators are already in the 60-70% take-up rates of premises passed in countries like Norway, which points to demand aggregation being an important factor in getting pre-commitments before you roll out. Howard concluded, “Competition is the key to ensuring that these targets are met because I don’t believe that incumbents alone will do it. They need to be driven, and driven by competition.” He added the introduction of ‘One Touch Switch’ adds another layer of competition into the UK market and presents an opportunity to break the stranglehold of the big retail providers, who still often tend to sell FTTC (Fiber to the Cabinet), by moving a significant number of customers to alternate providers who are more likely to offer FTTP. This initiative is crucial, but what’s more important is the need to retain competition for everyone.

The journey towards Europe’s gigabit revolution is indeed multifaceted and involves various factors such as regulatory landscapes, diverse deployment strategies, financial dependencies, and the imperative of competition. Achieving the Digital Decade 2030 targets demands not just the availability of physical networks but also a concerted effort to address adoption challenges and ensure that the benefits of enhanced connectivity reach all corners of society. A shared commitment to realizing Europe’s digital potential is crucial, and a regulatory framework that fosters competition emerges as a common thread, underlining its pivotal role in driving investment, innovation, and equality. Moving forward, collaboration, adaptability, and a unified approach are essential to achieving Europe’s digital aspirations. From our side, we will continue to report what we see from Ookla® data in terms of users actually experiencing speeds.

See the full webinar recording here.

About the Author

Sylwia Kechiche

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Katie Jolly | January 21, 2021

New Year, Great Data: The Best Ookla Open Data Projects We’ve Seen So Far

When we announced Ookla® Open Datasets from Ookla For Good™ in October, we were hoping to see exciting projects that raise the bar on the conversation about internet speeds and accessibility — and you delivered. From analyses of internet inequity in the United States to measures of data affluence in India, today we’re highlighting four projects that really show what this data can do. We also have a new, simpler tutorial on how you can use this data for your own efforts to improve the state of networks worldwide.

Highlighting the digital divide in the U.S.

Jamie Saxon with the Center for Data and Computing at the University of Chicago married Ookla data on broadband performance with data from the American Community Survey to create interactive maps of the digital divide in 20 U.S. cities. These maps provide views into many variables that contribute to internet inequities.

Ookla_open_datasets_James_Saxon_0121-1

Building a data affluence map

Raj Bhagat P shows how different variables can be combined with this map of data affluence that combines data on internet speeds and device counts in India.

Ookla_open_datasets_Raj-Bhagat-P_0121-1

Internet speeds are beautiful

This map of fixed broadband speeds across Europe from Boris Mericskay shows that internet performance can be as visually stunning as a map of city lights.

Ookla_open_datasets_Boris-Mericskay_0121-1

Topi Tjunakov created a similar image of internet speeds in and around Japan.

Ookla_open_datasets_Topi-Tjunakov_0121-1

Use Ookla Open Datasets to make your own maps

This section will demonstrate a few possible ways to use Ookla Open Datasets using the United Kingdom as an example. The ideas can be adapted for any area around the world. This tutorial uses the R programming language, but there are also Python tutorials available in the Ookla Open Data GitHub repository.

library(tidyverse)
library(patchwork)
library(janitor)
library(ggrepel)
library(usethis)
library(lubridate)
library(colorspace)
library(scales)
library(kableExtra)
library(knitr)
library(sf)

# colors for plots
purple <- "#A244DA"
light_purple <- colorspace::lighten("#A244DA", 0.5)
green <- colorspace::desaturate("#2DE5D1", 0.2)
blue_gray <- "#464a62"
mid_gray <- "#ccd0dd"
light_gray <- "#f9f9fd"

# set some global theme defaults
theme_set(theme_minimal())
theme_update(text = element_text(family = "sans", color = "#464a62"))
theme_update(plot.title = element_text(hjust = 0.5, face = "bold"))
theme_update(plot.subtitle = element_text(hjust = 0.5))

Ookla Open Datasets include quarterly performance and test count data for both mobile networks and fixed broadband aggregated over all providers. The tests are binned into global zoom level 16 tiles which can be thought of as roughly a few football fields. As of today, all four quarters of 2020 are available and subsequent quarters will be added as they complete.

Administrative unit data

I chose to analyse the mobile data at the Nomenclature of Territorial Units for Statistics (NUTS) 3 level (1:1 million). These administrative units are maintained by the European Union to allow for comparable analysis across member states. NUTS 3 areas mean:

In England, upper tier authorities and groups of unitary authorities and districts
In Wales, groups of Principal Areas
In Scotland, groups of Council Areas or Islands Areas
In Northern Ireland, groups of districts

To make a comparison to the U.S. administrative structure, these can be roughly thought of as the size of counties. Here is the code you’ll want to use to download the NUTS shapefiles from the Eurostat site. Once the zipfile is downloaded you will need to unzip it again in order to read it into your R environment:

# create a directory called “data”
dir.create("data")
use_zip("https://gisco-services.ec.europa.eu/distribution/v2/nuts/download/ref-nuts-2021-01m.shp.zip", destdir = "data")

uk_nuts_3 <- read_sf("data/ref-nuts-2021-01m.shp/NUTS_RG_01M_2021_3857_LEVL_3.shp/NUTS_RG_01M_2021_3857_LEVL_3.shp") %>%
  filter(CNTR_CODE == "UK") %>%
  st_transform(4326) %>%
  clean_names() %>%
  mutate(urbn_desc = case_when( # add more descriptive labels for urban variable
    urbn_type == 1 ~ "Urban",
    urbn_type == 2 ~ "Intermediate",
    urbn_type == 3 ~ "Rural"
  ),
  urbn_desc = factor(urbn_desc, levels = c("Urban", "Intermediate", "Rural")))

# contextual city data
uk_cities <- read_sf("https://opendata.arcgis.com/datasets/6996f03a1b364dbab4008d99380370ed_0.geojson") %>%
  clean_names() %>%
  filter(fips_cntry == "UK", pop_rank <= 5)

ggplot(uk_nuts_3) +
  geom_sf(color = mid_gray, fill = light_gray, lwd = 0.08) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  labs(title = "United Kingdom",
       subtitle = "NUTS 3 Areas") +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank())

plot_uk-1-1

Adding data from Ookla Open Datasets

You’ll want to crop the global dataset to the bounding box of the U.K. This will include some extra tiles (within the box but not within the country, i.e. some of western Ireland), but it makes the data much easier to work with later on.

uk_bbox <- uk_nuts_3 %>%
  st_union() %>% # otherwise would be calculating the bounding box of each individual area
  st_bbox()

Each of the quarters are stored in separate shapefiles. You can read them in one-by-one and crop them to the U.K. box in the same pipeline.

# download the data with the following code:

use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=1/2020-01-01_performance_mobile_tiles.zip", destdir = "data")
use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=2/2020-04-01_performance_mobile_tiles.zip", destdir = "data")
use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=3/2020-07-01_performance_mobile_tiles.zip", destdir = "data")
use_zip("https://ookla-open-data.s3.amazonaws.com/shapefiles/performance/type=mobile/year=2020/quarter=4/2020-10-01_performance_mobile_tiles.zip", destdir = "data")

# and then read in those downloaded files
mobile_tiles_q1 <- read_sf("data/2020-01-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)
mobile_tiles_q2 <- read_sf("data/2020-04-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)
mobile_tiles_q3 <- read_sf("data/2020-07-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)
mobile_tiles_q4 <- read_sf("data/2020-10-01_performance_mobile_tiles/gps_mobile_tiles.shp") %>%
  st_crop(uk_bbox)

As you see, the tiles cover most of the area, with more tiles in more densely populated areas. (And note that you still have tiles included that are outside the boundary of the area but within the bounding box.)

ggplot(uk_nuts_3) +
  geom_sf(color = mid_gray, fill = light_gray, lwd = 0.08) +
  geom_sf(data = mobile_tiles_q4, fill = purple, color = NA) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  labs(title = "United Kingdom",
       subtitle = "Ookla® Open Data Mobile Tiles, NUTS 3 Areas") +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank())

tile_map-1-3

Now that the cropped tiles are read in, you’ll use a spatial join to determine which NUTS 3 area each tile is in. In this step, I am also reprojecting the data to the British National Grid (meters). I’ve also added a variable to identify the time period (quarter).

tiles_q1_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>% # British National Grid
  st_join(mobile_tiles_q1 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-01-01")

tiles_q2_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>%
  st_join(mobile_tiles_q2 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-04-01")

tiles_q3_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>%
  st_join(mobile_tiles_q3 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-07-01")

tiles_q4_nuts <- uk_nuts_3 %>%
  st_transform(27700) %>%
  st_join(mobile_tiles_q4 %>% st_transform(27700), left = FALSE) %>%
  mutate(quarter_start = "2020-10-01")

In order to make the data easier to work with, combine the tiles into a long dataframe with each row representing one tile in one quarter. The geometry now represents the NUTS region, not the original tile shape.

tiles_all <- tiles_q1_nuts %>%
  rbind(tiles_q2_nuts) %>%
  rbind(tiles_q3_nuts) %>%
  rbind(tiles_q4_nuts) %>%
  mutate(quarter_start = ymd(quarter_start)) # convert to date format

With this dataframe, you can start to generate some aggregates. In this table you’ll include the tile count, test count, quarter and average download and upload speeds.

Exploratory data analysis

aggs_quarter <- tiles_all %>%
  st_set_geometry(NULL) %>%
  group_by(quarter_start) %>%
  summarise(tiles = n(),
            avg_d_mbps = weighted.mean(avg_d_kbps / 1000, tests), # I find Mbps easier to work with
            avg_u_mbps = weighted.mean(avg_u_kbps / 1000, tests),
            tests = sum(tests)) %>%
  ungroup()


knitr::kable(aggs_quarter) %>%
  kable_styling()

aggregates_table_kj

We can see from this table that both download and upload speeds increased throughout the year, with a small dip in upload speeds in Q2. Next, you’ll want to plot this data.

ggplot(aggs_quarter, aes(x = quarter_start)) +
  geom_point(aes(y = avg_d_mbps), color = purple) +
  geom_line(aes(y = avg_d_mbps), color = purple, lwd = 0.5) +
  geom_text(aes(y = avg_d_mbps - 2, label = round(avg_d_mbps, 1)), color = purple, size = 3, family = "sans") +
  geom_text(data = NULL, x = ymd("2020-02-01"), y = 47, label = "Download speed", color = purple, size = 3, family = "sans") +
  geom_point(aes(y = avg_u_mbps), color = light_purple) +
  geom_line(aes(y = avg_u_mbps), color = light_purple, lwd = 0.5) +
  geom_text(aes(y = avg_u_mbps - 2, label = round(avg_u_mbps, 1)), color = light_purple, size = 3, family = "sans") +
  geom_text(data = NULL, x = ymd("2020-02-05"), y = 14, label = "Upload speed", color = light_purple, size = 3, family = "sans") +
  labs(y = "", x = "Quarter start date",
       title = "Mobile Network Performance, U.K.",
       subtitle = "Ookla® Open Datasets | 2020") +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1)) +
  scale_y_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  scale_x_date(date_labels = "%b %d")

line_up_down-1

Examining test counts

We also saw above that the number of tests decreased between Q1 and Q2 and then peaked in Q3 at a little over 700,000 before coming back down. The increase likely followed resulted from interest in network performance during COVID-19 when more people started working from home. This spike is even more obvious in chart form.

ggplot(aggs_quarter, aes(x = quarter_start)) +
  geom_point(aes(y = tests), color = purple) +
  geom_line(aes(y = tests), color = purple, lwd = 0.5) +
  geom_text(aes(y = tests - 6000, label = comma(tests), x= quarter_start + 5), size = 3, color = purple) +
  labs(y = "", x = "Quarter start date",
       title = "Mobile Test Count, U.K.",
       subtitle = "Ookla® Open Datasets | 2020") +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        axis.text = element_text(color = blue_gray)) +
  scale_y_continuous(labels = comma) +
  scale_x_date(date_labels = "%b %d")

line_tests-1-1

Data distribution

Next, I wanted to check the distribution of average download speeds.

ggplot(tiles_all) + 
  geom_histogram(aes(x = avg_d_kbps / 1000, group = quarter_start), size = 0.3, color = light_gray, fill = green) + 
  scale_x_continuous(labels = label_number(suffix = " Mbps", accuracy = 1)) +
  scale_y_continuous(labels = comma) +
  facet_grid(quarter_start ~ .) +
  theme(panel.grid.minor = element_blank(), 
        panel.grid.major = element_blank(), 
        axis.title.x = element_text(hjust=1),
        axis.text = element_text(color = blue_gray),
        strip.text.y = element_text(angle = 0, color = blue_gray)) + 
  labs(y = "", x = "", title = "Mobile Download Speed Distribution by Tile, U.K.", 
       subtitle = "Ookla® Open Datasets | 2020")

histogram-1-1

The underlying distribution of average download speeds across the tiles has stayed fairly stable.

Mapping average speed

Making a quick map of the average download speed in each region across the U.K. is relatively simple.

# generate aggregates table
nuts_3_aggs <- tiles_all %>%
  group_by(quarter_start, nuts_id, nuts_name, urbn_desc, urbn_type) %>%
  summarise(tiles = n(),
            avg_d_mbps = weighted.mean(avg_d_kbps / 1000, tests), # I find Mbps easier to work with
            avg_u_mbps = weighted.mean(avg_u_kbps / 1000, tests),
            tests = sum(tests)) %>%
  ungroup()

ggplot(nuts_3_aggs %>% filter(quarter_start == "2020-10-01")) +
  geom_sf(aes(fill = avg_d_mbps), color = blue_gray, lwd = 0.08) +
  scale_fill_stepsn(colors = RColorBrewer::brewer.pal(n = 5, name = "BuPu"), labels = label_number(suffix = " Mbps"), n.breaks = 4, guide = guide_colorsteps(title = "")) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.text = element_text(color = blue_gray),
        axis.text = element_blank()) +
  labs(title = "Mobile Download Speed, U.K.", subtitle = "Ookla® Open Datasets | Q4 2020")

choropleth-1-1

As you can see, the areas around large cities have faster download speeds on average and the lowest average download speeds are typically in more rural areas.

Rural and urban analysis

People are often interested in the difference between mobile networks in urban and rural areas. The Eurostat NUTS data includes an urban indicator with three levels: rural, intermediate and urban. This typology is determined primarily by population density and proximity to a population center.

ggplot(uk_nuts_3) +
  geom_sf(aes(fill = urbn_desc), color = light_gray, lwd = 0.08) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = "#1a1b2e", 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = "U.K., NUTS 3 Areas") +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top")

rural_urban_reference-1

Data distribution overall and over time

When you aggregate by the urban indicator variable different patterns come up in the data.

# generate aggregates table
rural_urban_aggs <- tiles_all %>%
  st_set_geometry(NULL) %>%
  group_by(quarter_start, urbn_desc, urbn_type) %>%
  summarise(tiles = n(),
            avg_d_mbps = weighted.mean(avg_d_kbps / 1000, tests), # I find Mbps easier to work with
            avg_u_mbps = weighted.mean(avg_u_kbps / 1000, tests),
            tests = sum(tests)) %>%
  ungroup()

As you might expect, the download speeds during Q4 are faster in urban areas than in rural areas – with the intermediate ones somewhere in between. This pattern holds for other quarters as well.

ggplot(rural_urban_aggs %>% filter(quarter_start == "2020-10-01"), aes(x = avg_d_mbps, y = urbn_desc, fill = urbn_desc)) +
  geom_col(width = .3, show.legend = FALSE) +
  geom_jitter(data = nuts_3_aggs, aes(x = avg_d_mbps, y = urbn_desc, color = urbn_desc), size = 0.7) + 
  geom_text(aes(x = avg_d_mbps - 4, label = round(avg_d_mbps, 1)), family = "sans",  size = 3.5, color = blue_gray) +
  scale_fill_manual(values = c(purple, light_purple, green)) +
  scale_color_manual(values = darken(c(purple, light_purple, green))) +
  scale_x_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "none",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "", 
       title = "Mobile Download Speed Distribution by NUTS 3 Area, U.K.", 
       subtitle = "Ookla® Open Datasets | 2020")

rural_urban_bar-1-2
Interestingly though, the patterns differ when you look at a time series plot. Urban mobile networks steadily improve, while the intermediate and rural areas saw slower average download speeds starting in Q2 before going back up after Q3. This is likely the result of increased pressure on the networks during stay-at-home orders (although this graph is not conclusive evidence of that).

ggplot(rural_urban_aggs) +
  geom_line(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc)) +
  geom_point(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc)) +
  # urban label
  geom_text(data = NULL, x = ymd("2020-02-01"), y = 50, label = "Urban", color = purple, family = "sans", size = 3) +
  # intermediate label
  geom_text(data = NULL, x = ymd("2020-02-15"), y = 35, label = "Intermediate", color = light_purple, family = "sans", size = 3) +
  # rural label
  geom_text(data = NULL, x = ymd("2020-01-15"), y = 26, label = "Rural", color = green, family = "sans", size = 3) +
  scale_color_manual(values = c(purple, light_purple, green)) +
  scale_x_date(date_labels = "%b %d") +
  scale_y_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "none",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "Quarter start date", 
       title = "Mobile Download Speed by NUTS 3 Urban-Rural Type, U.K.", 
       subtitle = "Ookla® Open Datasets | 2020")

rural_urban_line-1-1

When you repeat the same plot but map the test count to the site of the point, you can see why the overall download speed increased steadily. The number of tests in urban areas is much higher than in intermediate and rural areas, thus pulling up the overall average.

ggplot(rural_urban_aggs) +
  geom_line(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc)) +
  geom_point(aes(x = quarter_start, y = avg_d_mbps, color = urbn_desc, size = tests)) +
  # urban label
  geom_text(data = NULL, x = ymd("2020-02-01"), y = 50, label = "Urban", color = purple, family = "sans", size = 3) +
  # intermediate label
  geom_text(data = NULL, x = ymd("2020-02-15"), y = 35, label = "Intermediate", color = light_purple, family = "sans", size = 3) +
  # rural label
  geom_text(data = NULL, x = ymd("2020-01-15"), y = 26, label = "Rural", color = green, family = "sans", size = 3) +
  scale_color_manual(values = c(purple, light_purple, green)) +
  scale_x_date(date_labels = "%b %d") +
  scale_y_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "none",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "Quarter start date", 
       title = ("Mobile Download Speed by NUTS 3 Urban-Rural Type, U.K."), 
       subtitle = "Ookla® Open Datasets | 2020",
       caption = "Circle size indicates test count")

rural_urban_line_size-1-1

Spotlighting regional variances

Parsing the data by specific geographies can reveal additional information.

bottom_20_q4 <- nuts_3_aggs %>% 
  filter(quarter_start == "2020-10-01") %>% 
  top_n(n = -20, wt = avg_d_mbps) %>%
  mutate(nuts_name = fct_reorder(factor(nuts_name), -avg_d_mbps))

map <- ggplot() +
  geom_sf(data = uk_nuts_3, fill = light_gray, color = mid_gray, lwd = 0.08) +
  geom_sf(data = bottom_20_q4, aes(fill = urbn_desc), color = mid_gray, lwd = 0.08, show.legend = FALSE) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = NULL,
       subtitle = NULL) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top")

barplot <- ggplot(data = bottom_20_q4, aes(x = avg_d_mbps, y = nuts_name, fill = urbn_desc)) +
  geom_col(width = .5) +
  scale_fill_manual(values = c(purple, light_purple, green), guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5, title = NULL)) +
  scale_x_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "top",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "", 
       title = ("Slowest 20 NUTS 3 Areas by Download Speed, U.K."), 
       subtitle = "Ookla® Open Datasets | Q4 2020")

# use patchwork to put it all together
barplot + map

bottom_20-1-2
Among the 20 areas with the lowest average download speed in Q4 2020 there were three urban areas and six intermediate. The rest were rural.

top_20_q4 <- nuts_3_aggs %>% 
  filter(quarter_start == "2020-10-01") %>% 
  top_n(n = 20, wt = avg_d_mbps) %>%
  mutate(nuts_name = fct_reorder(factor(nuts_name), avg_d_mbps))

top_map <- ggplot() +
  geom_sf(data = uk_nuts_3, fill = light_gray, color = mid_gray, lwd = 0.08) +
  geom_sf(data = top_20_q4, aes(fill = urbn_desc), color = mid_gray, lwd = 0.08, show.legend = FALSE) +
  geom_text_repel(data = uk_cities, 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = blue_gray, 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = NULL,
       subtitle = NULL) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top")

top_barplot <- ggplot(data = top_20_q4, aes(x = avg_d_mbps, y = nuts_name, fill = urbn_desc)) +
  geom_col(width = .5) +
  scale_fill_manual(values = c(purple, light_purple, green), guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5, title = NULL)) +
  scale_x_continuous(labels = label_number(suffix = " Mbps", scale = 1, accuracy = 1), breaks = c(50, 100)) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank(),
        axis.title.x = element_text(hjust=1),
        legend.position = "top",
        axis.text = element_text(color = blue_gray)) +
  labs(y = "", x = "", 
       title = "Fastest 20 NUTS 3 Areas by Mobile Download Speed, U.K.", 
       subtitle = "Ookla® Open Datasets | Q4 2020")

top_london <- ggplot() +
  geom_sf(data = uk_nuts_3 %>% filter(str_detect(fid, "UKI")), fill = light_gray, color = mid_gray, lwd = 0.08) +
  geom_sf(data = top_20_q4 %>% filter(str_detect(nuts_id, "UKI")), aes(fill = urbn_desc), color = mid_gray, lwd = 0.08, show.legend = FALSE) +
  geom_text_repel(data = uk_cities %>% filter(city_name == "London"), 
                           aes(label = city_name, geometry = geometry), 
                           family = "sans", 
                           color = "black", 
                           size = 2.2, 
                           stat = "sf_coordinates",
                           min.segment.length = 2) +
  scale_fill_manual(values = c(purple, light_purple, green), name = "", guide = guide_legend(direction = "horizontal", label.position = "top", keywidth = 3, keyheight = 0.5)) +
  labs(title = NULL,
       subtitle = NULL) +
  theme(panel.grid.major = element_blank(),
        panel.grid.minor = element_blank(),
        axis.text = element_blank(),
        axis.title = element_blank(),
        legend.position = "top",
        panel.border = element_rect(colour = blue_gray, fill=NA, size=0.5))

top_map_comp <- top_map + inset_element(top_london, left = 0.6, bottom = 0.6, right = 1, top = 1)

top_barplot + top_map_comp

top_20-1-1
Meanwhile, all of the fastest 20 NUTS 3 areas were urban.

What else you can do with this data

Don’t forget there are also more tutorials with examples written in Python and R. Aside from what I showed here, you could do an interesting analysis looking at clustering patterns, sociodemographic variables and other types of administrative units like legislative or school districts.

We hope this tutorial will help you use Ookla’s open data for your own projects. Please tag us if you share your projects on social media using the hashtag #OoklaForGood so we can learn from your analyses.

About the Author

Katie Jolly

| More Articles

Ookla Research™ Articles

Isla McKetta | March 14, 2019

Ditch the Lag: Cities with Great Gaming Culture and Low Ping

Yes, you can game from anywhere with an internet connection. But if you’re at all competitive, it’s nice to play from somewhere with low ping and fast internet speeds. Plus when you need to leave the house, it’s extra nice to know you’re also surrounded by gamer culture. We’ve examined February 2019 Speedtest results in 35 cities that are known for their esports events, gaming conferences, game companies and more to find out who has the advantage and ranked them based on their ping.

The top contenders

Eleven_Gaming_Cities_0219

First place Bucharest, Romania is home to super-low ping, a lightning fast download speed and a thriving gaming culture. From Bucharest Gaming Week (which includes the CS:GO Southeast Europe Championship and the FIFA National Tournament) to their numerous local game studios, Bucharest is a great place to be a gamer whether you’re online or out and about.

The next five gaming cities with the lowest pings are all in Asia. Hangzhou, China comes in second overall with a fast ping and world-class download speeds. This city is so devoted to its gamers that it opened a $280 million gaming “city” in 2018 and plans 14 new esports arenas before 2022. Coming in third, Chengdu, China has an equally low ping to our first two contenders and serves as one of two host locations in China for the Global Mobile Game Confederation (GMGC). Both Hangzhou and Chengdu are also franchise holders in the Overwatch League, giving local gaming fans something to cheer about. Fourth place Singapore, host of the 5th Annual GameStart Convention in October 2018, had only a slightly slower ping than the first four cities and the fastest download speed of any of the cities we considered.

South Korea is home to the fifth and sixth best cities for gamers. A satellite city of Seoul, Seongnam-si boasts the Pangyo Techno Valley (a.k.a. the Silicon Valley of Korea) and numerous game development companies. Perfect for a city with a 9 ms ping. Though Incheon’s ping was a little slower at 12 ms, gamers there can console themselves with the city’s gamer cred — the 2018 League of Legends World Championship was held in Incheon’s Munhak Stadium.

Coming in at number seven, Budapest, Hungary is an emerging game city, having hosted its first big esports event (the V4 Future Sports Festival) in 2018, but a 12 ms ping makes them a strong contender. More established Malmö, Sweden is number eight with a slightly slower average download speed but the city is headquarters to Massive Entertainment, creators of Tom Clancy’s The Division series, Far Cry 3, Assassin’s Creed: Revelations and many more.

Vancouver, Canada, North America’s only qualifier for the top gaming cities list, comes in at number nine with a 12 ms ping and many gaming companies including the Canadian arms of Nintendo of Canada and EA (Electronic Arts). We included both Shanghai, China and Moscow, Russia on the top gamer cities list as both had a 12 ms ping as well, though the internet speeds in Shanghai are superior. Shanghai will also host the International Dota 2 in 2019 while Moscow is known for Epicenter.

The rest of the pack

Notably absent from the list above is most of the western hemisphere. Cities in North America were held back by their high pings. Cities in South America suffered from high pings and also slow internet speeds — something that esports leagues have complained is a barrier to investment.

Our full list of gaming cities provides wider geographical representation, even if the internet performance is not always as stellar. You’ll find Los Angeles in 27th place, behind Seattle, Boston and Las Vegas. And São Paulo, Brazil has the best showing in Latin America at 23rd.

**Internet Performance in 35 Cities with a Gaming Culture**
Speedtest Results | February 2019
City	Ping (ms)	Mean Download (Mbps)	Mean Upload (Mbps)
Bucharest, Romania	8	172.13	126.57
Hangzhou, China	8	125.93	29.54
Chengdu, China	8	101.92	33.80
Singapore	9	196.43	200.08
Seongnam-si, South Korea	9	155.25	114.83
Incheon, South Korea	12	139.84	102.91
Budapest, Hungary	12	132.72	54.46
Malmö, Sweden	12	126.28	105.67
Vancouver, Canada	12	117.55	50.23
Shanghai, China	12	75.14	30.06
Moscow, Russia	12	64.56	63.59
Oslo, Norway	13	115.46	69.03
Hong Kong, Hong Kong (SAR)	14	167.59	161.14
Zürich, Switzerland	14	144.36	109.39
Seattle, United States	15	138.50	79.88
Stockholm, Sweden	15	134.16	93.83
Auckland, New Zealand	15	92.05	53.30
Toronto, Canada	16	134.75	67.42
Boston, United States	17	152.42	60.87
Las Vegas, United States	17	141.69	41.22
Chennai, India	17	48.40	42.93
Cologne, Germany	18	63.77	18.36
São Paulo, Brazil	18	46.43	21.57
Jakarta, Indonesia	18	17.88	10.21
Mumbai, India	19	23.40	19.26
Paris, France	20	161.04	93.68
Los Angeles, United States	20	121.00	23.57
London, United Kingdom	20	63.58	23.18
Rio de Janeiro, Brazil	20	36.50	13.33
Buenos Aires, Argentina	21	34.31	6.40
Katowice, Poland	22	83.99	20.91
Mexico City, Mexico	25	37.66	15.39
Sydney, Australia	25	34.20	9.61
Santiago, Chile	26	56.13	18.49
Tokyo, Japan	28	99.24	101.90

Of course, die-hard gamers will know that a low ping in your city won’t necessarily save you if you’re playing on a distant server.

What’s the ping like in your city? Take a Speedtest and see if your connection is hurting your gameplay.

About the Author

Isla McKetta

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Isla McKetta | November 15, 2023

Your Black Friday/Cyber Monday Guide to iPhone 15 and Samsung Galaxy Z Fold5 and Flip5 Performance

To upgrade or not to upgrade, with Black Friday and Cyber Monday deals on the latest iPhone and Samsung devices on the horizon you may be asking yourself just that question. We analyzed data from Speedtest Intelligence® in 13 major markets to see how well the Apple iPhone 15 devices and the Samsung Galaxy Z Fold5 and Flip5 models are performing in comparison to last year’s models over 5G to help you make an informed decision. For details on performance by Samsung Galaxy S23 models, read our analysis from earlier this year. We’re especially interested in seeing if technical improvements on iPhone 15 models including support for WiFi 6E drive better performance.

Data for iPhone models is provided for the period from September 22-October 20, 2023, while data for the Samsung models is for the period from August 11-October 20, 2023. Keep in mind that device data differs across markets due to a variety of factors, including: 5G investments by governments and mobile operators, different 5G spectrum allocations, and mobile 5G plans. As many of these devices are very new, the sample counts in some countries are still low so the statistical ranges of expected performance are wider for the newer devices than the older models.

Half of models surveyed worth the upgrade in Australia

In Australia, two out of four iPhone 15 models showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period. Speedtest Intelligence reveals the iPhone 15 Pro and the iPhone 15 Pro Max both had a 14% better download speed than their prior year counterparts. There was no statistical winner for the iPhone standard model or the iPhone Plus in Australia during this period.

The Galaxy Z Flip5 had a 30% better download speed than the Galaxy Z Flip4 during the August 11-October 20, 2023 period in Australia, while there was no statistical winner for the Galaxy Z Fold.

Recommendation: Depending on your model of choice, only half the devices surveyed merit an upgrade based on performance alone in Australia.

iPhones mostly worth the upgrade in Brazil

Three out of four iPhone 15 models in Brazil showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period. Speedtest Intelligence showed the iPhone 15 had a better download speed than the iPhone 14, with the iPhone 15 Pro Max having a 8% better download speed than the iPhone 14 Pro Max, and the iPhone 15 Pro showing a 1% better download speed than the iPhone 14 Pro. There was no statistical winner for the iPhone Plus in Brazil during this period.

There was no statistical winner for 5G median download speed during the August 11-October 20, 2023 period for the Galaxy Z Flip or the Galaxy Z Fold in Brazil.

Recommendation: iPhone users in Brazil should consider an upgrade based on performance, while Samsung Galaxy fans only need to upgrade if they are looking for feature improvements.

All iPhones show improvement over prior models in Canada

All four iPhone 15 models in Canada showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period. Data from Speedtest Intelligence demonstrated the iPhone 15 had a better download speed than the iPhone 14, with the iPhone 15 Pro Max having a 26% better download speed than the iPhone 14 Pro Max, the iPhone 15 Pro Plus showed a 12% better download speed than the iPhone 14 Pro Plus, and the iPhone 15 Pro had an 8% better download speed than the iPhone 14 Pro.

The Galaxy Z Fold5 had a better download speed than the Galaxy Z Fold4 during the August 11-October 20, 2023 period in Canada, while there was no statistical winner for the Galaxy Z Flip.

Recommendation: iPhone users in Canada should consider an upgrade based on performance, while Samsung Galaxy fans should make a decision based on which model they’re considering.

Three iPhone models show decent improvement over prior versions in France

Three out of four iPhone 15 models in France showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period. Speedtest Intelligence reveals the iPhone 15 and the iPhone 15 Pro Max both had 18% better download speeds than their respective prior year models. The iPhone 15 Pro had a 5% better download speed than the iPhone 14 Pro. There was no statistical winner for the iPhone Plus in France during this period.

There was no statistical winner for 5G median download speed during the August 11-October 20, 2023 period for the Galaxy Z Flip or the Galaxy Z Fold in France.

Recommendation: iPhone users in France should consider an upgrade based on performance, and Samsung Galaxy users only need to upgrade if they are looking for feature improvements.

Galaxy Z Fold5 shows some improvements in Germany

Two out of four iPhone 15 models showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents in Germany during the September 22-October 20, 2023 period. Speedtest Intelligence reveals slight improvements with the iPhone 15 Pro Max having a 6% better download speed than the iPhone 14 Pro Max and the iPhone 15 Pro having a 2% better download speed than the iPhone 14 Pro. There was no statistical winner for the iPhone standard model or the iPhone Plus in Germany during this period.

The Galaxy Z Fold5 had a 13% better download speed than the Galaxy Z Fold4 during the August 11-October 20, 2023 period in Germany, while there was no statistical winner for the Galaxy Z Flip.

Recommendation: Apple users won’t see major performance improvements from the new models, but the Galaxy Z Fold5 is worth the upgrade on performance alone.

India sees better performance on three iPhone models

Three out of four iPhone 15 models in India showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period. Speedtest Intelligence showed the iPhone 15, iPhone 15 Pro, and the iPhone 15 Plus had better speeds than their respective prior models. There was no statistical winner for the iPhone Pro Max in India during this period.

There was no statistical winner for 5G median download speed during the August 11-October 20, 2023 period for the Galaxy Z Flip or the Galaxy Z Fold in India.

Recommendation: Indian iPhone users should consider an upgrade based on performance, and Samsung Galaxy users only need to upgrade if they are looking for feature improvements.

No significant performance gains on new devices in the Philippines

Neither the iPhone 15 Pro nor the iPhone 15 Pro Max had a statistically better median download speed over 5G than their prior year models during the September 22-October 20, 2023 period in the Philippines. There were not enough samples to properly assess the performance of the other two iPhone models.

Likewise, there was no statistical winner for 5G median download speed during the August 11-October 20, 2023 period for the Galaxy Z Flip or the Galaxy Z Fold in the Philippines.

Recommendation: Filipino consumers looking to upgrade their phones to the latest models will have to look for reasons beyond performance.

Galaxy Z Fold5 sees performance improvement in South Korea

Mobile speeds in South Korea are already fast with a top 10 performance on the Speedtest Global Index™ as of September 2023. New phones may not push performance boosts, though, as Speedtest Intelligence data did not show significant increases in median download speed over 5G for the iPhone 15 Pro or the iPhone 15 Pro Max in South Korea during the September 22-October 20, 2023 period. However, the iPhone 15 Pro Max had a 16% better upload speed than the iPhone 14 Pro Max. There were not enough samples to properly assess the performance of the other two iPhone models.

On the other hand, the Galaxy Z Fold5 had a 10% better download speed than the Galaxy Z Fold4 during the August 11-October 20, 2023 period in South Korea, while there was no statistical winner for the Galaxy Z Flip.

Recommendation: If South Korean consumers are looking for better performance, upgrading from the Galaxy Z Fold4 to the Galaxy Z Fold5 is worth looking into.

Spain sees major increases in iPhone speed

Three iPhone 15 models in Spain showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period, and the improvements in performance were mostly greater than we saw in other countries, with the exception of the United States. Speedtest Intelligence reveals the iPhone 15 Pro had a 40% better download speed than the iPhone 14 Pro, the iPhone 15 Pro Max had a 36% better download speed than the iPhone 14 Pro Max, and the iPhone 15 had an 11% better download speed than the iPhone 14. There were not enough samples to properly assess the performance of the iPhone Plus.

There were not enough samples to evaluate the Galaxy Z Flip or the Galaxy Z Fold during the August 11-October 20, 2023 period in Spain.

Recommendation: Spanish iPhone fans should definitely upgrade their devices while Samsung users can hold off for now.

Unbeatable performance in U.A.E. makes upgrades unnecessary

While Speedtest Intelligence data did not show significant increases in median download speed over 5G for the iPhone 15 Pro or the iPhone 15 Pro Max during the September 22-October 20, 2023 period, performance likely isn’t a concern in the United Arab Emirates, whose blisteringly fast download speeds topped the Speedtest Global Index™ in September 2023. There were not enough samples to properly assess the performance of the other two iPhone models.

Similarly, there was no statistical winner for 5G median download speed during the August 11-October 20, 2023 period for the Galaxy Z Fold in the U.A.E., and there were not enough samples to evaluate the Galaxy Z Flip.

Recommendation: Consumers in the U.A.E. should upgrade if they are looking for the new features on the new phone models, but upgrades for performance are unnecessary.

iPhone upgrades are the way to go in the U.K.

All four iPhone 15 models in the United Kingdom showed median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period. Speedtest Intelligence reveals the iPhone 15 had a 16% better download speed than the iPhone 14, the iPhone 15 Pro had a 14% better download speed than the iPhone 14 Pro, iPhone 15 Pro Max had a 10% better download speed than the iPhone 14 Pro Max, and iPhone 15 Plus has a 4% better download speed than the iPhone 14 Plus.

There was no statistical winner for 5G median download speed during the August 11-October 20, 2023 period for the Galaxy Z Flip or the Galaxy Z Fold in the U.K.

Recommendation: iPhone users in the U.K. should see performance improvements that make upgrading to the latest models worthwhile. Samsung Galaxy users only need to upgrade if they are looking for new features.

U.S. consumers see some of the highest improvements when upgrading to new iPhone models

Not only did all four iPhone 15 models in the United States show median 5G download speeds that were significantly faster than their iPhone 14 equivalents during the September 22-October 20, 2023 period, the improvements in performance were greater than we saw in most other countries, with the exception of Spain. Speedtest Intelligence showed the iPhone 15 Plus had a 54% better download speed than the iPhone 14 Plus, the iPhone 15 had a 45% better download speed than the iPhone 14, iPhone 15 Pro Max had a 27% better download speed than the iPhone 14 Pro Max, and iPhone 15 Pro has a 25% better download speed than the iPhone 14 Pro.

Samsung users also saw increased median download speeds over 5G when using the newer models during the August 11-October 20, 2023 period in the U.S. The Galaxy Z Flip5 had a 15% better download speed than the Galaxy Z Flip4, and the Galaxy Z Fold5 had a 10% better download speed than the Galaxy Z Fold4.

Recommendation: Upgrades for all this holiday season!

No performance boost on iPhone 15 Pro Max in Vietnam

The iPhone 15 Pro Max did not have a statistically better median download speed over 5G than the iPhone 14 Pro Max during the September 22-October 20, 2023 period in Vietnam. There were not enough samples to properly assess the performance of the other three iPhone models. Likewise, there were not enough samples to evaluate the Galaxy Z Flip or the Galaxy Z Fold.

Recommendation: Vietnamese consumers don’t need to upgrade to newer models on performance alone.

Ookla will continue evaluating device performance

We’re excited by the number of countries where mobile device performance increased with the new models and even more excited by the countries where performance is so fast that consumers can look to new modes of connectivity. Even if your country didn’t see the speed boosts you were hoping for, don’t hold back on upgrading if you want to treat yourself or a loved one based on any other number of reasons. Remember to download the iOS or Android Speedtest® app on any new devices to make sure your mobile operator is delivering the speeds you expect.

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Isla McKetta

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Sylwia Kechiche | October 23, 2023

A Reality Check on the Progress toward a Gigabit Society

The European Commission has set forth an ambitious goal of achieving a Digital Decade 2030 strategy, also known as the Digital Compass. The aim is to expedite the digital transformation of Member States by 2030. One of the primary objectives of this strategy is to improve digital connectivity, which will be measured through specific targets such as 100 Mbps services by 2025 and gigabit coverage to all EU households by 2030. In this article, we will discuss the progress made so far, the disparities in user experience, and the challenges that need to be addressed to achieve Europe’s connectivity goals.

Key messages

Digital Decade Ambition: The ambitious goals of the EU’s Digital Decade strategy are indeed lofty. Broadband services might promise speeds in excess of 1 Gbps, but the reality is that users rarely experience that level of speed. However, while the gap between advertised speeds and actual speeds for gigabit services is wide, speeds approaching 100 Mbps are far more common.
Median Download Speeds and Infrastructure Development: Several European countries are making substantial progress in offering high-speed broadband. Denmark, Spain, France, and Romania have notably fast median download speeds, primarily due to their fiber-to-the-home (FTTH) infrastructure investments. The type of broadband technology used in those countries (and others) significantly influences the gap between download and upload speeds, with fiber-based networks showing more balanced speeds.
AltNets Drive Fiber Adoption: Alternative network providers (AltNets) play a vital role in accelerating fiber adoption and addressing challenges mainstream ISPs face. Their role varies across countries and regions.
Take-up rates remain a challenge: With the completion of fiber rollout in several countries, the focus has now shifted towards promoting fiber subscriptions. However, there are challenges that persist, such as consumer reluctance and the need for incentives. A survey conducted in rural France revealed that 42% of the respondents found their current internet sufficient, while 37% said that they would be encouraged to upgrade if offered incentives.

You can also register for our November 8 webinar, where a panel of industry experts will discuss how Europe can accelerate the expansion of gigabit-capable infrastructure. Register now.

On the road to 100 Mbps

The European Commission aims to ensure that all European households, businesses, and public institutions should have access to “high internet speeds” of at least 100 Mbps by year-end 2025. The EU is showing progress in terms of achieving that target. According to Broadband Coverage in Europe 2022, 86.6% of EU households were within 100 Mbps + coverage, meaning they had access to broadband services capable of providing at least 100 Mbps download speeds.

While having networks available does not automatically equate to real penetration or adoption rates, it is an important prerequisite. Physical accessibility to network services is a vital first step before actual usage, which is influenced by factors such as affordability, awareness, and the perceived need for the service.

According to the Digital Economy and Society Index DESI 2023 dashboard for the Digital Decade, 55.08% of EU households had already subscribed to fixed broadband services with internet speeds of at least 100 Mbps. While this rate of subscribers is significant and an indicator of the EC’s ongoing progress, the region is still far from achieving its goal of universal, 100 Mbps coverage by 2025. Some countries like Spain, Sweden, and Romania, where over 80% of households subscribe to broadband exceeding 100 Mbps, have already made significant progress in terms of fiber coverage.

However, in those countries, there is a significant gap between what households subscribe to and what we see from Ookla® data in terms of users actually experiencing speeds above 100 Mbps. Netherlands, France, and Germany are the outliers where we see more users having “high internet speeds” compared to the speeds advertised in their broadband subscription package. This is particularly interesting because Germany still heavily relies on VDSL for high-speed access technologies. Still, there is a significant amount of work to be done before countries can deliver on their strategies to achieve the 100 Mbps target.

The EC’s goal of gigabit connectivity is certainly one of the driving forces behind the rollout of fiber networks in the region. So far, progress is mixed across the region in terms of fiber network rollouts and adoption. As we have discussed, regulatory incentives propel the move to fiber. For example, Romania has one of the highest Fiber to the Home/ Building (FTTP/B) penetration rates across the region — nearly 97.7% of households — which is partially driven by government-backed fixed infrastructure projects such as RoNet, and the special attention given to rural and disadvantaged areas. Portugal, which already scored high on fiber coverage, plans to launch an international public tender by the end of 2023 for a project to cover all underserved areas with fiber-optic networks to boost fiber penetration further.

The reality of gigabit speeds

The European Commission’s Digital Decade 2030 strategy seeks to extend gigabit (1 Gbps) connectivity to every European Union household by 2030. To track the progress of these objectives, the DESI plays a crucial role in tracking EC’s progress. Only 56% of households in the EU have access to the necessary fiber networks for gigabit connectivity, and the take-up rate (proportion of households that subscribe to fiber) is even lower. According to the DESI 2023 dashboard for the Digital Decade, 13.76% of households in the European Union have subscribed to fixed broadband with at least 1 Gbps as of 2022. Nevertheless, there is a significant disparity in these percentages across different EU nations. For instance, only five countries surpassed the EU value – France leading with 39.94%, Hungary second at 29.81%, followed by Romania at 23.35%, Denmark at 18.66%, and Spain at 14.57%.

Looking at this data one might believe that many European households have access to Gigabit internet speeds. However, the reality is different as not all of them genuinely experience such high speeds. In fact, the proportion of Speedtest® users registering median download speeds of at least 1 Gbps in many countries is quite low. For example, France only had 1.42%, Hungary at 0.54%, Romania at 0.1%, Denmark at 0.03%, and Spain at 0.27%.

The significant gap between expectations and reality underscores the importance of not only rolling out gigabit-capable networks but also stimulating demand for those services. Service providers also need to pay attention to home networking equipment. Our research has shown that in markets where legacy broadband technology (such as DSL or coax cable) is being replaced by advanced cable and fiber connections, Wi-Fi performance can lag behind ethernet. Wi-Fi speeds typically range from 30-40% of ethernet, indicating a need to accelerate the adoption of more advanced Wi-Fi technologies and optimize the home network environment.

Median download and upload disparities

Median speeds are a standard metric for measuring performance, but there’s more to the story for the end-user experience. Access technology, be it DSL, cable, or fiber, as well as customer premises equipment and end-user devices, significantly influence the user experience. In our recent article, we highlighted how the persistent use of legacy and underperforming Wi-Fi standards in home networks can hamper efforts to provide the best network experience to customers despite progress in terms of fiber rollout and adoption.

According to Speedtest Intelligence® in Q3 2023, across Europe, Denmark had the fastest median download speed for fixed broadband (196.43 Mbps), followed by Spain (176.08 Mbps), France (170.51 Mbps), and Romania (166.39 Mbps). Notably, several of those countries have a substantial gap between median download and upload speeds. The type of broadband technology implemented can heavily influence the divergence between download and upload performance. Nations still reliant on DSL and cable often exhibit lower median upload speeds and a wider gap between upload and download speeds. On one hand, the UK and Germany lag behind other countries in broadband infrastructure upgrades due to their reliance on copper-based technologies and cable networks and are at the tail end of the ranking.

On the other hand, Sweden, with a 63% Fiber-to-the-Home (FTTH) penetration rate in 2022, has the narrowest gap between download and upload speeds. Forward-thinking broadband infrastructure and significant municipal involvement have positioned Sweden to reach the EC’s goals in the coming years. France, Spain, Denmark, Romania, and Portugal are also making significant progress toward achieving full-fiber coverage, with France expecting a full-fiber rollout by 2025. As fiber broadband adoption increases, the gap between download and upload speeds will narrow, mainly because fiber subscriptions are typically offered with symmetrical speeds, where users would experience the same level of speed for both download and upload usage.

However, even when we look at “the best-connected” Speedtest users (those seeing speeds in the top 10th percentile of our results), there’s a wide range of performance. Download speeds ranged between 417.23 Mbps and 844.04 Mbps, while the range for upload speeds was even wider, with median upload speeds ranging from 57.11 Mbps to 599.39 Mbps.

When looking at speeds at the 10th percentile, only four countries topped 700 Mbps. France led with a top speed of 844.08 Mbps, followed by Hungary at 765.85 Mbps, Denmark at 734.91 Mbps, and Romania at 704.04 Mbps. Notably, three of these countries (Romania, France, and Denmark) also lead in the top 10% of upload speeds, with all three exceeding 500 Mbps.

While for most countries included in this analysis, top speeds are at least a few hundred Mbps apart, there are a few exceptions. Spain shined bright, with the top 10% of its download and upload speeds closely matched at 611.17 Mbps and 609.17 Mbps, respectively.

Beyond median speeds

To delve deeper into the performance and reliability of internet services across different countries, it can be helpful to look at the expected speed range, i.e., the range of speeds that the majority of users experience. This middle 50% of speeds are captured by the interquartile range, with the lower value of the range, or lower quartile, indicating the bottom 25% of speeds and the upper value of the range, or upper quartile, indicating the top 25% of speeds. Examining Speedtest Intelligence data from Q3 2023, the lower quartile download speed across European countries ranged from 28.15 Mbps to 81.48 Mbps (in other words,, 25% of downloads were below that speed), while upper quartile speeds clocked in between 166.16 Mbps and 441.38 Mbps (i.e., 25% of downloads were above this speed).

Role of AltNets

According to the FTTH Council Europe, alternative operators (AltNets) are playing a significant role in the adoption of fiber in the EU39 region. The EU39 region comprises the EU27, the UK, Iceland, Israel, North Macedonia, Norway, Serbia, Switzerland, Turkey, and 4 CIS other countries. In 2021, around 56% of FTTH/B initiatives were led by AltNets, which marks a shift from 2011 when alternative ISPs had a 71% share, and incumbents accounted for only 21% of initiatives.

We looked at data from Omdia to determine whether there is a correlation between the number of active ISPs and the speed of the transition to fiber networks measured by FTTH share of all connections. The relationship is not straightforward and varies significantly depending on each country’s competitive landscape and government initiatives.

Across a number of countries fiber accounts for the majority of subscriptions – Spain comes on top with 81.8%, followed by Romania (81.7%), Sweden (77.5%), and Portugal (62.4%). Spain is a good example of a market that has been migrating to fiber away from copper ahead of the incumbent Telefonica turning off its legacy fixed network in 2024. Furthermore, Spain’s National Commission for Markets and Competition (CNMC) has simplified its ‘MARCo offer’, making it easier for alternative operators to access Telefonica’s infrastructure to launch their own fiber optic services.

It is worth noting that countries like the UK and Poland, which have many ISPs, are also leading the way in AltNet-driven fiber initiatives. In our previous article looking at the impact of AltNets in the UK, we concluded that AltNets played an important role. In fact, AltNets provided the top speeds in London, Glasgow, Liverpool, and Manchester, as well as across a number of counties. Public funding has helped facilitate the emergence of fiber ISPs in rural areas where fiber deployment is not commercially viable. Other AltNets like Hyperoptic are already well established, deploying and operating an FTTP network in high-density areas, which connects existing and new multi-dwelling buildings.

Take-up rates come with challenges

As fiber rollout nears completion in some countries, the focus shifts to selling fiber subscriptions to households that are within fiber network coverage. Sweden leads with an 80.1% consumer take-up rate (proportion of households that subscribed to and are actively using fiber-optic broadband services), but Spain, Norway, and France also boast high rates above 70%.

Sweden was the country that pioneered the open access model for fiber networks to drive competition and contributed to the country’s high fiber broadband penetration rates. Fiberhost, a Polish open-access network provider, is a significant beneficiary of EU funds, with 99% of funding for building the country’s fiber network in white spot areas (areas with limited or no access to high-speed internet).

There also has been notable progress in the wholesale networks market in Europe, some of which look to connect remote and rural areas. The Italian wholesale operator, Open Fiber, is partially funded by the country’s National Recovery and Resilience Plan (PNRR), with the goal of connecting the grey areas (where no other operator has plans to develop an NGA network) to gigabit speeds.

However, challenges persist in convincing consumers to switch to full fiber, even in countries with high take-up rates. For instance, a joint venture by Orange conducted a survey in rural areas of France to understand why households with FTTH access hadn’t upgraded to fiber services. The study revealed that 42% found their current internet sufficient, while 37% said incentives would encourage them to upgrade. Incentives and other initiatives are being implemented to migrate customers onto fiber networks in many countries in the region and across the world.

Future Initiatives and Investments

Fiber offers superior internet speeds, lower latency, enhanced security, and environmental sustainability – a noteworthy upgrade from copper networks and also a path forward for some cable operators (instead of DOCSIS 4.0). AltNets are making strides in driving fiber deployment across Europe, pushing toward the EC’s ambitious goals of achieving a gigabit society.

Despite progress, obstacles remain in convincing consumers to fully transition to fiber services. Comprehending consumer behavior, promoting fiber benefits, and inspiring initiatives will all play significant roles in this endeavor. Likewise, continued investments must be made to keep Europe on track to attain its connectivity targets

For more insightful updates on Europe’s fiber connectivity status, look forward to the Network X event in October 2023. It’ll offer a live pulse on the latest developments in fiber connectivity. We will continue to follow European countries’ progress toward Gigabit society and monitor its impact on fixed broadband speeds. If you’d like to learn more about internet speeds and speed performance in other markets around the world, visit the Speedtest Global Index™.

You can also register for our upcoming webinar, “Accelerating Europe’s Gigabit Revolution” on Wednesday, November 8 at 9 a.m. CET (GMT+1). A panel of industry experts will come together to discuss how Gigabit Society fits into Europe’s digital transformation strategy and propose strategies to ensure digital access for all. A recording will be provided for registrants who can’t join the live presentation. Register now.

About the Author

Sylwia Kechiche

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Isla McKetta | June 28, 2017

Seeking Out the Fastest Free Wi-Fi at European Airports

If Europe is on your travel itinerary this summer, you probably want to know which airports offer free Wi-Fi and whether the service is fast enough for you to handle all of life’s last minute details before jetting across the continent. We took a look at Speedtest data from March through May 2017 from twelve of Europe’s busiest airports to help you find out.

Fastest airport Wi-Fi

It’s a good thing many airports in Europe offer paid Wi-Fi options if you want better speeds, because speeds on the free Wi-Fi everywhere besides Moscow and Munich are slow.

Moscow’s Sheremetyevo International Airport has the fastest free Wi-Fi in Europe, about equal to the mobile Wi-Fi country average in Russia of 27.96 Mbps, although you’ll need a Russian phone number to access the airport Wi-Fi.

Germany’s second busiest airport, Munich, comes in a close second. Both airports have even faster upload speeds than download, so you can spend your layover safely stowing those vacation pics in the cloud. Munich’s Wi-Fi is 36% slower than Germany’s average download speed over mobile Wi-Fi of 37.94 Mbps.

The rest of the airports offer speeds that are much slower than the average mobile Wi-Fi speeds in their respective countries: Spain (42.72 Mbps), the UK (41.98 Mbps), Italy (21.02 Mbps), and the Netherlands (57.07 Mbps).

For comparison, Hong Kong’s International Airport offers free Wi-Fi with an average speed of 8.93 Mbps while the three largest airports in mainland China offer service ranging from 2.40 to 3.72 Mbps. Those are the slowest airports in Asia, read about the fastest.

Oddly, we saw no Speedtest results in Istanbul’s Atatürk Airport or at either of Paris’ two airports on the published free airport Wi-FI SSIDs during the time we surveyed. At both Orly and Charles de Gaulle, though, we did see networks called “*WIFI-AIRPORT”. If those are indeed the free airport Wi-Fi networks, Charles de Gaulle would rank 7th in Europe at 2.33 Mbps and Orly would rank 8th at 2.32 Mbps.

You can help us get accurate speed data for those airports by taking a Speedtest using the airport’s free Wi-Fi.

Fastest airport cell

In cases where you can’t connect to Wi-Fi, you’ll be delighted to find that cellular service in these airports is much, much faster than the Wi-Fi.

Munich Airport has the fastest average download speed on cellular with Rome’s Fiumicino Airport and Istanbul’s Atatürk Airport ranking a very close second and third, respectively. And Istanbul has the fastest average upload speed on cell networks.

In many cases, cellular service at these airports is faster than average speeds in the country as a whole. The airports in Munich, Istanbul, and Moscow are all more than twice as fast as that in their respective countries of Germany (23.05 Mbps), Turkey (29.45 Mbps) and Russia (14.92 Mbps). Cell downloads at Rome’s Fiumincino Airport are 56% faster than Italy’s average of 32.52 Mbps over the same period.

The Spanish and British airports we surveyed offer download speeds that are loosely comparable to the averages in their respective countries: Spain’s average is 28.32 Mbps and the UK’s is 25.92 Mbps. Download speed at Paris’s two airports is harder to summarize with the speed at Charles de Gaulle 27% slower than the country average of 29.08 Mbps while Orly’s downloads coming in 54% slower than the country. And Amsterdam’s Schiphol download speed is only half as fast as that in the Netherlands overall (47.38 Mbps).

If you want to know more, read our full country reports on Germany, Turkey and the United Kingdom.

Wi-Fi or cell?

Given those painful Wi-Fi speeds, this is kind of a no-brainer, but we thought you might want to see just how slow the Wi-Fi is at various airports compared to the cellular service.

We omitted data about the Istanbul and Paris airports from these graphs because we can’t verify the Wi-Fi SSIDs, but you get the point: when in doubt in Europe, use cellular service rather than free airport Wi-Fi.

Regional trends

You might be surprised how similar and how different Wi-Fi and cellular service can be at two different airports in the same country or even the same city.

Heathrow vs. Gatwick

The free Wi-Fi at Heathrow and Gatwick is similarly bad but you’ll get faster downloads at Heathrow and slightly faster uploads at Gatwick.

Charles de Gaulle vs. Orly

Wi-Fi downloads at Charles de Gaulle and Orly on the *WIFI-AIRPORT are almost exactly as awfully slow as each other. But on cellular, Charles de Gaulle has significantly faster download and upload speeds.

Barcelona Airport vs. Madrid-Barajas

Barcelona Airport’s slow 5.72 Mbps download speed over Wi-Fi is more than twice as fast as the 2.11 Mbps at Madrid–Barajas Airport. When it comes to cellular, however, Madrid’s downloads are 28% faster and their uploads are 15% faster than those in Barcelona.

Frankfurt Airport vs. Munich Airport

Munich Airport’s Wi-Fi download speed is more than three times faster than Frankfurt’s and Munich’s upload speed is nearly two and a half times faster. Munich also shows an average download speed over cellular that is 67% faster than Frankfurt’s while Munich’s uploads are 59% faster.

If your experience of internet performance at European airports is different than what’s reported here, take a Speedtest on Android or iOS so we can see what you’re experiencing. We’ll be watching for big changes and reporting on them here.

Up next in our fastest airports in the world series, we’ll be looking at internet speeds at the busiest airports in Africa.

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Isla McKetta

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Isla McKetta | January 24, 2018

GOOOOAL: Which World Cup Finalist Scored the Fastest Internet in their Capital City?

Whether you call it soccer or football, everyone calls the World Cup fun. We couldn’t wait for the actual match-ups in June, so we decided to pit the qualifying countries against one another to see who has the fastest internet speeds in their capital cities. The results might surprise you.

Get ready to watch Russia best Brazil and Portugal defeat Iran; meanwhile, Argentina and Nigeria and Belgium and England are preparing for penalty shoot-outs.

Using data from Speedtest Intelligence for Q3-Q4 2017, we’ve calculated which capital cities of World Cup-qualifying countries have the fastest mobile and fixed broadband speeds. We also took a peek at the fastest carriers and internet service providers (ISPs) in each capital using Speed Score, a comprehensive metric that combines measures of internet performance at all levels.

Mobile winners

Iceland’s sixth place ranking for mobile download speed in the Speedtest Global Index^TM virtually assured that Reykjavík would come out at the top of the list of fastest World Cup contenders. Canberra represents Australia well with a second place finish for mobile download speeds among World Cup capitals. And Brussels, Belgium barely surpasses Bern, Switzerland for a third place finish.

**Mobile Internet Speeds**
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country	Capital City	Average Download (Mbps)	Average Upload (Mbps)
Iceland	Reykjavík	55.49	21.53
Australia	Canberra	44.24	12.60
Belgium	Brussels	42.52	16.74
Switzerland	Bern	42.02	17.52
South Korea	Seoul	41.85	14.15
Denmark	Copenhagen	41.78	18.29
Croatia	Zagreb	41.16	16.40
Sweden	Stockholm	40.12	12.63
Spain	Madrid	38.30	14.02
Portugal	Lisbon	30.60	11.39
Serbia	Belgrade	30.33	12.49
France	Paris	29.03	9.26
Poland	Warsaw	26.94	9.84
Germany	Berlin	25.83	9.51
England	London	25.09	11.49
Russia	Moscow	21.89	8.49
Japan	Tokyo	19.89	7.10
Uruguay	Montevideo	19.82	11.49
Mexico	Mexico City	19.11	11.51
Peru	Lima	18.33	12.90
Tunisia	Tunis	18.27	8.07
Brazil	Brasília	18.00	8.64
Morocco	Rabat	17.32	9.76
Colombia	Bogotá	16.87	9.50
Nigeria	Abuja	16.17	6.76
Iran	Tehran	15.05	7.04
Argentina	Buenos Aires	13.77	7.70
Egypt	Cairo	13.15	6.33
Panama	Panama City	12.89	8.45
Saudi Arabia	Riyadh	12.28	8.88
Senegal	Dakar	8.85	3.81
Costa Rica	San José	5.97	3.33

Looking at the group draw, Group A fares the worst with 16th place Moscow, Russia being the capital city with the fastest mobile downloads in the group. In Group B, Spain comes out on top. Australia wins Group C, Iceland takes Group D, Switzerland leads Group E and South Korea has the fastest mobile download speed in Group F. Belgium finishes first in Group G and Poland prevails in Group H, despite a 13th place finish overall.

From a regional perspective, European capitals top the rankings with all 14 European World Cup capitals sitting in the top half of the list. Latin American, Middle Eastern and African cities fare worst. Asia’s two contenders are split with Seoul boasting the fifth fastest mobile download speed among World Cup capitals and Tokyo, Japan coming in 17th.

The fastest World Cup capital in Latin America (Montevideo, Uruguay) shows a 64.3% slower mobile download speed than Reykjavík. First place among African World Cup capitals, Rabat, Morocco is 68.8% slower than Reykjavík for mobile downloads. And Tehran, Iran, the fastest World Cup capital in the Middle East, is 72.9% slower than Reykjavík.

Fastest carriers

We also looked into which carriers were fastest in each of the 32 World Cup capital cities.

With Speed Scores ranging from 8.89 in Dakar, Senegal to 46.57 in Brussels, mobile carrier Orange was fastest in four cities and tied for fastest in one. Vodafone was fastest in both Lisbon, Portugal and Madrid, Spain with comparable Speed Scores in the two locations. The rest of the cities show the diversity of fastest carriers that you might expect from a worldwide competition.

**Fastest Carriers Speeds**
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country	Capital City	Fastest Carrier	Speed Score
Argentina	Buenos Aires	Personal	16.15
Australia	Canberra	Telstra	50.21
Belgium	Brussels	Orange	46.57
Brazil	Brasília	Claro	24.72
Colombia	Bogotá	Avantel	20.93
Costa Rica	San José	ICE	8.30
Croatia	Zagreb	Hrvatski Telekom	49.35
Denmark	Copenhagen	TDC / Telia	45.34 / 45.09
Egypt	Cairo	Orange	16.50
England	London	EE	36.83
France	Paris	Orange	33.15
Germany	Berlin	Telekom	53.54
Iceland	Reykjavík	Nova	64.61
Iran	Tehran	MTN IranCell	15.89
Japan	Tokyo	SoftBank	27.26
Mexico	Mexico City	AT&T	20.26
Morocco	Rabat	inwi	20.51
Nigeria	Abuja	MTN	29.23
Panama	Panama City	Cable & Wireless Panama / Movistar	14.85 / 14.80
Peru	Lima	Entel Peru	20.73
Poland	Warsaw	T-Mobile	36.07
Portugal	Lisbon	Vodafone	42.44
Russia	Moscow	MegaFon	37.06
Saudi Arabia	Riyadh	Zain	13.20
Senegal	Dakar	Orange	8.89
Serbia	Belgrade	Vip mobile	45.56
South Korea	Seoul	LG U+	50.03
Spain	Madrid	Vodafone	40.17
Sweden	Stockholm	Telia	54.49
Switzerland	Bern	Sunrise / Swisscom	42.14 / 41.91
Tunisia	Tunis	Ooredoo / Orange	19.90 / 19.89
Uruguay	Montevideo	Antel	20.35

Fixed broadband winners

Given that Iceland ranks second in the world for fixed broadband download speed on the Speedtest Global Index and has the world’s highest gigabit user penetration (GUP), we’re not surprised to see Reykjavík shut out the competition by coming out on top of World Cup contenders for fixed broadband speed, too. Seoul, South Korea comes in second for fixed broadband download speed among World Cup capitals and Paris, France takes third.

**Fixed Broadband Internet Speeds**
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country	Capital City	Average Download (Mbps)	Average Upload (Mbps)
Iceland	Reykjavík	142.89	154.28
South Korea	Seoul	130.75	131.96
France	Paris	112.58	55.86
Sweden	Stockholm	98.77	66.68
Spain	Madrid	86.59	73.43
Japan	Tokyo	75.88	70.46
Denmark	Copenhagen	72.74	52.13
Switzerland	Bern	68.82	54.44
Poland	Warsaw	62.57	16.19
Portugal	Lisbon	55.80	30.97
England	London	52.53	16.12
Germany	Berlin	46.84	9.52
Russia	Moscow	45.25	42.96
Belgium	Brussels	43.25	9.63
Panama	Panama City	29.11	5.93
Australia	Canberra	28.85	12.46
Serbia	Belgrade	26.45	5.59
Croatia	Zagreb	26.20	11.40
Mexico	Mexico City	24.11	10.14
Uruguay	Montevideo	23.02	5.82
Argentina	Buenos Aires	22.03	4.26
Brazil	Brasília	21.57	5.29
Saudi Arabia	Riyadh	20.93	9.05
Peru	Lima	18.15	3.51
Colombia	Bogotá	13.43	6.48
Morocco	Rabat	11.83	2.51
Iran	Tehran	9.33	4.18
Costa Rica	San José	8.79	4.29
Nigeria	Abuja	8.07	5.27
Tunisia	Tunis	7.82	4.49
Senegal	Dakar	7.42	3.11
Egypt	Cairo	5.61	1.92

Group A again suffers on the fixed side with leader Russia coming in 13th based on Moscow’s fixed broadband download speed. Spain’s still the front-runner of Group B. France takes Group C, Iceland wins Group D, Switzerland tops Group E, South Korea reigns over Group F, England heads up Group G and Japan starts Group H based on average download speeds over fixed broadband in their respective capitals.

European capitals again fare well, with 12 of the 14 placing in the top half of fastest World Cup capitals for fixed broadband download speed. Belgrade, Serbia and Zagreb, Croatia rank 17th and 18th, respectively. Tokyo ranks much better for fixed broadband download speed than for mobile, which puts both Asian World Cup capitals in the top six.

With the exception of Panama City, Panama, which ranks 15th, all Latin American World Cup capitals are in the bottom half of the list for download speed over fixed broadband. As are all Middle Eastern and African capital cities.

Panama City’s fixed broadband download speed is 79.6% slower than Reykjavík’s. Riyadh, Saudia Arabia boasts the title of fastest World Cup capital in the Middle East, but is still 85.4% slower for fixed broadband downloads than Reykjavík. The fastest World Cup capital in Africa — Rabat, Morocco — is 91.7% slower than Reykjavík.

Fastest providers

Comparing Speed Scores for fixed broadband across World Cup capitals, Vodafone had wins in Berlin, Germany and Lisbon and Orange took Paris and tied for first in Madrid. The rest of the fastest ISPs vary by location as listed below:

**Fastest ISPs Speeds**
Capitals of World Cup Qualifying Countries | Q3 – Q4 2017
Country	Capital City	Fastest ISP	Speed Score
Argentina	Buenos Aires	Cablevisión Fibertel	21.72
Australia	Canberra	iiNet	33.23
Belgium	Brussels	Telenet	66.95
Brazil	Brasília	NET Virtua	27.30
Colombia	Bogotá	ETB	19.17
Costa Rica	San José	Cabletica	8.28
Croatia	Zagreb	vip	30.23
Denmark	Copenhagen	Fiberby	103.26
Egypt	Cairo	TE Data	4.84
England	London	Hyperoptic	117.40
France	Paris	Orange	107.20
Germany	Berlin	Vodafone	55.46
Iceland	Reykjavík	Nova	278.06
Iran	Tehran	Mobin Net	11.74
Japan	Tokyo	So-net	118.05
Mexico	Mexico City	Axtel	45.83
Morocco	Rabat	Maroc Telecom	9.25
Nigeria	Abuja	MTN	10.73
Panama	Panama City	Cable Onda	25.08
Peru	Lima	Movistar	16.64
Poland	Warsaw	UPC	82.72
Portugal	Lisbon	Vodafone	61.80
Russia	Moscow	MGTS	62.00
Saudi Arabia	Riyadh	STC	16.46
Senegal	Dakar	Tigo	6.42
Serbia	Belgrade	SBB	34.60
South Korea	Seoul	KT	162.45
Spain	Madrid	Masmovil / Orange	101.52 / 101.34
Sweden	Stockholm	Ownit	158.78
Switzerland	Bern	Fiber7	241.93
Tunisia	Tunis	TOPNET	7.61
Uruguay	Montevideo	Antel	22.01

Did your team not come out as expected? Or are you defending a tight match? Take a Speedtest on Android, iOS or on the web and we’ll check back in on scores closer to the main event.

About the Author

Isla McKetta

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Isla McKetta | April 17, 2018

EU Roaming is Free! But is it Fast?

When the European Commission put an end to roaming charges within the European Union (EU) last summer, they gave residents of member countries the freedom to take their mobile phones with them on vacation without fearing the bill when they got home. But how well are those phones performing when faced with foreign cell towers?

To find out, we took a look at Speedtest data from the first quarter of 2018 to see which countries’ residents are having the best (and worst) internet speed experiences abroad.

How much download speeds drop when you cross a border

The mean download speed in the EU when customers are at home is 30.57 Mbps, but that slows 16.6% to 25.50 Mbps when Europeans roam across a border.

Because your experience of speeds abroad is going to be based on what you’re used to, we compared countries based on the amount download speeds decreased rather than the actual speed abroad. Italians enjoyed a 15.4% increase in download speed when traveling. Estonians, Latvians and the Portuguese also saw faster downloads abroad.

**Mobile Download Speeds**
EU Countries | Q1 2018
Country	Local (Mbps)	Roaming (Mbps)	% Change
Austria	31.62	28.66	-9.4%
Belgium	44.56	26.00	-41.7%
Bulgaria	35.71	22.31	-37.5%
Croatia	34.75	31.36	-9.8%
Cyprus	25.34	23.40	-7.7%
Czech Republic	38.30	25.78	-32.7%
Denmark	42.55	22.40	-47.4%
Estonia	31.98	34.24	7.1%
Finland	32.68	29.99	-8.2%
France	32.35	24.47	-24.4%
Germany	26.03	26.00	-0.1%
Greece	34.48	28.40	-17.6%
Hungary	46.10	26.01	-43.6%
Ireland	19.98	19.00	-4.9%
Italy	30.32	34.98	15.4%
Latvia	27.37	28.97	5.8%
Lithuania	36.80	28.28	-23.2%
Luxembourg	42.43	22.46	-47.1%
Malta	42.14	25.05	-40.6%
Netherlands	53.07	25.46	-52.0%
Poland	22.05	20.29	-8.0%
Portugal	26.45	27.44	3.7%
Romania	28.74	21.95	-23.6%
Slovakia	28.79	23.73	-17.6%
Slovenia	28.42	27.15	-4.5%
Spain	31.94	24.32	-23.9%
Sweden	38.23	26.13	-31.7%
United Kingdom	26.16	21.08	-19.4%

On the other end of the spectrum, Dutch travelers experienced a 52% decrease in download speed when using mobile phones elsewhere in the EU. Residents of Denmark, Luxembourg, Hungary, Belgium and Malta all saw decreases of more than 40% when roaming.

In some cases, the decrease in download speed is due to the country’s relative speed. For example, the Netherlands has recently had the third fastest mobile speeds in the world according to the Speedtest Global Index so its residents are likely to see much slower speeds when traveling anywhere but Norway and Iceland. Other differences are probably better explained by how carriers prioritize out of country traffic, a decision that’s made between each individual carrier in each individual country.

Slow or not, at least roaming no longer comes with extra fees for EU residents. Unless you’re British, of course. With Brexit looming, not only could citizens of the UK have to return to paying roaming fees, the download speed they’ll be paying for abroad will be 19.4% slower than it is at home.

Again, a lot of factors go into what speeds you experience while roaming the continent. We hope this data will help you make an informed choice about your carrier depending on what your roaming data needs are. Share your experience by taking a Speedtest on Android or iOS.

About the Author

Isla McKetta

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