WHAT SPEED DO MOBILE USERS REALLY GET? - P3 DATA SPEED REPORT ABOUT DATA SPEED COMPARISON IN THE US MARKETS - P3 Group
←
→
Page content transcription
If your browser does not render page correctly, please read the page content below
WHAT SPEED DO MOBILE USERS REALLY GET? P3 DATA SPEED REPORT ABOUT DATA SPEED COMPARISON IN THE US MARKETS The US mobile networks are fast. At general speed capability of the mo- looks at the downlink speed as per- least, that’s what we hear every day. bile network, to the tariff used plus ceived by the users in our panel in the But does this reflect the actual user many other effects. different urban areas, defined by the experience? Not always. We aim to bring more transparen- U.S. Office of Management and Bud- In order to understand why the user’s cy into the discussion about speed. get as so-called Metropolitan Statisti- experience sometimes differs from Therefore, we have compared the cal Areas (MSA). the carriers’ advertisements, we have speed of the cellular networks in the made a thorough analysis examining United States in a new and differenti- THE REPORT PROVIDES TWO the actual speed of data transmissions ated way: We look at the actual speed DIFFERENT VIEWS ON SPEED. while consumers use their smart- of data transmissions while consumers First, we look at the top speeds ob- phones in real life. use their favorite apps and services. served at the fastest locations by the Looking at what is happening in This is significantly different to so- fastest users within an urban area. reality is very important. How long called legacy or traditional speed We call this: Network Top Speed. does it take to drive from home to tests. Those tests are usually based Here only the fastest samples con- work very much depends on both on artificially initiated data transfers tribute to the results, thus reflecting road and traffic conditions as well – thus, they less represent real life which speed users can get regardless as on the hour of commuting. Ask- conditions. of any possible limitations. ing how fast is your mobile net- We have examined and compared the Second, we look at the User Speed work, will probably lead to the big four mobile network carriers: Ve- Experience where we analyze the same answer: It depends. Here, the rizon, AT&T, T-Mobile and Sprint – the average speed results as well as the speed experience is related to the results are presented in this report. It fastest samples of all users. 1
Who is the leading carrier with respect to
downlink Network Top Speed, i.e. the Network
Top Speed that the fastest users were able to
reach or exceed in the best 10% locations in every
metropolitan statistical areas (MSA)? Colored
areas indicate which carrier leads the benchmark
in each MSA. Grey indicates MSAs where at least
two networks are on par providing about the
Alaska
same results for downlink speed (within a relative
margin of 1%).
Verizon
AT&T
T-Mobile
Sprint
Hawaii
On Par
(Mbit/s)
How fast are the networks? The
numbers show the downlink Net-
work Top Speed that on average is 69,1 50,0 49,9 37,9
exceeded in the best 10% of each
Metropolitan Statistical Area. Network Verizon AT&T T-Mobile Sprint
NETWORK TOP SPEED
From the network’s perspective, it is important what top The map shows the different MSAs and marks the leading
downlink speed a user can achieve when there is no limi- carrier with respect to network top downlink speed capa-
tation on the user’s side, e.g. due to device capabilities bilities. The top speeds achieved, averaged over all MSAs,
or tariff restrictions. This is because carriers invest a lot are shown in the bar chart.
in frequency spectrum, network densification and in up-
grading the networks to the latest technology – like car-
rier aggregation to enable faster data transmissions. The
Network Top Speed is a result of network capabilities and
coverage, and consequently very much depends on where
you use your smartphone. The speed a network shows in Verizon
one part of the city is not necessarily the same in anoth- clearly leads the
er part of the city. Therefore, for benchmarking the net-
works we look at the fastest speed achieved by any user at Network Top Speed
a measurement location and then do a statistical analysis benchmark
of all measurement locations in a Metropolitan Statistical
Area (MSA) with 472,760,281 samples.
2
Looking at both, the number of MSAs While Verizon leads in metro areas all
where a carrier delivers higher top over the country, T-Mobile leads in its
speeds than the competition and also headquarters’ neighborhood in Belle-
at the top speed effectively measured vue, WA and is especially strong in
– Verizon clearly leads the Network Florida with remarkably high Net-
Top Speed benchmark. With an aver- work Top Speeds, outperforming the
age Network Top Speed of about 69 competition by far.
Mbit/s, Verizon outperforms the oth- However, the diversity of Network
er carriers in 294 metropolitan areas Top Speeds amongst the different
by far. T-Mobile still leads in 47 of the metro areas is smallest for Verizon
metro areas, AT&T wins the bench- which means that Verizon shows the
mark in only 31 MSAs, though being most consistent picture across all
on the same Network Top Speed level MSAs. AT&T shows a similarly small
as T-Mobile. Sprint wins in only one diversity across the metro areas while
metro area at a Network Top Speed the top speeds observed for T-Mobile
level of about 38 Mbit/s lagging be- and Sprint vary much more from one
hind the other carriers. MSA to another.
Verizon provides the most
consistent Network Top Speeds
across the country.
T-Mobile stands out with
high speeds in Florida.
NETWORK TOP SPEED
From the countless millions of downlink speed samples observed while
consumers use their smartphone in everyday life, the fastest samples in-
dicate what the speed networks can deliver regardless of any limitations,
e.g. by tariff or smartphone capabilities. Of course, depending on network
properties like coverage or available spectrum, the achievable speed var-
ies amongst different locations in a market. We take that into consideration
by segmenting each MSA into a regular grid and identify the fastest speed
sample observed in each grid zone of about 1.5x1.5 miles. The fastest 10%
of all grid zones in each MSA determine the Network Top Speed that we
use for comparing the different networks in the metro areas.
3
USER SPEED EXPERIENCE
The user’s perspective on speed can be different from the
network’s perspective. Though the Network Top Speeds
Speed observed from a consumer’s perspective and the User Speed Experience are related, they are still
while using a smartphone. The graph shows the
two different sides of the same coin. In real life, users face
user experienced speeds averaged over all users
and Metropolitan Statistical Areas (top) and the quite a few limitations that typically make their achieved
speed of the best 10% of the experienced speeds. speed by far lower than the top throughput the network
can provide. Sharing the network capacity with other users,
traffic shaping by the carrier, bad local coverage conditions,
Average
tariff limitations and not least the type of application used
(Mbit/s) – all these factors may determine which speed consumers
really face when using their smartphones.
So, the speed achieved from a user’s perspective typical-
5,3 4,3 4,6 5,2
ly amount about one tenth of the Network Top Speed.
Again, Verizon leads the benchmark with an average user
Network Verizon AT&T T-Mobile Sprint
speed of 5.3 Mbit/s. Sprint shows only slightly lower user
speeds with an average of 5.2 Mbit/s. This is remarkable
since Sprint’s Network Top Speed was only a little more
than half of what the Verizon network showed. Obvious-
Fastest 10% ly, consumers on Sprint face less limitations in their real
(Mbit/s)
life smartphone usage than users in the other networks.
The average user speed with T-Mobile is 4.6 Mbit/s, while
AT&T is slowest with still competitive 4.3 Mbit/s.
In addition to benchmarking the networks with respect
to the average of the experienced speed, it is also worth
looking at the diversity of the speed, i.e. at how consis-
tently the throughput experience is achieved. A good
indication for the variation is the relation between the av-
erage and the fastest 10% of the observed speeds. Sprint
13,5 10,9 12,2 13,7
and T-Mobile show little higher variation than the compe-
tition and achieve a “fastest-10%” level of 13.7 Mbit/s and
Network Verizon AT&T T-Mobile Sprint
12.2 Mbit/s, respectively.
Obviously, consumers
on Sprint face less limitations
in their real life smartphone
usage than users in the other
networks.
4
With both T-Mobile and AT&T showing distinctly lower val- differences in network area coverage are deliberately
ues than the other networks, the User Speed Experience ignored to show a like-for-like comparison focusing on
benchmark remains between Verizon and Sprint. Howev- speed only. For a detailed analysis about network cover-
er, even though the user speed values show Verizon and age – see P3 Connectivity on Interstate Report (www.p3-
Sprint head-to-head, Verizon users still have a more con- group.com/en/p3-interstate-comparison-US-2018) and
sistent speed experience, both regarding peak-to-average P3 State Connectivity Report (www.p3-group.com/en/
and regarding the different Metropolitan Statistical Areas. US-State-Connectivity).
Finally, without understating Sprint’s pursuit, it is worth
mentioning that the benchmark shown here is based on the
common footprint of all four networks, i.e. on the area
within the MSAs where consumers from all four carriers
have transferred data with their smartphone. Potential
USER SPEED EXPERIENCE
When comparing the networks from the user’s perspective, we take into consideration that the speed a user
achieves while using the smartphone depends on the consumer’s usage profile, i.e. the apps used, the locations
where the phone is used and, to some extent, also on the tariff. Therefore, each consumer has an own speed expe-
rience depending on the usage profile. For comparing the networks, we analyze the User Speed Experience of each
of the 2.3 million users in our crowd panel and then look at the average and top speed throughout of these users.
In the hundreds of millions of downlink speed samples, we first identify the smartphone data traffic that creates a
distinguishable speed experience. This step is important as most app generated data traffic, e.g. a WhatsApp chat,
is not representing the user experience of network speed simply because the bandwidth demand of a chat session
is far from what modern networks can deliver even under bad conditions.
For the calculation of the User Speed Experience we also segment each MSA into a regular grid and identify the
speed achieved by each user in each of the grid zones visited. This way, we take the location-dependent nature of
the speed into account. For each user, we consider the different locations as equally important for the experienced
speed and therefore do the network benchmark based on all these speed samples from all users in the respective
Metropolitan Statistical Area. We look at the common footprint of the four networks, i.e. the area within the MSAs
where consumers of all four carriers have used their smartphone. Here, we look at the average of all speed samples
and the 10% fastest samples representing the user experienced top speeds.
5
METHODOLOGY
WITH MORE THAN 15 YEARS OF EXPERIENCE IN BENCHMARKING MOBILE NETWORKS ALL OVER THE WORLD,
P3 AGGREGATES DATA INTO MEANINGFUL METRICS, PROVIDING A BALANCED AND INDEPENDENT PICTURE
OF THE COMPETITIVE SITUATION ACROSS DIFFERENT MARKETS.
The P3 methodology looks at the real life data traffic speed
and thus analyses what really happens on the consumers’ Verizon shows higher
smartphones when they use any of their apps. Compared
to old fashioned speed tests that are based on download
top speeds than the
ing bulks of artificial data, the analysis of real life traffic for competition in more than
doing a meaningful speed benchmark is much harder, but
it is worth it. A proper cleansing and smart aggregation
75% of the metro areas.
of the collected data allows a nuanced view on different
facets of speed.
The P3 solution is integrated into 800+ very diverse Android rience databases in the world, adding billions of measure-
apps and passively collects data in the background. If one ments every month. The data set is the most realistic and
of the applications is installed on the end-user’s phone, diverse that is currently available in the market in terms
the data collection takes place continuously – 24/7/365 of locations, geography, devices, subscriptions, networks,
– on this device. Other data solutions from other sourc- technologies and smartphone usage patterns. And, just
es have a very technical user base or they measure speed like in blockchain, P3 has designed their technology with a
with artificial data traffic not representing real life condi- complex security layer that makes it impossible to manipu
tions. Thus, their results are typically skewed towards high- late the data.
end and high-volume data users. With the integration into P3 applies advanced data analytics to find the relevant in-
diverse apps covering different market segments, the data formation from the bulk data, transferring it to the P3 Big
set used is much more representative and tamper-proof Data Platform. Automated aggregation with P3 developed
than data from classical speed test apps. The unique user software provides us flexibility and control. P3 has gained
base and dataset allows P3 to collect data about the real- extensive experience in collecting, storing and analyzing
world customer experience – wherever and whenever large data sets. P3 can provide information for the optimi-
customers use their phones. zation of networks and show whether networks live up to
consumers’ expectations. P3 data scientists can drill down
HARDENED TO PREVENT MANIPULATION into large data sets and analyze them on a global scale.
In the US, about 2.3 million consumers contribute to P3’s The information gathered and processed by P3 can be pur-
dataset. This equals about one out of every 140 inhabitants chased by interested parties in an anonymized format. This
in the United States. This is one of the biggest mobile expe- can provide valuable insights for network improvements.
6
P3 CROWD FACTS USA
472,760,281 41.3 BILLION
SPEED SAMPLES TOTAL SAMPLES
383 3 MONTHS,
METROPOLITAN MAY TO JULY 2018
STATISTICAL AREAS
DATA COLLECTION
TIME PERIOD
2,195,628
USERS
7 7SNAPSHOT: OUR DATA
COLLECTION CAPABILITY
DATA COLLECTION DURING
THE BURNING MAN FESTIVAL
Once a year, 70,000 people gather for one week in
Nevada’s Black Rock Desert to create Black Rock City,
a temporary metropolis, to celebrate Burning Man
which took place August 26 – September 3, 2018. The
map shows the data points collected by P3 in that
area for the 2018 event. It resembles the iconic shape
of the city and shows what massive amount of data can
be collected with a passive crowdsourced solution.
CONTACT
Hakan Ekmen P3 communications GmbH
CEO, P3 communications GmbH Am Kraftversorgungsturm 3 │ 52070 Aachen │ Germany
hakan.ekmen@p3-group.com www.p3-group.com │ info@p3-group.com
+49 151 571 33 235 +49 241 9437400
Find more reports on www.p3-networkanalytics.com.
8You can also read
