Facebook 2012 Annual Report Download - page 32

may only be discovered after the code has been released. Any errors, bugs, or vulnerabilities discovered in our
code after release could result in damage to our reputation, loss of users, loss of revenue, or liability for damages,
any of which could adversely affect our business and financial results.
Certain of our user metrics are subject to inherent challenges in measurement, and real or perceived
inaccuracies in such metrics may harm our reputation and negatively affect our business.
The numbers of our MAUs, DAUs, and mobile MAUs and average revenue per user (ARPU) are calculated
using internal company data based on the activity of user accounts. While these numbers are based on what we
believe to be reasonable estimates of our user base for the applicable period of measurement, there are inherent
challenges in measuring usage of our products across large online and mobile populations around the world. For
example, there may be individuals who maintain one or more Facebook accounts in violation of our terms of
service. We estimate, for example, that “duplicate” accounts (an account that a user maintains in addition to his
or her principal account) may have represented approximately 5.0% of our worldwide MAUs as of December 31,
2012. We also seek to identify “false” accounts, which we divide into two categories: (1) user-misclassified
accounts, where users have created personal profiles for a business, organization, or non-human entity such as a
pet (such entities are permitted on Facebook using a Page rather than a personal profile under our terms of
service); and (2) undesirable accounts, which represent user profiles that we determine are intended to be used
for purposes that violate our terms of service, such as spamming. As of December 31, 2012, for example, we
estimate user-misclassified accounts may have represented approximately 1.3% of our worldwide MAUs and
undesirable accounts may have represented approximately 0.9% of our worldwide MAUs. We believe the
percentage of accounts that are duplicate or false is meaningfully lower in developed markets such as the United
States or Australia and higher in developing markets such as Indonesia and Turkey. However, these estimates are
based on an internal review of a limited sample of accounts and we apply significant judgment in making this
determination, such as identifying names that appear to be fake or other behavior that appears inauthentic to the
reviewers. As such, our estimation of duplicate or false accounts may not accurately represent the actual number
of such accounts. We are continually seeking to improve our ability to identify duplicate or false accounts and
estimate the total number of such accounts, and such estimates may change due to improvements or changes in
our methodology.
Some of our historical metrics through the second quarter of 2012 have also been affected by applications
on certain mobile devices that automatically contact our servers for regular updates with no user action involved,
and this activity can cause our system to count the user associated with such a device as an active user on the day
such contact occurs. For example, we estimate that less than 5% of our estimated worldwide DAUs as of
December 31, 2011 and 2010 resulted from this type of automatic mobile activity, and that this type of activity
had a substantially smaller effect on our estimate of worldwide MAUs and mobile MAUs. The impact of this
automatic activity on our metrics varied by geography because mobile usage varies in different regions of the
world. In addition, our data regarding the geographic location of our users is estimated based on a number of
factors, such as the user’s IP address and self-disclosed location. These factors may not always accurately reflect
the user’s actual location. For example, a mobile-only user may appear to be accessing Facebook from the
location of the proxy server that the user connects to rather than from the user’s actual location. The
methodologies used to measure user metrics may also be susceptible to algorithm or other technical errors. For
example, in early June 2012, we discovered an error in the algorithm we use to estimate the geographic location
of our users that affected our attribution of certain user locations for the period ended March 31, 2012. While this
issue did not affect our overall worldwide MAU and DAU numbers, it did affect our attribution of users across
different geographic regions. We estimate that the number of MAUs as of March 31, 2012 for the United
States & Canada region was overstated as a result of the error by approximately 3% and this overstatement was
offset by understatements in other regions. Our estimates for revenue by user location and revenue by user device
are also affected by these factors. We regularly review and may adjust our processes for calculating these metrics
to improve their accuracy. In addition, our MAU and DAU estimates will differ from estimates published by
third parties due to differences in methodology. For example, some third parties are not able to accurately
measure mobile users or do not count mobile users for certain user groups or at all in their analyses. If marketers,
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