Hi all,
here is the weekly look at our most important readership metrics, a bit
belatedly this time.
As laid out earlier
<https://lists.wikimedia.org/pipermail/mobile-l/2015-September/009773.html>,
the main purpose is to raise awareness about how these are developing, call
out the impact of any unusual events in the preceding week, and facilitate
thinking about core metrics in general. We are still iterating on the
presentation and eventually want to create dashboards for those which are
not already available in that form already. Feedback and discussion welcome.
For readers of this report who haven’t already seen it, I’d like to mention
the exciting announcement
<https://lists.wikimedia.org/pipermail/analytics/2015-November/004529.html>
of the new pageview API for per-article readership metrics.
Now to the usual data. (All numbers below are averages for November 9-15,
2015 unless otherwise noted.)
Pageviews
Total: 540 million/day (+0.7% from the previous week)
Context (April 2015-November 2015):
(see also the Vital Signs dashboard
<https://vital-signs.wmflabs.org/#projects=all/metrics=Pageviews>)
Some may remember that back in September, this weekly report called
<https://lists.wikimedia.org/pipermail/mobile-l/2015-September/009794.html>
out
<https://lists.wikimedia.org/pipermail/mobile-l/2015-September/009785.html>
a “conspicuous 4.3% drop” in total pageviews during the week until Sept 20
(followed by another 0.7% decrease the following week). Well, last week the
Analytics team solved that mystery
<https://phabricator.wikimedia.org/T114379#1802927>: An improvement in
detection of web crawlers had caused much more pageviews to be classified
as non-human, from Sept 16 on (e.g. for Commons, estimated human traffic
dropped
<https://vital-signs.wmflabs.org/#projects=commonswiki/metrics=Pageviews>
from about 12 million to about 4 million per day).
Desktop: 57.5% (previous week: 57.5%)
Mobile web: 41.3% (previous week: 41.3%)
Apps: 1.2% (previous week: 1.2%)
Global North ratio: 77.6% of total pageviews (previous week: 77.5%)
Context (April 2015-November 2015):
New app installations
Android: 55.3k/day (-8.8% from the previous week)
Daily installs per device, from Google Play
Context (last month):
As already mentioned in last week’s report, the Android Wikipedia app got
featured in the "New and Updated Apps" section of the Google Play store on
November 5, enabled by the Android team’s recent update work and
facilitated by the Partnerships team. The promotion lasted one week and we
can now see that it was a huge success (with the effect on download numbers
much more clearly discernible than in the case of the “Back to School”
feature we discussed last month
<https://lists.wikimedia.org/pipermail/mobile-l/2015-October/009835.html>).
Predictably, uninstalls went up slightly too, but most of the new users
kept the app on their phone. What is a little concerning though is that
after the promotion, install numbers fell below the previous baseline, with
the install base even shrinking a tiny bit right afterwards. (One
possibility is that we are seeing some sort of depletion effect, due to
people who would have installed the app anyway around this time, but saw it
earlier due to the promotion.) For that reason, we will wait a bit longer
before estimating the overall impact of this promotion.
iOS: 4.59k/day (+4.3% from the previous week)
Download numbers from App Annie
Context (last 12 months):
No big news here - things are back to normal after the App Store feature
last month.
App user retention
Android: 15.2% (previous week: 13.9%)
(Ratio of app installs opened again 7 days after installation, among all
installed during the previous week. 1:100 sample)
Context (last three months):
Recall that this metric lags one week behind, so to speak. I.e. the effects
of the Play Store promotion are not fully visible yet above (spoiler
though, having looked at a few more days of data already: retention for
installs who had come in during the promotion does not appear to have been
lower than usual, which is good news).
In general, this data is quite noisy due to the low (1:100) sample rate.
iOS: N/A
(Ratio of app installs opened again 7 days after installation, among all
installed during the previous week. From iTunes Connect, opt-in only = ca.
20-30% of all users)
Unfortunately I encountered some data quality issues with this metric this
week. Will investigate, and report iOS retention again once this is sorted
out. (The numbers and charts provided in the iTunes Connect App Analytics
appears to have changed quite a bit retroactively.) Unique app users
Android: 1.217 million / day (+2.7% from the previous week)
Context (last three months):
A somewhat noticeable rise that could well be connected with the
aforementioned Play Store promotion, but still needs a closer look once
more data is in.
iOS: 281k / day (+0.2% from the previous week)
Context (last three months):
No news here.
----
For reference, the queries and source links used are listed below (access
is needed for each). Most of the above charts are available on Commons, too
<https://commons.wikimedia.org/w/index.php?title=Special:ListFiles&offset=20150923010000&user=Tbayer+%28WMF%29&ilshowall=1&limit=4>
.
hive (wmf)> SELECT SUM(view_count)/7000000 AS avg_daily_views_millions FROM
wmf.projectview_hourly WHERE agent_type = 'user' AND
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0"))
BETWEEN "2015-11-09"
AND "2015-11-15";
hive (wmf)> SELECT year, month, day,
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0"))
as date,
sum(IF(access_method <> 'desktop', view_count, null)) AS mobileviews,
SUM(view_count) AS allviews FROM wmf.projectview_hourly WHERE year=2015 AND
agent_type = 'user' GROUP BY year, month, day ORDER BY year, month, day
LIMIT 1000;
hive (wmf)> SELECT access_method, SUM(view_count)/7 FROM
wmf.projectview_hourly WHERE agent_type = 'user' AND
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0"))
BETWEEN "2015-11-09"
AND "2015-11-15" GROUP BY access_method;
hive (wmf)> SELECT SUM(IF (FIND_IN_SET(country_code,
'AD,AL,AT,AX,BA,BE,BG,CH,CY,CZ,DE,DK,EE,ES,FI,FO,FR,FX,GB,GG,GI,GL,GR,HR,HU,IE,IL,IM,IS,IT,JE,LI,LU,LV,MC,MD,ME,MK,MT,NL,NO,PL,PT,RO,RS,RU,SE,SI,SJ,SK,SM,TR,VA,AU,CA,HK,MO,NZ,JP,SG,KR,TW,US')
0, view_count, 0))/SUM(view_count) FROM
wmf.projectview_hourly WHERE
agent_type = 'user' AND
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0"))
BETWEEN "2015-11-09"
AND "2015-11-15";
hive (wmf)> SELECT year, month, day,
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0")),
SUM(view_count) AS
all, SUM(IF (FIND_IN_SET(country_code,
'AD,AL,AT,AX,BA,BE,BG,CH,CY,CZ,DE,DK,EE,ES,FI,FO,FR,FX,GB,GG,GI,GL,GR,HR,HU,IE,IL,IM,IS,IT,JE,LI,LU,LV,MC,MD,ME,MK,MT,NL,NO,PL,PT,RO,RS,RU,SE,SI,SJ,SK,SM,TR,VA,AU,CA,HK,MO,NZ,JP,SG,KR,TW,US')
0, view_count, 0)) AS Global_North_views FROM
wmf.projectview_hourly
WHERE year = 2015 AND agent_type='user' GROUP BY
year, month, day ORDER BY
year, month, day LIMIT 1000;
https://console.developers.google.com/storage/browser/pubsite_prod_rev_0281…
(“overview”)
https://www.appannie.com/dashboard/252257/item/324715238/downloads/?breakdo…
(select “Total”)
SELECT LEFT(timestamp, 8) AS date, SUM(IF(event_appInstallAgeDays = 0, 1,
0)) AS day0_active, SUM(IF(event_appInstallAgeDays = 7, 1, 0)) AS
day7_active FROM log.MobileWikiAppDailyStats_12637385 WHERE timestamp LIKE
'201511%' AND userAgent LIKE '%-r-%' AND userAgent NOT LIKE
'%Googlebot%'
GROUP BY date ORDER BY DATE;
(with the retention rate calculated as day7_active divided by day0_active
from seven days earlier, of course)
https://analytics.itunes.apple.com/#/retention?app=324715238
hive (wmf)> SELECT SUM(IF(platform = 'Android',unique_count,0))/7 AS
avg_Android_DAU_last_week, SUM(IF(platform = 'iOS',unique_count,0))/7 AS
avg_iOS_DAU_last_week FROM wmf.mobile_apps_uniques_daily WHERE
CONCAT(year,LPAD(month,2,"0"),LPAD(day,2,"0")) BETWEEN 20151109 AND
20151115;
hive (wmf)> SELECT
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0"))
as date, unique_count AS Android_DAU FROM wmf.mobile_apps_uniques_daily
WHERE platform = 'Android';
hive (wmf)> SELECT
CONCAT(year,"-",LPAD(month,2,"0"),"-",LPAD(day,2,"0"))
as date, unique_count AS iOS_DAU FROM wmf.mobile_apps_uniques_daily WHERE
platform = 'iOS';
--
Tilman Bayer
Senior Analyst
Wikimedia Foundation
IRC (Freenode): HaeB