Hi all,

here is the weekly look at our most important readership metrics.

As laid out earlier, 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 will continue to iterate on the presentation (e.g. to better take seasonality into account, in particular including year-over-year comparisons) and eventually want to create dashboards for those which are not already available in that form already. Feedback and discussion welcome.

(All numbers below are averages for September 21-27, 2015 unless otherwise noted.)

Pageviews

Total: 519 million/day

Context (April 2015-September 2015):

After the conspicuous 4.3% drop the previous week, pageviews decreased a bit further (0.7%) this time. (For a more dramatized view, see the Vital Signs dashboard).

Desktop: 57.5%

Mobile web: 41.3%

Apps: 1.2%

Global North ratio: 77.4% of total pageviews

Context (April 2015-September 2015):

Unique app users

Android: 1.340 million /day

Context (January 2015-September 2015):

iOS: 328k / day

Context (January 2015-September 2015):

New app installations

Android: 42,782/day (Daily installs per device, from Google Play, September 21-27)

Context (September 2014-September 2015):

iOS: 4,603/day (download numbers from App Annie)

Context (September 2014-September 2015):

As a bonus track (because this week’s report doesn’t offer much news otherwise ;) here’s a chart of the day 1 retention rate for the iOS app. (That’s defined as the percentage of users who used the app on the day after first installing it.)

(from August 30 = leftmost bar to September 26, source: iTunes Connect)

It’s not quite clear why the rate dropped around September 16 and then rose again last Wednesday - no feature changes or influx of downloaders from particular sources that we’re aware of during that time.

(Per discussion in last week’s thread, I’ll look into including similar metrics for Android too.)

----

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.

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 "2015-09-21" AND "2015-09-27";

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 "2015-09-21" AND "2015-09-27" 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 "2015-09-20" AND "2015-09-27";

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;

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 20150920 AND 20150927;

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';

https://play.google.com/apps/publish/?dev_acc=02812522755211381933#StatsPlace:p=org.wikipedia&statm=DAILY_DEVICE_INSTALLS&statd=OS_VERSION

https://www.appannie.com/dashboard/252257/item/324715238/downloads/?breakdown=country&date=2014-09-28~2015-09-27&chart_type=downloads&countries=ALL (select “Total”)