Hi all,
with this email we are starting a weekly look at our most important readership metrics.
The main purpose is to raise awareness about how these are developing, call out the impact of any unusual events in the preceding week (e.g. the media promotion for the Android app this time) and facilitate thinking about core metrics in general.
We will 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 7-13, 2015 unless otherwise noted.)
Pageviews:
Total: 546 million/day
Context (April 2015-September 2015):
After the drop in June, which by now looks not merely seasonal but likely to be at least partially connected to the rollout of HTTPS-only access begun on June 12, overall pageviews are slightly rising again recently. (Notably, the recent drop in comScore’s numbers - also in their pageview estimates for Wikimedia sites, not reproduced in that report card - is not consistent with our own traffic data; these discrepancies are being looked into.)
Mobile web: 39.9%
Apps: 1.2%
Global North ratio: 77.5% of total pageviews
Context (April 2015-September 2015):
Unique app users
Android: 1.136 million /day
Context (January 2015-September 2015):
While this number is slightly higher than in the preceding week, there’s no noticeable effect visible yet from the media promotion for the Android app (blog post on September 10, media coverage on September 10, 11 and 13).
iOS: 290k / day
Context (January 2015-September 2015):
New app installations
Android: 40,168/day (Daily installs per device, from Google Play, September 7-11)
Context (September 2014-September 2015):
Unfortunately, the stats function of the Google Play is having issues currently and data for recent days has been delayed. (They “expect to resolve the issue shortly”, but the September 11 only became available this morning and I’m sending this report out now, a fuller assessment of the impact of the media campaign will need to wait.) The first two days after the blog post went out on September 10 did not yet show a marked increase:
20150911 | 40648 |
20150910 | 39862 |
20150909 | 39927 |
20150908 | 39981 |
20150907 | 40420 |
iOS: 5,262/day (download numbers from App Annie)
Context (September 2014-September 2015):
We seem to have a slight upwards trend in recent weeks, but it’s still way below the download rate a year ago.
----
For reference, the queries and source links used are listed below (access is needed for each). I’ll also see to upload charts to Commons.
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 "2015-09-07" AND "2015-09-13";
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 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 "2015-09-07" AND "2015-09-13";
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 "2015-09-07" AND "2015-09-13" GROUP BY access_method;
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 20150907 AND 20150913;
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 Android_DAU FROM wmf.mobile_apps_uniques_daily WHERE platform = 'iOS';