Dear Tilman, Can you provide a link for this summary below?
Thank you, *~Orsolya* 2016-02-18 23:37 GMT+01:00 Tilman Bayer <tba...@wikimedia.org>: > Hi all, > > this resumes the usual look at our most important readership metrics. > Among other things, this time we observe the annual Christmas slump in > pageviews, hail the advent of the mobile singularity (December saw the > first ever day with >50% mobile pageviews), and resolve the mystery of the > Android app’s installation drop since mid November. > > 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; feedback and discussion welcome. > > After switching away from the weekly schedule (week-over-week and > month-over-month changes are now being recorded on the Product page > <https://www.mediawiki.org/wiki/Wikimedia_Product#Reading> at > MediaWiki.org) we also skipped an issue and added one week, so this edition > of the report covers a timespan of nine weeks. > > See also the slides from the Reading team’s quarter review meeting > <https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarterly_reviews/Reading_and_Community_Tech,_January_2016> > on January 20 for an in-depth look at various metrics. > > Now to the usual data. (All numbers below are averages for December 7, > 2015 to February 7, 2016 unless otherwise noted.) > > Pageviews > > Total: 529 million/day > > Context (April 2015-February 2016): > > > > (see also the Vital Signs dashboard > <https://vital-signs.wmflabs.org/#projects=all/metrics=Pageviews>) > > Total pageviews saw a sharp drop about a week before Christmas (almost > entirely on desktop), coinciding with a drop > <http://discovery.wmflabs.org/external/#traffic_by_engine> in Google > referrals. But both recovered in early January, even rising above earlier > levels, thanks to mobile (cf. below). Historical data from one and two > years ago shows a very similar slump in total and desktop pageviews in the > second half of December (with a lasting increase in mobile around > Christmas, too), so I’m interpreting this as seasonal even though it > preceded the actual holidays by a few days. In January 2014, traffic did > not fully recover to the levels of November/early December. In January > 2015, it rose slightly above them, similar to now. > > Desktop: 54.3% > > Mobile web: 44.4% > > Apps: 1.3% > > Context (April 2015-February 2016): > > > December 20, 2015 will forever be engraved in Wikimedia history as the > first day where mobile pageviews surpassed desktop pageviews (51% vs. 49%). > It was a Sunday - as we have known for a long time, mobile usage is higher > on weekends. In general, the mobile percentage over a whole week still > remains well below 50%. But even as desktop pageviews recovered from the > Christmas slump at the beginning of January, the mobile percentage remains > roughly 2% higher than before mid-December - quite likely due to a lot of > new phones entering usage as Christmas presents. > > Global North ratio: 78.3% of total pageviews > > Context (April 2015-February 2016): > > New app installations > > Android: 38.4k/day > > Daily installs per device, from Google Play > > Context (January 2015-February 2016): > > As reported earlier, the app was featured twice on Google Play in recent > months, and we can now estimate how many additional installs each may have > caused. November’s placement in the “new and updated” section appears to > have brought in more than 200k installs, and from early December to early > January, the apps was featured as one of the “Best Apps of 2015” in many > countries, resulting in around 350k additional installs. > > The preceding reports also described how we noticed a sharp drop in the > new install rate around November 12, and started investigating the cause > with our contact at Google. After some detective work, it turned out that > the app had been benefitting (since April) from a new feature > <https://googlewebmastercentral.blogspot.com/2015/04/drive-app-installs-through-app-indexing.html> > in Google Search showing install buttons for a website’s app next to search > results from that site for general search terms. Google ended this > experiment in November, causing the app’s baseline install rate to drop > significantly (coincidentally around the end of the “new and updated” > promotion). Going forward, this means that the ongoing growth rate > (installs minus uninstalls) remains much lower than it was during most of > 2015. > > > iOS: 4.94k/day > > Download numbers from App Annie > > Context (last three months): > > Like for the Android app, there was a notable bump around Christmas, but > also an even larger spike on January 14 - the reason is not clear to us. > > App user retention > > Android: 16.8% > > (Ratio of app installs opened again 7 days after installation, among all > installed during the previous week. 1:100 sample) > > Context (last four months): > > Retention for installations since around Christmas appears to be higher; > but the data is quite noisy. > > 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) > > As reported earlier, we encountered data quality issues with this metric. > We eventually received an explanation from Apple last week, but it doesn’t > look very satisfactory for our purposes. We are now working > <https://phabricator.wikimedia.org/T126693> to measure retention > ourselves via EventLogging, like we do on Android. > Unique app users > > Android: 1.206 million / day > > Context (last four months): > > A clearly visible and lasting increase around Christmas, which again > indicates that the retention rates for the install peak around that time > were higher than during the install peaks caused by the Google Play > promotions (even though they resulted in more installs initially). > > iOS: 303 k / day > > Context (last four months): > > Similar to Android, a clearly visible and lasting increase around > Christmas. > > ---- > > For reference, the queries and source links used are listed below (access > is needed for each). Unless otherwise noted, all content of this report is > © Wikimedia Foundation and released under the CC BY-SA 3.0 > <https://creativecommons.org/licenses/by-sa/3.0/> license. 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*9) 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 "2015-12-07" > AND "2016-02-07"; > > 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 > 0 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 "2015-12-07" > AND "2016-02-07" 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 "2015-12-07" > AND "2016-02-07"; > > 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 > 0 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_02812522755211381933/stats/installs/ > (“overview”) > > > https://www.appannie.com/dashboard/252257/item/324715238/downloads/?breakdown=country&date=2015-12-07~2016-02-07&chart_type=downloads&countries=ALL > (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 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 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 > > _______________________________________________ > Mobile-l mailing list > Mobile-l@lists.wikimedia.org > https://lists.wikimedia.org/mailman/listinfo/mobile-l > >
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