Mobile-l October 2015

mobile-l@lists.wikimedia.org

50 participants
25 discussions

Fwd: [Analytics] Eventlogging replication issues
by Tilman Bayer 27 Oct '15

27 Oct '15

Forwarding, as this is affecting a lot of the "Mobile..." tables on stat1003 (see the list in the linked incident documentation) ---------- Forwarded message ---------- From: Nuria Ruiz <nuria(a)wikimedia.org> Date: Mon, Oct 26, 2015 at 8:50 AM Subject: [Analytics] Eventlogging replication issues To: "A mailing list for the Analytics Team at WMF and everybody who has an interest in Wikipedia and analytics." <analytics(a)lists.wikimedia.org> Cc: Jaime Crespo <jcrespo(a)wikimedia.org> Hello: There are replication issues regarding Eventlogging data. For some tables (see: https://wikitech.wikimedia.org/wiki/Incident_documentation/20151022-EventLo…) data has not been replicated since 2015-10-22. All dashboards read from the slave rather than master so the data they display is outdated until this issue is resolved. Ditto for any query running on 1002. You can follow the work of our DBA on this regard on the following ticket: https://phabricator.wikimedia.org/T116599 Thanks, Nuria _______________________________________________ Analytics mailing list Analytics(a)lists.wikimedia.org https://lists.wikimedia.org/mailman/listinfo/analytics -- Tilman Bayer Senior Analyst Wikimedia Foundation IRC (Freenode): HaeB

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Cleanup of Reading/Web/Team
by Joaquin Oltra Hernandez 26 Oct '15

26 Oct '15

Hi! I've cleaned https://www.mediawiki.org/wiki/Reading/Web and moved the mobile specific information to https://www.mediawiki.org/wiki/Reading/Web/Mobile Feedback welcome! Cheers

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"Ambient Details from Wikipedia" (third-party Blackberry app)
by Tilman Bayer 26 Oct '15

26 Oct '15

FYI, there's a new commercial app ($0.99) that offers a Nearby-like functionality on Blackberry: https://appworld.blackberry.com/webstore/content/59979896/ http://world-of-blackberry.com/ambient-details-from-wikipedia-new-applicati… -- Tilman Bayer Senior Analyst Wikimedia Foundation IRC (Freenode): HaeB

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[Apps] Android Wikipedia beta app release (2.1.132-beta-2015-10-23)
by Stephen Niedzielski 24 Oct '15

24 Oct '15

The Android team[0] is happy to announce a new Wikipedia Android app beta release, v2.1.132-beta-2015-10-23[1]. In precisely 500 characters, this revision contains the following features and fixes[2]: * More consistent article language and simpler app language selection dialog. * Fixed occasional abnormal CPU usage * Many UI enhancements and tweaks. * Improved crash reporting. * Better link preview UI and extract. * Add preference to enable/disable link previews. * Use higher resolution icons when possible. * Display system notification after saving an image. * Fix page thumbnail caching. * Fix possible crash when sharing highlighted text. * Fix possible crash when returning to Nearby screen. This release saw volunteer contributions from Daniel Rey[3] and Wikinaut[4]. Great work, devs! You, too, can help make it better! Read our getting started guide[5]. We can't wait for your contributions! -The WMF Android team [0] https://www.mediawiki.org/wiki/Wikimedia_Apps/Team#Android_App [1] Rolling out at https://play.google.com/store/apps/details?id=org.wikipedia.beta [2] A complete list of changes is available at http://git.wikimedia.org/commits/apps%2Fandroid%2Fwikipedia/beta%2F2.1.131-… [3] https://twitter.com/DanReyLop [4] https://twitter.com/Wikinaut, WikiMail [5] https://www.mediawiki.org/wiki/Wikimedia_Apps/Team/Wikipedia_Android_app_ha…

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Readership metrics for the week until October 18, 2015
by Tilman Bayer 23 Oct '15

23 Oct '15

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 are still iterating 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. The most interesting news this time is the effect of the iOS Wikipedia app getting featured in the App Store, see below. For those who haven’t been following the discussion on this list (Mobile-l), I’d also like to highlight that Jon Katz has recently posted <https://lists.wikimedia.org/pipermail/mobile-l/2015-October/009839.html> (to quote his TLDR) “Directional data [that] suggests that the project-wide drop we see in pageviews is, in part, caused by shorter sessions on mobile web compared to desktop (and a migration from desktop to mobile web)”. Now to the usual data. (All numbers below are averages for October 12-18, 2015 unless otherwise noted.) Pageviews Total: 528 million/day (+0.9% from the previous week) Context (April 2015-October 2015): See also the Vital Signs dashboard <https://vital-signs.wmflabs.org/#projects=all/metrics=Pageviews> Desktop: 57.3% Mobile web: 41.5% Apps: 1.2% Global North ratio: 76.9% of total pageviews (previous week: 77.0%) Context (April 2015-October 2015): Unique app users Android: 1.16 million /day (+-0.0% from the previous week) Context (January 2015-October 2015): Not much news here. iOS: 280k / day (+0.9% from the previous week) Context (January 2015-September 2015): The overall DAU number don’t yet show a noticeable impact of the app getting featured (see below), we’ll see. New app installations Android: 37.9k/day (-4.0% from the previous week) (Daily installs per device, from Google Play) Context (July-October 2015): The sustained rise in installs we’ve been seeing since around August 21 (see also the discussion in last week’s report about the possible connection with the “Back to School” recommendation in the Play store) is ebbing now, whereas the uninstall rate holds pretty much constant. iOS: 6.69k/day (+48.0% from the previous week) (download numbers from App Annie) Context (July 24-Oct 21, 2015): Last week, the Wikipedia app became featured on the iOS App Store homepage (below the fold, as second item in a list called "Learn Your Facts"). The effect on downloads is already clear - I’m including the last three days in the above chart too; we’ll see how the impact on user numbers and pageviews turns out. Josh from the IOS team is following this closely. ---- 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=20…> . 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 "2015-10-12" AND "2015-10-18"; 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 "2015-10-12" AND "2015-10-18" 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 "2015-10-12" AND "2015-10-18"; 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 20151012 AND 20151018; 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#StatsPla… https://www.appannie.com/dashboard/252257/item/324715238/downloads/?breakdo… (select “Total”) -- Tilman Bayer Senior Analyst Wikimedia Foundation IRC (Freenode): HaeB

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Older iOS test devices available
by Brion Vibber 23 Oct '15

23 Oct '15

Hey all -- I've got a few older ios devices that I no longer test with much, and am looking to clear them out of my inventory. If nobody working on the Wikipedia app needs them I'll sell em on gazelle or something, so speak up quick! This is still supported & 64-bit, but a couple generations behind the latest: * iPhone 5s (retina 4") These 32-bit devices run current iOS 9.1 but will probably be dropped by ios 10: * iPhone 4s (retina 3.5") * iPod Touch 5th-gen (retina 4") * iPad mini first-gen (non-retina 7.9") And these are stuck on ios 6: * iPhone 3Gs (non-retina 3.5") * a second one! I can bring them into the WMF office next week, or ship them to wherever. -- brion

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Tilman is joining the Reading Team!
by Jon Katz 19 Oct '15

19 Oct '15

Hi Everyone, I’m happy to announce that, as of today, Tilman Bayer has officially joined the Reading product team as a Senior Analyst. He will increase our capacity for understanding our users and the impact of our efforts through data analysis. Tilman is responsible for: - generating our primary metrics and communicating them - consulting on, analyzing and communicating the results of feature-specific instrumentation - driving best practices within the team with regard to analysis (aided by his background in mathematics) Tilman has been shadowing the team for about a quarter, and has ramped up his involvement dramatically over the last month. During this period, Tilman has moved quickly and is already owning the analysis of a significant number of our ongoing projects. Tilman’s weekly reading metrics report (example <https://drive.google.com/a/wikimedia.org/file/d/0B-YjaiFnAja3eGdIUGlSV0oxTW…>) is currently being sent out to the Mobile-l mailing list (which serves as the Reading team’s primary public mailing list). We are still gathering feedback from the subscribers of that list and once we have a sustainable and stable format, we hope to share more widely. Tilman has been working with us since July 2011, and has been a Wikipedian since 2003. He was an analyst on the Communications team until Erik Moeller asked him to join Product & Strategy at the beginning of this year. Tilman will be moving out of his current role in Terry’s department where he is right now wrapping up the current round of quarterly reviews and preparation of the organization-wide quarterly report for Q1. Best, Jon

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Fwd: Wikimedia Foundation quarterly reviews for July-September 2015
by Tilman Bayer 17 Oct '15

17 Oct '15

Forwarding regarding the Reading team's quarterly review documentation ---------- Forwarded message ---------- From: Tilman Bayer <tbayer(a)wikimedia.org> Date: Fri, Oct 16, 2015 at 10:15 PM Subject: Wikimedia Foundation quarterly reviews for July-September 2015 To: Wikimedia Mailing List <wikimedia-l(a)lists.wikimedia.org> Cc: Wikimedia developers <wikitech-l(a)lists.wikimedia.org> Greetings everyone, the Wikimedia Foundation's quarterly reviews of teams' work in the past quarter (July-September, Q1 of the 2015-16 fiscal year) took place last week. Minutes and slides for those meetings are now available: Community Engagement: https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… Discovery: https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… Reading and Advancement (with Fundraising Tech): https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… Editing (comprising the Collaboration, Language Engineering, Multimedia, Parsing, and VisualEditor teams): https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… Infrastructure (comprising the Analytics, Release Engineering, Services, TechOps, and Labs teams) and CTO (comprising the Design Research, Research & Data, Performance, and Security teams): https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… Legal, Talent & Culture (HR), Communications, Finance & Administration & Office IT, and Team Practices: https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… As usual, much of this information will also be available in consolidated form as part of the general WMF quarterly report for Q1, which is planned to be published on October 19. See https://meta.wikimedia.org/wiki/WMF_Metrics_and_activities_meetings/Quarter… for some general background about the Foundation's quarterly review process. -- Tilman Bayer Senior Analyst Wikimedia Foundation IRC (Freenode): HaeB -- Tilman Bayer Senior Analyst Wikimedia Foundation IRC (Freenode): HaeB

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Pageview drop
by Jon Katz 15 Oct '15

15 Oct '15

Hi Folks, TLDR: Directional data suggests that the project-wide drop we see in pageviews is, in part, caused by shorter sessions on mobile web compared to desktop (and a migration from desktop to mobile web) *Context:* Danny and I took some time last week to try and understand the dramatic drop in pageviews that we saw globally and in the global south just over the last quarter. The numbers we quoted in the Q1 quarterly review <https://commons.wikimedia.org/wiki/File:WMF_Reading_Quarterly_Review_Q1_201…> last week were (pageviews across all projects, platforms and geographies): - -12.4% Quarter over quarter - -7% Year over year* *The YoY data is sampled and there may be anomalies that force us to consider an inaccuracy of up to +-5% difference possible (i.e. a YoY change from -2% to -12%) (source: Tilman, Hive). Here is the answer to one question we had: Is this drop due to fewer people or fewer pages per user? I will preface this by saying that I erred on the side of getting this out sooner than in making it incredibly replicable, share-able. If you are interested in the specific queries or access to the raw data, I will prep and send it out. Otherwise, curious to hear your questions/concerns/suggestions. *Details:* Is this drop due to fewer people or fewer pages per user? The answer here, is interesting and the impact is more significant than I would have expected. On Desktop the pageviews per visit (as internal referers/external+ unknown) is relatively constant. On Mobile web, however, the pageviews per visit is much lower and appears to be dropping. The following graphs explain: Daily *desktop* pageviews, by referer 4/13--present (all wikipedias, all geos). There is strong correlation between pageviews that come from the outside v. the inside: [image: Inline image 3] [image: Inline image 4] Daily *Mobile web* pageviews, by referer 4/13--present (all wikipedias, all geos). [image: Inline image 2] Compared the 60% we have on desktop, you can see that the ratio is 40% (33% smaller) on mobile and that this gap has widened (though not in the last 2 years): [image: Inline image 5] I don't know if we can explain all of our traffic decreases to the drop in session length, but it is certainly a big factor. Basically 60% of our pageviews (internal) shrink by 33% on mobile. So all else being equal, if we transfer all our traffic to mobile we lose 33% of our pageviews. Right now we're at 50%. This assumes that there is no change in numbers of sessions...on which we have no data right now. *Next Steps:* Unless I hear otherwise, I think the next steps are to start thinking through what the implications are. - Do we try to identify reasons users might be skipping out earlier on mobile and fixing those? - Do we try to make it easier for people to find content on mobile? - Maybe sessions across the internet are just shorter on mobile and we should focus our efforts on helping people find us? Regardless, I find this a bit comforting, because having the same number of users who spend less time would be much better than reaching fewer people: controlling the experience once they found us is relatively easier than altering the channels by which people find us in the first place. Again questions/concerns/suggestions encouraged. -J mobile, which is a 15% drop in pageviews (again, assuming a 1:1 traffic switch).

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Browse Hypothesis Results
by Jon Katz 14 Oct '15

14 Oct '15

Hi Team, I just wanted to update you on the results of something we internally referred to as the '*browse' *prototype. TLDR: as implemented the mobile 'browse by category' test did not drive significant engagement. In fact, as implemented, it seemed inferior to blue links. However, we started with a very rough and low-impact prototype, so a few tweaks would give us more definitive results. Here is the doc from which I am pasting from below: https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz… Questions/comments welcome! Best, J Browse Prototype Results  Intro <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Process <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Results <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Blue links in general <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Category tags <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Conclusion and Next Steps <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Process <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…> Do people want to browse by categories? <https://docs.google.com/document/d/1Mqw-awAcp01IcLhHPsHmWsqaAyK1l2-w_LMDtiz…>  Intro As outlined in this doc <https://docs.google.com/presentation/d/1ZssE8G0P5WVg8XmkBTi5G3n4OdLHPFGWZDZ…>, the concept is a tag that allows readers to navigate WP via categories that are meaningful and populated in order of 'significance' (as determined by user input). The hypothesis: - users will want to navigate by category if there are fewer, more meaningful categories per page and those category pages showed the most ‘notable’ members first. Again, see the full doc <https://docs.google.com/presentation/d/1ZssE8G0P5WVg8XmkBTi5G3n4OdLHPFGWZDZ…> to understand the premise. Process The first step was to validate: do users want to navigate via category? So we built a very lightweight prototype on mobile web, en wikipedia (stable, not beta) using hardcoded config variables, in the following categories ( ~4000 pages). Here we did not look into sub-categories with one exception (see T94732 <https://phabricator.wikimedia.org/T94732> for details). There was also an error and 2 of the categories did not have tags implemented (struck through, below) Category Pagecount NBA All Stars 400 American Politicians 818 Object-Oriented Programming Languages 164 European States 24 American Female Pop Singers 326 American drama television series 1048 Modern Painters 983 Landmarks in San Francisco, California 270 Here is how it appeared on the Alcatraz page When the user clicked the tag, they were taken to a gather-like collection based on manually estimated relevance (sorry cropped shot) The category pages were designed to show the most relevant (as deemed by me) to the broadest audience, first. Here is the ordering: https://docs.google.com/spreadsheets/d/12xLXQsH1zcg6E8lDuSonumZNdBvfaBuHOS1… This was intended to lie in contrast with our current category pages, which are alphabetical and not really intended for human browsing: https://en.wikipedia.org/wiki/Category:American_male_film_actors We primarily measured a few things: - when a tag was seen by a user - when a tag was clicked on by a user - when a page in the new ‘category view’ was clicked on by a user As a side effort, I looked to see if overall referrals from pages with tags went up--this was a timed intervention rather than an a/b test and given the click-thru on the tags, the impact would have been negligible anyway. This was confirmed by some very noisy results. Results Blue links in general One benefit of the side study mentioned in the previous paragraph is that I was able to generate a table that looked at the pages in question before we started the test that shows a ratio of total pageviews/pageviews referred by a page (estimate of how many links were opened from that page). Though it is literally just for 0-1 GMT, 6/29/15, now that we have the pageview hourly table, a more robust analysis can tell us how categories differ in this regard: Category links clicked #pvs clicks/pvs Category:20th-centuryAmericanpoliticians 761 1243 61% Category:Americandramatelevisionseries 5981 8844 68% Category:Americanfemalepopsingers 2502 4280 58% Category:LandmarksinSanFrancisco, 104 287 36% Category:Modernpainters 136 369 37% Category:NationalBasketballAssociationAll-Stars 1908 3341 57% Category:Object-orientedprogramminglanguages 48 181 27% Category:WesternEurope 657 1221 54% Grand Total 12099 19766 50% You can see here that for pages in the category ‘Landmarks in San Francisco’, if there are 10 pageviews, 5.4 clicks to other pages are generated on average. I do not have the original queries for this handy, but can dig them up if you’re really interested. Category tags Full data and queries here: https://docs.google.com/a/wikimedia.org/spreadsheets/d/1vD3DopxGyeh9FQsuTQD… The tags themselves generated an average click-through rate of .18%. Given the overall click thru rate on the pages estimated above ~50%, this single tag is not driving anything significant. Furthermore, given Leila and Bob’s paper suggest that this is performing no better than a mid-article click--given the mobile web sections are collapsed, I would need to understand more about their method to know just how to interpret their results against our mobile-web only implementation. Furthermore, our click through rate used the number of times the tag appeared on screen as the denominator, whereas their research looked at overall pageviews. This being noted, the tag was implemented to be as obscure as possible to establish a baseline. Furthermore, any feature like this would probably be different in the following ways: - each page would be in 1-4 tag groups (as opposed to just 1) - each page would be tagged, creating the expectation on the part of the user that this was something to look for - presumably the categories could be implemented as a menu item as opposed to being buried at the bottom of the page (and competing with features like read more. - Using the learnings from ‘read more’ tags with images or buttons would likely fare much better. The follow graph shows: - number of impressions on the right axis - click-thru-rate on the left-axis. When you look at click through rates on the ‘category’ pages themselves, you see that they average at 41% (Chart below) Meaning that for every 10 times a user visited a category page, there were 4.1 clicks to one of those pages as a result. Here is the same broken up by category: Each ‘category’ page here had at least 400 visits, and you can see that the interest seems to vary dramatically across categories. It is worth noting that the top three categories here are the ones with the fewest entities. Each list, however, was capped at ~50 articles, so it is unclear what might be causing this effect, if it is real. As mentioned above, the average article page has an overall click rate of 50%. So this page of categories did not have the click-through rate that a page has. However, this page had summaries of each of the pages, so it could be that users were generating value beyond what a blue link would provide. A live-user test of Gather collections, from whom this format was borrowed, suggested that the format used up too much vertical space on each article and was hard to flip through. Shortening the amount of text or image space might be something to try to make the page more useful Conclusion and Next StepsProcess - This was the first time I am aware of that we ran a live prototype and learn something without building a scalable solution. Win - Developer time was estimated at 1 FTE for 2 weeks (by pheudx), but the chronological time for pushing to stable took a quarter. Room for improvement - The time to analysis was almost 2 quarters, due to a lack of data analysis support (I ran the initial analysis within 2 weeks of launch, during paternity leave, but was unable to go back and get it ready to distribute for 3 months). Room for improvement--possibly solved by additional Data Analyst. This experiment was not designed to answer questions definitively in one round, but with the understanding that multiple iterations would allow us to fully answer our questions. The long turn-around time, particularly around analysis and communication, meant that tweaking a variable to test the conclusions or the new questions that arosee below will involve a whole lot more work and effort than if we had been able to explore modifications within a few weeks of the initial launch. Do people want to browse by categories? Category tags at the bottom of the mobile web page in a dull gray background that lead to manually curated categories are not a killer feature :) I would be reluctant to say that this means users are not interested in browsing by category, however. For instance, it is likely that - users did not notice the tag, even if it appeared on screen - users are accustomed to our current category tags on desktop and not interested in that experience - users who did like the tag were unlikely to find another page that had it--there was no feedback mechanism by which the improved category page would drive additional tag interactions - the browse experience created was not ideal If we decide to pursue what is currently termed “cascade c: update ux”, I would like to proceed with more tests in this arena, by altering the appearance and position of the tags, and by improving the flow of the ‘category’ pages. If we choose a different strategy, hopefully other teams can build off of what was learned here.

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Mobile-l October 2015