An In-Situ Study of Mobile Search & Mobile App Interactions
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This study analyzed mobile search and app interactions through logging apps, a search app, and interviews with 18 participants over 2 weeks. The results showed that: 1) Search sessions involved more app launches, unique apps, and longer duration than non-search sessions. 2) Certain app categories like browsers and games were used more after mobile search. 3) Triggers for search included both external stimuli and internal states, and post-search actions included consuming, sharing, and booking information. 4) Participants switched between apps to complete tasks like buying tickets or sharing search results. The implications are that mobile search could better support task completion, sharing, note-taking across sessions and devices.
![App switching to buy tickets.
P8: I will actually go to Ticketmaster, see the price and
then open up another window or another Groupon like that
and then if I get one [groupon code], I'll copy it. Get out of
there and go back to Ticketmaster to where it usually has a
little icon where it says you can enter a coupon code, so
paste it.
Search for
tickets
Check for
deals
Copy+paste](https://image.slidesharecdn.com/chi2015-mobilesearchmobileappinteractions-pdf-150428214646-conversion-gate01/85/An-In-Situ-Study-of-Mobile-Search-Mobile-App-Interactions-36-320.jpg)
An In-Situ Study of Mobile Search & Mobile App Interactions
- 1. an in-situ study of mobile search and app interactions JP Carrascal, Human Media Lab jp@cs.queensu.ca Karen Church, Yahoo Labs kchurch@yahoo-inc.om Presented @ CHI 2015, Seoul, Korea
- 3. Motivation
- 4. Motivation
- 5. Motivation
- 6. Motivation
- 8. ≒ How does mobile search activity interacts with mobile app activity? ≒ What are some common triggers of mobile search and actions that are commonly taken after search? Research Question Mobile apps Triggers & Actions Mobile search
- 10. o 18 participants o Average age 32.7 (sd=9.8) o 8 females, 10 males o All living in SF / Greater Bay Area o Diverse occupations o Varying levels of education: high-school to college o Majority of the devices were Samsung Galaxys Participants
- 11. 1. Initial Interview: o Asked participants about their device, their app usage, their app arrangement patterns, their use of mobile search o Focused on their most recent searches, triggers and actions 2. Installed 2 apps and ran a 2 week in-situ study (Jun-Jul 2014): o App logging software 則р tracked all app opens, timestamp and duration of app use o Yahoo prototype mobile search app (MSearch app) 則р embedded yahoo mobile search, tracked mobile sensors o Daily online diary 3. Final interview: o Clari鍖ed any diary entries o Probed participants about triggers, actions and app interactions Mixed-Method Study
- 12. data collected
- 13. 54,022 app launches (avg 3,001.2, s = 2, 003.9). 394 unique android apps (avg of 52, s = 20.6) > 4 hours per day using mobile apps (s = 248.2 mins). App Usage
- 14. 882 unique queries through the MSearch app 2794 webpage visits Mobile Search Usage
- 15. 535 Total diary entries ~20 Hours of interview data >3000 Individual quotes Online Diary & Interviews
- 16. analysis
- 17. 1-hour of a participant in our study
- 18. Device sessions: sequence of interactions with a device that occur without the device going into standby mode (i.e. displaying turning o鍖) for >30 secs App sessions: sessions that involve at least one app open/app launch Search sessions: app sessions in which the user interacted with mobile search Non-search sessions: app sessions in which the user did not engage with mobile search De鍖nitions
- 19. 1-hour of a participant in our study Non-search session Search session Non-search sessions
- 20. Statistical analysis for app sessions ≒ Two researchers categorized the logged app launches and search queries ≒ Comparison of app launches between Search and Non-search sessions Non-paired Welchs t-tests, signi鍖cance at p<0.05 ≒ Comparison of application launches, per- category, before and after search activity Paired t-tests, signi鍖cance at p<0.05
- 21. Analysis of diary and interview data Grounded-theory a鍖nity analysis
- 22. results
- 23. #1 are search & non-search sessions different?
- 24. Yes, they are di鍖erent Di鍖er in number of app launches, use of unique apps and in session duration o Search sessions involve > 2 times as many app launches as non-search sessions on average o Search sessions involve > 2 times as many unique app usages compared to non-search sessions o Search sessions are almost 4 times longer than non-search sessions in terms of duration
- 25. #2 how do they differ?
- 26. Search vs. Non-Search: Categories Several app categories were used more intensively when people engaged with mobile search, both in terms of app launches and duration of app usage (apps categories with the highest di鍖erences shown) Browsers Games Tools & Utilities Social Networks SMS / Texting
- 27. app use before & after mobile search... #3
- 28. Apps Before & After Search Several categories of apps are launched signi鍖cantly more frequently after mobile search (top 5 categories shown) Browsers Email Tools & Utilities Photography Games
- 29. #4 triggers
- 30. Identi鍖ed 6 Mobile Search Triggers 2 broad categories o External: sensory stimuli o Internal: connected with our thoughts, emotions, body, or habits. 4 External triggers o Media: e.g. watching tv, listening to music, reading a newspaper; o Conversations: face to face as well as in apps; o Tangible: noticing something material in physical surroundings; o Activities & Events: e.g. 4 July, doing something, etc. 2 Internal triggers o Physiological: signals like hungry, stress, etc. o State of Mind: e.g. random thoughts.
- 31. How app interactions trigger search? Manual inspection of data showed interesting connections between app launches and succeeding mobile search queries (anecdotal) Closer Hollywood sign BCBG Generation Jelly Thong Sandals
- 33. Identi鍖ed 9 Post Mobile-Search Actions 9 actions that take place as result of mobile search o Consuming content, e.g. watching, reading, listening o Sharing information/content o Keeping information (digitally, physical notes, mental notes) o Buying goods/services o Booking something o Visiting somewhere o Contacting a person, business or place o Making/doing, e.g. trying a recipe
- 34. How search actions map to app usage? P2: I called store and con鍖rmed they have what Im looking for and will stop by after work Tuesday to buy the item. (Contacting) P1: I posted the picture of a Mohawk warrior on Facebook. (Sharing)
- 36. App switching to buy tickets. P8: I will actually go to Ticketmaster, see the price and then open up another window or another Groupon like that and then if I get one [groupon code], I'll copy it. Get out of there and go back to Ticketmaster to where it usually has a little icon where it says you can enter a coupon code, so paste it. Search for tickets Check for deals Copy+paste
- 37. App switching to share results. P6: Voxer is her favorite, and so, she had me sign up for Voxer so that she can communicate with me, which is actually kind of cool because while I'm searching for stu鍖, we can talk back and forth or we could text or we can send pictures between us P6: I will give her the information and she'll look at it, and then she'll text me something back and then we'll both look at it, so we were just going back and forth with ideas
- 38. implications
- 39. (1) Task Completion Overarching theme is task completion, e.g. buying concert tickets, going to a beach with family, involving the use of several apps Participants used multiple information sources & take common post-search actions Scope for search engines to take app interactions into account
- 40. (2) Sharing Search is frequently conducted collaboratively with loved ones and family Sharing is required in order to make joint decisions and purchases
- 41. (3) Keeping Users need to take notes and/or keep track of their search results Including mental and written notes, digital notes, screenshots and bookmarking In some cases keeping was done for the individual but in many cases it was done for others
- 42. (4) Looking beyond sessions Searches can span multiple sessions to address a given need, and these sessions can span di鍖ering hours, days, weeks, etc. Especially when searching for bigger events like buying a car or planning a vacation. These tasks take more time and involve more research before a decision is made.
- 43. Summary There is a need for more collaborative, shared mobile search that supports joint note-taking & bookmarking, and variable time frame search activity.
- 44. Interesting to gather similar data for a longer time period and with more users to determine if such patterns could be mined to provide predictive mobile search capabilities. o Perhaps the probability of issuing certain queries is higher after using certain types of apps? o Likewise probably of using certain apps is higher after engaging with di鍖erent types of mobile search interactions. o If such probabilities can be detected, future mobile search could pre-empt these behaviors and o鍖er more proactive search experiences. o Essentially supporting users in task continuation and task completion. Future work should focus on cross-session and cross device interactions Future work
- 45. Thank you! Questions? JP Carrascal, Human Media Lab jp@cs.queensu.ca Karen Church, Yahoo Labs kchurch@yahoo-inc.om