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.

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

2. Motivation
KatyPeter

3. Motivation

4. Motivation

5. Motivation

6. Motivation

7. Motivation
10 minutes later...

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

9. participants &
method

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 Galaxy’s
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
§ tracked all app opens, timestamp and duration of app use
o Yahoo prototype mobile search app (MSearch app)
§ embedded yahoo mobile search, tracked mobile sensors
o Daily online diary
3. Final interview:
o Clarified 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 off) 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
Definitions

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 Welch’s t-tests, significance at p<0.05
• Comparison of application launches, per-
category, before and after search activity
Paired t-tests, significance at p<0.05

21. Analysis of diary and interview data
Grounded-theory affinity analysis

22. results

23. #1
are search & non-search
sessions different?

24. Yes, they are different
● Differ 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 differences
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 significantly more
frequently after mobile search (top 5 categories shown)
Browsers
Email
Tools & Utilities
Photography
Games
…

29. #4
triggers

30. Identified 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

32. #5
post-search actions

33. Identified 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 confirmed they have what I’m 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)

35. #5
complex switching
between apps...

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 stuff, 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 differing 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
different types of mobile search interactions.
o If such probabilities can be detected, future mobile search could pre-empt
these behaviors and offer 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