This invited talk was given at ECIR 2013 Industry Day in Moscow on the 27th March 2013. The talk was on the topic of mobile search, a research area I've devoted the past 10 years to.
Recently the world has witnessed a revolution in terms of mobile web and mobile search usage. Mobile phones, once deemed as simple communications devices, now provide mobile users with access to a wealth of online content, anytime and anywhere. In 2012, the increasing presence of mobile devices caused desktop search to decline for the first time ever; a level of growth that simply cannot be ignored.
My aim is to take a nostalgic look back at the simple beginnings of mobile search and discuss how, why and in what ways mobile search has evolved over the past 8-10 years. I highlight patterns of mobile search usage and show how they not only differ from desktop search, but they are continually evolving. And instead of taking a single, data-centric viewpoint of mobile search, I also discuss user-centric studies, highlighting the unique needs, intents and motivations of mobile searchers. Finally, I share some thoughts about where mobile search is heading, the challenges that lie ahead and discuss some of the factors that I think are important when it comes to enriching the future search experiences of mobile users.
Karen Church
Research Scientist
Telefonica Research
www.karenchurch.com
@karenchurch
31. Global Mobile Traffic as % of Total Internet Traffic
14
12
% of Internet Traffic
10
8
6
4
2
0
2009 2010 2011 2012
- 2012 Internet Trends Report: http://www.kpcb.com/insights/2012-internet-trends-update
32. Global Mobile Traffic as % of Total Internet Traffic
14
12
% of Internet Traffic
10
8
6
1%
4
2
0
2009 2010 2011 2012
- 2012 Internet Trends Report: http://www.kpcb.com/insights/2012-internet-trends-update
33. Global Mobile Traffic as % of Total Internet Traffic
14
13%
12
% of Internet Traffic
10
8
6
1%
4
2
0
2009 2010 2011 2012
- 2012 Internet Trends Report: http://www.kpcb.com/insights/2012-internet-trends-update
34. “ By 2015 more end users
will access the Internet
through a mobile device
“
than a PC.
- International Data Corporation (IDC) Report 2012
37. 25%
of queries come from mobile devices
- Covario, Mar 2013,
http://searchengineland.com/4-mobile-search-trends-tackled-at-smx-west-2013-151657
38. 1in 3
queries will come from a mobile device
(by end of 2013)
- Covario, Mar 2013,
http://searchengineland.com/4-mobile-search-trends-tackled-at-smx-west-2013-151657
46. User-centric
Diary studies, surveys,
interviews, prototype usage
Understanding perceptions
and intent
Tend to be smaller-scale
Very good at answering WHY
48. M. Kamvar and S. Baluja. A large scale study of wireless search
behavior: Google mobile search. In Proceedings of CHI’06,
pages 701–709. ACM, 2006. [Google 2006]
M. Kamvar and S. Baluja. Deciphering trends in mobile search.
Computer, 40(8):58–62, 2007. [Google 2007]
M. Kamvar, M. Kellar, R. Patel, and Y. Xu. Computers and iphones
and mobile phones, oh my!: a logs-based comparison of search
users on different devices. In Proceedings of WWW’09, pages
801–810. ACM, 2009. [Google 2009]
49. R. Baeza-Yates and J. Velasco. A study of mobile search queries
in japan. In Query Log Analysis: Social and Technological
Challenges, WWW 2007 Workshop, 2007. [Yahoo 2007]
J. Yi, F. Maghoul, and J. Pedersen. Deciphering mobile search
patterns: a study of yahoo! mobile search queries. In
Proceedings of WWW’08, ACM, 2008 [Yahoo 2008]
J. Yi and F. Maghoul. Mobile Search Pattern Evolution: The Trend
and the Impact of Voice Queries. In Proceedings of WWW’11,
ACM, 2011
50. Mobile Operator Studies
K. Church, B. Smyth, P. Cotter, and K. Bradley. Mobile information
access: A study of emerging search behavior on the mobile
internet. ACM Transactions on the Web, 1(1):4, 2007. [Mobile
Operator 2007]
K. Church, B. Smyth, K. Bradley, and P. Cotter. A large scale study
of european mobile search behaviour. In Proceedings of
MobileHCI ’08, pages 13–22. ACM, 2008. [Mobile Operator 2008]
M. Vojnovic. On mobile user behaviour patterns. In International
Zurich Seminar on Communications. IEEE Communications
Society, 2008.
K. Church. and N. Oliver Understanding Portal-Based Mobile
Search: a Case Study. In 2nd Research in the Large Workshop
(held as part of UbiComp ’11)
52. Search engine / Where Dataset From Length Length
publication (Terms) (Chars)
Google (2006) U.S 2005 2.3 15.5
Mobile Europe 2005 2.1 13
Operator (2007)
Yahoo! (2007) Japan 2006 2.3 17.9
Mobile operator Europe 2006 2.2 13.8
(2008)
Google (2007) U.S. 2007 2.6 16.8
Yahoo! (2008) U.S. and Int 2007 2.4 (US) 13.7 (US)
2.1 (Int) 13.6 (Int)
Google (2009) U.S. 2008 2.9 (iPhone) 18.2 (iPhone)
2.4 (Mobile) 15.9 (Mobile)
53. iPhone search behavior is
more similar to desktop
search behavior than other
mobile phones!
54. Mobile queries are less
diverse than desktop queries
but…..this is changing
and device type plays a role
55. Query diversity in mobile search
Search Dataset Top Query Top 1000
engine / From Queries
publication
Google (2006) 2005 1.2% 22%
Google (2007) 2007 0.8% 17%
Google (2009) 2008 3.8% 33%
(Mobile) (Mobile)
0.3% 13%
(iPhone) (iPhone)
56. Clicks have been used as a
measure of search success
Less success in mobile
57. Evolving click patterns
Search engine / Dataset Queries leading
publication From to Clicks
Google (2006) 2005 < 10%
Mobile Operator 2006 <10%
(2008)
Google (2007) 2007 > 50%
62. >50%
of mobile queries related to adult content
Church et al. Mobile information access: A study of emerging search behavior on the mobile internet. ACM
Transactions on the Web, 1(1):4, 2007.
65. Only 1.7% more local queries
issued from iPhone than from a
computer
- Kamvar et al. WWW 2009
66. “ mobile users will continue to search
for a higher proportion of local
content than computer users, but
may look for this information within “
an application that can provide a
richer experience than what a
browser can provide.
- Kamvar et al. WWW 2009
71. Motivators of mobile web usage
Time
Awareness Curiosity
Management
Social Social
Diversion
Connection Avoidance
- Taylor et al. A framework for understanding mobile internet motivations and
behaviors. In Proceedings ofCHI'08 extended abstracts, ACM (2008)
72. Motivators of mobile web usage
Time
Awareness Curiosity
Management
Social Social
Diversion
Connection Avoidance
- Taylor et al. A framework for understanding mobile internet motivations and
behaviors. In Proceedings ofCHI'08 extended abstracts, ACM (2008)
73. Diary Study of Mobile Internet Use
- Church & Oliver, Understanding Mobile Web and Mobile Search Use in Today’s
Dynamic Mobile Landscape, MobileHCI2011
74. Diary Study of Mobile Internet Use
Why mobile users access the Web?
Their motivations and intents of use
In what situations or contexts?
What’s lacking?
- Church & Oliver, Understanding Mobile Web and Mobile Search Use in Today’s
Dynamic Mobile Landscape, MobileHCI2011
75. Motivations of web usage
Classified participant motivations according to the list
of motivations generated by Taylor et al. 2008 and
found very similar results
Motivation # Diary Entries % Diary Entries
Awareness 401 48
Time management 205 24.6
Curiosity 40 4.8
Diversion 106 12.7
Social Connection 80 9.6
Social Avoidance 3 0.4
Total 835 100%
80. As well as settling
friendly bets /
Proving someone
wrong!
81. Some examples from our
participants as to what
conversations and interactions
lead them to use mobile
search…
82. “Having lunch with colleagues and we
couldn’t remember the character name
of Graham Norton in Father Ted”
83. “I was looking for the history of the dance
move The Moonwalk. I was intending to
find a wikipedia page about it, and this
was the first site that came up, I found the
information I was looking for and proved
my brother wrong about a statement he
had made. We were having a discussion
as to whether the moonwalk was originally
a dance move or a mime theatre action”
84. “The name of actor based on a known
film they had appeared in. I was
discussing an actor in random
conversation. I was in a bar with friends
socializing and I used search to fill in gaps
in memory”
86. 70% of mobile Web access is
@home or @work
- Church & Oliver, Understanding Mobile Web and Mobile Search Use in Today’s Dynamic
Mobile Landscape, MobileHCI2011
87. 66% while watching TV
http://searchengineland.com/highest-use-of-mobile-search-at-home-report-69557
92. 65 %
Mobile searches take place in presence
of other people
- Church & Oliver, Understanding mobile web and mobile search use in today’s
dynamic mobile Landscape, MobileHCI 2011
93. 67 %
searches conducted while in transit
were social, compared to only 53%
while stationary
- Teevan et al.. Understanding the importance of location, time and people in mobile
local search behavior. MobileHCI 2011
94. how, why and in what situations
do people use mobile search in
social settings for shared
information needs?
- Church et al, I Wanted to Settle a Bet! - Understanding Why and How People Use
Mobile Search in Social Settings, MobileHCI 2012
98. Studies of mobile information needs
Sohn, T., Li, K. A., Griswold, W. G., and Hollan,J. D. A diary study of
mobile information needs. In Proceedings of CHI'08, ACM (2008)
Church, K and Smyth, B. (2009) Understanding the intent behind
mobile information needs. In Proceedings of the 14th
International Conference on Intelligent User Interfaces (IUI ’09)
Church, K., Cherubini, M., Neumann, J. and Oliver N. (2011)
Understanding Mobile Information Needs on a Large-Scale:
Tools, Experiences and Challenges. In 2nd Research in the Large
Workshop (held as part of UbiComp ’11
Heimonen, T. Information needs and practices of active mobile
internet users. In Proceedings of Mobility '09, ACM (2009)
100. FaThumb
- Karlson et al. FaThumb: A Facet-based interface for mobile search, CHI 2006
101. Mobile Findex
Heimonen, T. (2012). How do users search the mobile Web with a clustering interface? A longitudinal study.
International Journal of Mobile Human–Computer Interaction, 4(3), 44–66
102. Questions not Answers
- Jones et al, Questions not answers: a novel mobile search technique, CHI 2007
- Arter et al. Incidental information and mobile search, MobileHCI 2007
105. Future Work
• Analysis of more detailed search data could
reveal more interesting results and more concrete
design implications for future mobile search
services:
– Temporal patterns: by identifying certain behaviours
based on time-of-day or day-of-week then certain
mobile search requests could be preempted and
quick access to answers could be provided.
– User demographics: it’s likely that search patterns
differ based on differ user demographics, e.g.
gender.
– If we had access to location information we could
study the impact of location in mobile search/mobile
users
Challenges & Open Q’s
107. Understanding truly mobile vs.
using mobile in non-mobile
contexts?
Exploring casual mobile
information access vs. need to
know information access?
109. The mobile phone will be the first
point of contact to online
content for some users
How do we make sure that
search and information access
experiences for feature phone
users are enriching?
115. We’ve moved from desktop to
tablet to mobile. We’ll have
access in our cars, on our TVs…
What is next and what new
behaviors, interactions and
needs will we have to support?
116. “ NO ONE WILL EVER
USE THEIR MOBILE
PHONE TO SEARCH
“
THE WEB.
- Anonymous Reviewer
117. thank you! Qs?
Karen Church
www.karenchurch.com
karen@tid.es
@karenchurch
Images from: Flickr (or where acknowledge) – others from stock.xchng http://www.sxc.hu
119. More related research papers
• Cui, Y., and Roto, V. How people use the web on mobile
devices. In Proceeding of WWW '08, ACM (2008)
• Hinze, A. M., Chang, C., and Nichols, D. M. Contextual queries
express mobile information needs. In Proceedings of
MobileHCI '10, ACM (2010)
• Kaikkonen, A. Full or tailored mobile web- where and how do
people browse on their mobiles? In Proceedings of Mobility'08,
ACM (2008)
• Lee, I., Kim, J., and Kim, J. Use contexts for the mobile internet:
A longitudinal study monitoring actual use of mobile internet
services. International Journal of Human-Computer Interaction
18, 3 (2005)
• Nylander, S., Lundquist, T., and Brannstrom, A. At home and
with computer access: why and where people use cell phones
to access the internet. In Proceedings of CHI'09, ACM (2009)
120. More related research papers
• Chua, A. Y. K., Balkunje, R. S., and Goh, D.H.-L. Fulfilling mobile
information needs: a study on the use of mobile phones. In
Proceedings of ICUIMC '11, ACM (2011)
• Hinman, R., Spasojevic, M., and Isomursu, P. They call it surfing
for a reason: identifying mobile internet needs through pc
internet deprivation. In Proceedings of CHI '08 extended
abstracts, CHI '08, ACM (2008)
• A. Amin, S. Townsend, J. Ossenbruggen, and L. Hardman.
Fancy a drink in canary wharf?: A user study on location-
based mobile search. In Proceedings of INTERACT ’09:, pages
736–749. Springer-Verlag, 2009.
• C. Tossell, P. Kortum, A. Rahmati, C. Shepard, and L. Zhong.
Characterizing web use on smartphones. In Proceedings of the
SIGCHI Conference on Human Factors in Computing Systems,
CHI ’12, pages 2769–2778. ACM, 2012