Ramzi Alqrainy provides an overview of Search Behavior Patterns and How people deal with Search Engine ?

1. Search Behavior Patterns
Ramzi Sh. Alqrainy

2. Agenda
• Introduction
• Factors that affect user behavior
• Personas
• Patterns of Behavior
• Conclusion
• References

3. Introduction
• Search, more than any other activity, is a living, evolving process
of discovery— a conversation between a customer and the Web
site. Unfortunately, this conversation is often fraught with
miscommunication, and so it is critical for you to keep this
conversation going even when the customer has initiated a
search that yielded no results.

4. Factors that affect user behavior
• Search behavior is the result of interplay among several
independent factors the user brings to the search operation,
four of which are described below. Designers have no more
control over these than they have over the color of the user’s
hair.
• A search engine on an organization’s website or intranet is often
built to support an overly narrow model of user behavior, which
goes something like this:
– User types in a search
– Search engine gives back matching results
– User reads the results and picks the best one

5. 1. Domain Expertise
User behavior has a lot do to with a user’s familiarity with the
subject on which he or she is searching. When searching outside a
domain of expertise, people will be less certain where to start, use
less precise language, and have more difficulty evaluating search
results. By contrast, experts in a field generally know what
verbiage will work best, and so generally get better results, from
which they’re better able to discern the most useful documents.

6. 2. Search experience
Users who have a better understanding of the breadth of a search
engine’s capabilities have more ways to go about finding
information. If you know how to use Boolean operators, exact
strings, filtering controls, and have proven strategies for exploiting
search, then you have a much richer toolset at your disposal. But
search experience also isn’t an absolute requirement for success. We
have seen that users who are short on technical know-how but rich
in domain knowledge can often get by. On the other hand,
technophiles can have great difficulty finding information in an
unfamiliar body of knowledge.

7. 3. Goal type
Search goals will vary from one query to the next, and may be
broadly classified into three categories as outlined by Andrei Broder
in his article ―A Taxonomy of Web Search:‖
– Navigational searches are efforts to reach a particular location,
such as an intranet’s timesheet application.
– Informational searches seek out any documents relating to a
topic, like a description of employee benefits.
– Transactional searches occur when the user primarily wants to
accomplish something online, like changing her benefits
elections.

8. 4. Mode of seeking
The extent to which users understand what they are trying to find
determines their mode of seeking. The level of understanding can
range from known items, where people know exactly what they
need and how to describe it, to much more exploratory searches,
where they have only a loose concept what they want to find.
Furthermore, as Marcia Bates pointed out in her oft-cited 1989
paper ―The Design of Browsing and Berrypicking Techniques for
the Online Search Interface,‖ information needs are often unstable
and may evolve as a user learns more about a subject area.

9. Personas
• Grounding abstract ideas in concrete personas can help bring all of these
factors to life. Personas are descriptions of typical users that illustrate key
attributes that are relevant to the design of a website or online system. An
understanding of the motives underlying user actions, like those detailed
above, provides a great starting point for authoring personas.
• For instance, the hypothetical people described below each illustrate
different areas of domain knowledge, and represent a spectrum of search
experiences and cognitive styles. They will be used to relate the factors
above to the common search behavior patterns that follow.
– Andrea is a technical wiz who is completely comfortable with search engines.
She is a project manager for a mainframe manufacturing division of her
company. Her cognitive style tends to be analytical.
– Dmitry has moderate technical know-how. He works in the benefits
administration division of his company’s HR department. He learns new
information globally about as often as he does analytically.
– Kazue is generally uncomfortable with technology, but is a recognized expert
in her field of instructional design. She tends to be a global thinker who
prizes an understanding of the big picture.

10. Patterns of Behavior
• Despite the large number of variables tugging user actions this
way and that, they translate into a relatively small number of
common patterns of behavior.
1) Minimizing the results set
2) Surveying quickly
3) Making immediate judgments
4) Agonizing over the query
5) Pogo sticking

11. 1. Minimizing the results set
Users sometimes measure the success of a query primarily by the
number of results it returns. If they feel the number is too large, they
add more terms in an effort to bring back a more manageable set.
Given her understanding of how search engines determine
relevance, you’d expect Andrea to do this if she needed to quickly
locate a known item within her domain expertise, like ―mainframe
manufacturing.‖

12. Design recommendations:
– Allow users to filter the search results by categories, so they can reduce the
number of results while making them more topical.
– Include a numeric count of the total number of results returned for the query
and the total number for each category.
– Use ―and‖ as the default operator rather than ―or,‖ so the number of results
narrows instead of growing as the user adds more terms.
– Don’t confound this behavior by truncating the total results set at a round
number like 100 or 500; this makes it difficult for users like Andrea to gauge
the quality of her query.

13. 2. Surveying quickly
Some users scan through the results quickly, and if none of the
titles strike them as an ideal match, they may proceed several
pages deep into the results set. I’ve seen these users go to the
fifth or sixth page of results without hesitation, then go back to
the initial results to look more carefully or submit another
query.
For instance, Dmitry could do this to hedge his strategy if his
task isn’t fully defined. Hopeful that something will just pop
out at him, he may do a quick scan of the first few pages, then
fall back to another strategy if that doesn’t work out.

14. Design recommendations:
– Ensure that result titles are comprehensible at a glance, including
application files like PDFs and Word documents, which often
return cryptic file names by default.
– Highlight the terms that match the words originally submitted to
help people scan the titles and descriptions more easily.
– Allow users to change the number of results shown per page to
avoid navigating through too many paginated results.

15. 3. Making immediate judgments
Other users look only at the first few results before deciding whether
the query was successful or not. Finding nothing, these users may
then resubmit the query or give up on search altogether.
Andrea, the analytical thinker, would be discriminating about a
result’s relevance to a narrowly defined informational goal.
Confident in her expertise, she would also be quick to conclude that
search is flawed if it cannot return a good match in the first few
listings. This behavior requires that the best match be returned as
close to the top of the list as possible.

16. Design recommendations:
– Optimize results for the most commonly submitted queries.
Working from the search logs, try out each of the top queries and
evaluate the quality of the top results returned, then optimize the
content of those pages to improve their ranking.
– When pages cannot be further optimized, include a manually
generated ―Best Bets‖ sidebar to force those matches to appear at
the top. This gives the page a second chance to hit the specific
target in Andrea’s mind.

17. 4. Agonizing over the query
Sometimes users have difficulty translating the concept they want to
find into a specific search phrase. They will often rewrite the query
several times before submitting it, and then focus on revising it
further if the results are not as they had expected them to be.
Less experienced users like Kazue are more likely to show this
behavior, especially if the task isn’t well defined and lies
conceptually outside of her domain. Kazue may also be inclined to
phrase the query generally enough to satisfy her global cognitive
style, but fret over how general is too general.

18. Design recommendations:
– Consider providing tools that assist in formulating the query,
such as suggestion functions that present searches similar to the
one the user is typing.
– Consider including lists of popular searches or automated
storage of the user’s previous queries, saved to a profile or
cookie.

19. 5. Pogo sticking
Some users click several results in rapid succession, quickly
sampling each before settling on a best candidate to meet their
needs. Jared Spool has described this as ―pogo sticking‖—bouncing
up and down between choices of uncertain relative value. This is the
kind of behavior that Dmitry might resort to if the quick surveying
behavior described for him above didn’t yield anything. Assuming
that his temperament is fairly tolerant and he isn’t pressed for time,
Dmitry may decide that he cannot determine the usefulness of pages
without looking at them. These users need support for three primary
tasks: assessing result listings, comparing result pages, and tracking
work.

20. Design recommendations:
– Again, provide comprehensible titles and descriptions on the results page, as
well as highlighted search terms.
– Pages can be even more effectively compared if highlighting can be extended
to the display of the results page itself (as is possible with Yahoo! and Google
toolbars).
– Allow users the option to open results in a new browser window to assist
comparison. Sites like Ask and Easy Search Live are experimenting with page
previews.
– Be sure to include a visited link color on the results page. This is absolutely
essential for Dmitry to keep track of the pages he has already tried and rejected
as he jumps to each of the matches from the hub listing page.

21. Conclusion
• Search behavior varies with domain expertise and technical knowledge,
goal, and mode of seeking. All of these factors will interact in complex
ways to influence a user’s actions. Even then, behaviors will vary
depending upon whether at that moment the user is under pressure, in a
good mood, or any number of other idiosyncrasies.
• The point is that the designer cannot select the behavior that a user will
follow when conducting a search. This may invite the impression that the
design must be overly broad, providing any conceivable function regardless
of the likelihood it will be used, because we cannot predict whether it will
be needed. Fortunately, users’ actual behaviors do fall into generally
describable patterns, each of which has dependencies upon specific
affordances of the interface. This is how designers can better cater to what
appears to be chaos: make available those capabilities that best support the
range of known behavior patterns for your target personas.

22. References
(1) James Kalbach provides an overview of literature around this topic in his article ―Designing
for Information Foragers: A Behavioral Model for Information Seeking on the World Wide
Web‖
(2) For more on expert search behavior, see these two articles: Christoph Hšlscher & Gerhard
Strube (2000): ―Web Search Behavior of Internet Experts and Newbies‖; Suresh K. Bhavanani
(2002): ―Domain-Specific Search Strategies for the Effective Retrieval of Healthcare and
Shopping Information,‖ CHI 2002, pp. 610-611. and Search Behavior Patterns by John
Ferrara
(3) See Ryen W. White & Steven M. Drucker (2007): ―Investigating Behavioral Variability in Web
Search,‖ International World Wide Web Conference 2007, pp. 21-30.
(4) See Donna Maurer (2006): ―Four Modes of Seeking Information and How to Design for
Them.‖
(5) David Fiorito and Richard Dalton further described different types of navigation in their
presentation at the 2004 IA Summit, ―Creating a Consistent Enterprise Web Navigation
Solution‖.
(6) Greg Nudelman is author of ―Designing Search – UX Strategies for eCommerce Success‖

23. ramzi.alqrainy@gmail.com