Search Behaviour Patterns

8/2/2019 Search Behaviour Patterns

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Search Behavior PatternsRamzi Sh. Alqrainy



Agenda

• Introduction

• Factors that affect user behavior

•

Personas• Patterns of Behavior

• Conclusion

• References



Introduction

• Search, more than any other activity, is a living, evolving processof discovery— a conversation between a customer and the Website. Unfortunately, this conversation is often fraught withmiscommunication, and so it is critical for you to keep thisconversation going even when the customer has initiated asearch that yielded no results.



Factors that affect user behavior

•Search behavior is the result of interplay among severalindependent factors the user brings to the search operation,four of which are described below. Designers have no morecontrol over these than they have over the color of the user’shair.

•

A search engine on an organization’s website or intranet is oftenbuilt to support an overly narrow model of user behavior, whichgoes something like this:

– User types in a search

– Search engine gives back matching results

– User reads the results and picks the best one



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 whatverbiage will work best, and so generally get better results, from

which they’re better able to discern the most useful documents.

1. Domain Expertise



Users who have a better understanding of the breadth of a searchengine’s capabilities have more ways to go about findinginformation. If you know how to use Boolean operators, exactstrings, filtering controls, and have proven strategies for exploitingsearch, then you have a much richer toolset at your disposal. But

search experience also isn’t an absolute requirement for success. Wehave seen that users who are short on technical know-how but richin domain knowledge can often get by. On the other hand,technophiles can have great difficulty finding information in anunfamiliar body of knowledge.

2. Search experience



Search goals will vary from one query to the next, and may bebroadly 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 benefitselections.

3. Goal type

http://www.sigir.org/forum/F2002/broder.pdf












4. Mode of seeking The extent to which users understand what they are trying to finddetermines 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 1989paper ―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.

http://www.gseis.ucla.edu/faculty/bates/berrypicking.html



























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 detailedabove, provides a great starting point for authoring personas.

• For instance, the hypothetical people described below each illustratedifferent areas of domain knowledge, and represent a spectrum of searchexperiences 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 hercompany. Her cognitive style tends to be analytical.

– Dmitry has moderate technical know-how. He works in the benefitsadministration division of his company’s HR department. He learns newinformation globally about as often as he does analytically.

– Kazue is generally uncomfortable with technology, but is a recognized expertin her field of instructional design. She tends to be a global thinker whoprizes an understanding of the big picture.



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



Users sometimes measure the success of a query primarily by thenumber 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.‖

1. Minimizing the results set



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 gaugethe quality of her query.



Some users scan through the results quickly, and if none of thetitles 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 anotherquery.

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.

2. Surveying quickly




– 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.



Other users look only at the first few results before deciding whetherthe 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.

3. Making immediate judgments




–

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 atthe top. This gives the page a second chance to hit the specific

target in Andrea’s mind.



Sometimes users have difficulty translating the concept they want tofind 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.

4. Agonizing over the query




– Consider providing tools that assist in formulating the query,

such as suggestion functions that present searches similar to theone 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.



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 trackingwork.

5. Pogo sticking




– 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 extendedto 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.

http://www.ask.com/

http://www.easysearchlive.com/

http://www.easysearchlive.com/

http://www.ask.com/



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 regardlessof 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 therange of known behavior patterns for your target personas.



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 WebSearch,‖ 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‖



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Search Behaviour Patterns

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