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Agenda• Introduction• Factors that affect user behavior• Personas• Patterns of Behavior• Conclusion• References
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.
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
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.
2. Search experienceUsers 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. Butsearch 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.
3. Goal typeSearch goals will vary from one query to the next, and may bebroadly classified into three categories as outlined by Andrei Broderin 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.
4. Mode of seekingThe extent to which users understand what they are trying to finddetermines their mode of seeking. The level of understanding canrange from known items, where people know exactly what theyneed 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 forthe Online Search Interface,‖ information needs are often unstableand may evolve as a user learns more about a subject area.
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.
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 set2) Surveying quickly3) Making immediate judgments4) Agonizing over the query5) Pogo sticking
1. Minimizing the results setUsers sometimes measure the success of a query primarily by thenumber of results it returns. If they feel the number is too large, theyadd more terms in an effort to bring back a more manageable set.Given her understanding of how search engines determinerelevance, you’d expect Andrea to do this if she needed to quicklylocate a known item within her domain expertise, like ―mainframemanufacturing.‖
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.
2. Surveying quicklySome users scan through the results quickly, and if none of thetitles strike them as an ideal match, they may proceed severalpages deep into the results set. I’ve seen these users go to thefifth or sixth page of results without hesitation, then go back tothe initial results to look more carefully or submit anotherquery.For instance, Dmitry could do this to hedge his strategy if histask isn’t fully defined. Hopeful that something will just popout at him, he may do a quick scan of the first few pages, thenfall back to another strategy if that doesn’t work out.
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.
3. Making immediate judgmentsOther users look only at the first few results before deciding whetherthe query was successful or not. Finding nothing, these users maythen resubmit the query or give up on search altogether.Andrea, the analytical thinker, would be discriminating about aresult’s relevance to a narrowly defined informational goal.Confident in her expertise, she would also be quick to conclude thatsearch is flawed if it cannot return a good match in the first fewlistings. This behavior requires that the best match be returned asclose to the top of the list as possible.
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.
4. Agonizing over the querySometimes users have difficulty translating the concept they want tofind into a specific search phrase. They will often rewrite the queryseveral times before submitting it, and then focus on revising itfurther if the results are not as they had expected them to be.Less experienced users like Kazue are more likely to show thisbehavior, especially if the task isn’t well defined and liesconceptually outside of her domain. Kazue may also be inclined tophrase the query generally enough to satisfy her global cognitivestyle, but fret over how general is too general.
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.
5. Pogo stickingSome users click several results in rapid succession, quicklysampling each before settling on a best candidate to meet theirneeds. Jared Spool has described this as ―pogo sticking‖—bouncingup and down between choices of uncertain relative value. This is thekind of behavior that Dmitry might resort to if the quick surveyingbehavior described for him above didn’t yield anything. Assumingthat his temperament is fairly tolerant and he isn’t pressed for time,Dmitry may decide that he cannot determine the usefulness of pageswithout looking at them. These users need support for three primarytasks: assessing result listings, comparing result pages, and trackingwork.
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.
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.
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‖