Section 10.5. Users


10.5. Users

They're called users, respondents, visitors, actors, employees, customers, and more. They're counted as clicks, impressions, advertising revenues, and sales. Whatever you call them and however you count them, they are the ultimate designers of the Web. Build a web site that confuses customers, and they'll go elsewhere. Build an intranet that frustrates employees, and they won't use it.

This is the Internet's fast-forward brand of evolution. Remember the original Pathfinder web site from Time Warner? They spent millions of dollars on a flashy, graphical extravaganza. Users hated it. A complete redesign followed months after the original launch. This was an expensive and embarrassingly public lesson in the importance of user-sensitive design.

So, we've established that users are powerful. They're also complex and unpredictable. You can't blindly apply lessons learned by Amazon to the information architecture design of Pfizer.com. You've got to consider the unique nature of the site and of the user population.

There are many ways to study user populations.[] Market-research firms run focus groups to study branding preferences. Political pollsters use telephone surveys to gauge the publics feelings about candidates and issues. Usability firms conduct interviews to determine which icons and color schemes are most effective. Anthropologists observe people acting and interacting within their native environments to learn about their culture, behavior, and beliefs.

[] If youd like to dig deeper, we recommend reading User and Task Analysis for Interface Design by Joann Hackos and Janice Redish (Wiley). And then, of course, there are all sorts of wonderful articles and books by usability guru Jakob Nielsen (http://useit.com).

No single approach can stand alone as the one right way to learn about users and their needs, priorities, mental models, and information-seeking behavior. This is a multidimensional puzzleyou've got to look at it from many different perspectives to get a good sense of the whole. It's much better to conduct five interviews and five usability tests than to run one test ten times. Each approach is subject to the law of diminishing returns.

As you consider integrating these user research methods into your design process, keep a couple of things in mind. First, observe the golden rule of discount usability engineering: any testing is better than no testing. Don't let budgets or schedules become an excuse. Second, remember that users can be your most powerful allies. It's easy for your colleagues and your boss to argue with you, but it's difficult for them to argue with their customers and with real user behavior. User research is an extremely effective political tool.

10.5.1. Usage Statistics

Most projects today involve redesigning an existing site. In these cases, it makes sense to begin by looking at data that shows how people have been using the site and where they've been running into problems.

Your site's usage statistics are a reasonable place to start. Most statistics software packages, such as Google Analytics shown in Figure 10-5, provide the following reports:


Page information

The number of hits per day for each page in the site. This data will show which pages are most popular. By tracking page hits over time, you can observe trends and tie page popularity to events such as advertising campaigns or the redesign of site navigation.


Visitor information

Statistics products claim they can tell you who is using your site and where the users are coming from. In reality, they'll tell you only the domains (e.g., aol.com, mitre.org) of those users' Internet service providers, which is often of limited value.

Your stats software may provide additional views into the usage data, indicating the times and dates when people are visiting, the referring sites your users are coming from, and the types of browsers being used, as shown in Figure 10-5.

Figure 10-5. Usage data presented by Google Analytics


The path that users trace as they move through a web site is known as the clickstream. If you want a higher level of sophistication in your usage statistics, you can buy software that handles clickstream analysis. You can trace where a user comes from (originating site), the path he takes through your site, and where he goes next (destination site). Along the way, you can learn how long he spends on each page of your site. This creates a tremendously rich data stream that can be fascinating to review, but difficult to act upon. What you really need to make clickstream data valuable is feedback from the user explaining why he came to the site, what he found, and why he left. Some companies use pop-up surveys to capture this information as users are leaving the web site.

10.5.2. Search-Log Analysis

A simpler and extremely valuable approach involves the tracking and analysis of queries entered into the search engine. By studying these queries, you can identify what users are looking for, and the words and phrases they are using. This is fantastic data when you're developing controlled vocabularies. It's also useful when prioritizing terms for a "Best Bets" strategy. (You'll learn more about Best Bets in the MSWeb case study in Chapter 20.)

At a basic level, search-log analysis will sensitize you to the way your users really search. Users generally enter one or two keywords, and you're lucky if they spell them right. Looking at search logs provides a valuable education for information architects who are fresh out of school and all steamed up about the power of Boolean operators and parenthetical nesting. You can achieve the same effect using a live search display[] such as Metacrawlers metaspy, which shows the terms that real people are using to search right now (see Figure 10-6).

[] See http://searchenginewatch.com/facts/searches.html for more on live search displays.

Figure 10-6. A public search voyeur service


But with your own site's search logs, you can learn much more. At a bare minimum, you should be able to get a monthly report that shows how many times users searched on particular terms during that month, as shown here:

54 e-victor 53 keywords:"e-victor" 41 travel 41 keywords:"travel" 37 keywords:"jupiter" 37 jupiter31 esp 30 keywords:"esp" 28 keywords:"evictor" 28 evictor 28 keywords:"people finder" 28 people finder 27 fleet 27 keywords:"fleet" 27 payroll 26 eer 26 keywords:"eer" 26 keywords:"payroll" 26 digital badge 25 keywords:"digital badge"

But hopefully, you can work with your IT group to buy or build a more sophisticated query-analysis tool that allows you to filter by date, time, and IP address. Figure 10-7 shows a good example of such a tool. This tool can help you answer the following questions:

  • Which popular queries are retrieving zero results?

  • Are these zero-hit users entering the wrong keywords, or are they looking for stuff that doesn't exist on your site?

  • Which popular queries are retrieving hundreds of results?

  • What are these hundred-hit users actually looking for?

  • Which queries are becoming more popular? Less?

Based on the answers, you can take immediate and concrete steps to fix problems and improve information retrieval. You might add preferred and variant terms to your controlled vocabulary, change navigation labels on major pages throughout the site, improve search tips, or edit content on the site. Note that smart marketing groups are also getting interested in search logs as a valuable source of information about customer needs.

Figure 10-7. A query-analysis tool


10.5.3. Customer-Support Data

In addition to reviewing web site statistics, it's worth looking to the customer- or technical-support departments to see if they've been capturing and analyzing the problems, questions, and feedback from the customers of your web site or intranet. Help-desk operators, call-center representatives, librarians, and administrative assistants can also be rich sources of information; in many large corporations, these are the people to whom customers or employees turn for answers. That means they are the people who know the questions.




Information Architecture for the World Wide Web
Information Architecture for the World Wide Web: Designing Large-Scale Web Sites
ISBN: 0596527349
EAN: 2147483647
Year: 2006
Pages: 194

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