A Brief History of Web Performance

Soon after the birth of the web, HCI researchers started studying online environments. Networked environments like the Internet add another dimension to the mixnamely, network latency. Unlike the closed computing environments that HCI researchers studied in the past, on the Internet the delay between requesting a resource and receiving it is unpredictable. The more resources a page has (graphics, multimedia), the less predictable the response rate.

Initially researchers studied the effects of fixed response times on user satisfaction. Later studies simulated variable response rates for more real-world results. Their metrics changed from user satisfaction and performance to measures such as attunability , quality of service, quality of experience, and credibility.

In the late 1990s and early 2000s, researchers started looking at Shackel's likability dimension by studying the effects of download delays on user perceptions of web sites, flow states, ^[9] and emotional appeal .

^[9] Donna L. Hoffman and Thomas P. Novak, "Marketing in Hypermedia Computer-Mediated Environments: Conceptual Foundations," Journal of Marketing 60 (July 1996): 5068.

Users form negative impressions from web site delays. Users perceive fast-loading pages to be of high quality, while they perceive slow-loading pages to be of low quality and untrustworthy. A user's tolerance for delay also decreases with experience. These topics are covered in more depth later in this chapter.

In fact, slow-loading web pages can cause users to believe that an error has occurred, because the computer has not responded in an appropriate amount of time. ^[10]

^[10] Jonathan Lazar and Yan Huang, "Designing Improved Error Messages for Web Browsers," in Human Factors and Web Development , 2d edition, ed. Julie Ratner (Mahwah, NJ: Lawrence Erlbaum Associates, 2002).

Affective Computing

Some researchers theorize that if a computer could respond "supportively" to delay-induced frustration, any negative emotional effects could be mitigated. According to researchers who have studied "affective computing," computers can respond to human emotions in order to lower frustration levels. ^[12]

^[12] Rosalind W. Picard, Affective Computing (Cambridge, MA: MIT Press, 1997).

Pre-Attentive Recognition

In their classic book on the psychology of human performance, Wickens and Hollands describe parallel processing in visual searching, or pre-attentive recognition. ^[11] We can recognize features much more quickly on the screen using color or grouping than we can locate a word in a body of text. That's why links default to blue; this helps us locate them immediately.

^[11] Christopher D. Wickens and Justin G. Hollands, Engineering Psychology and Human Performance , 3d ed. (Upper Saddle River, NJ: Prentice Hall, 1999), 8489.

Using galvanic skin response and blood volume pressure, Scheirer found that random delays can be a cause of frustration with computers. ^[13] Rather than ignoring their frustration (the most common condition) or letting them vent, a supportive approach gave users the most relief from frustration. ^[14] Perhaps we'll soon hear something like: "I'm sorry I'm so slow, Dave. Would you like me to speed up this web site?"

^[13] Jocelyn Scheirer, Raul Fernandez, Jonathan Klein, and Rosalind W. Picard, "Frustrating the User on Purpose: A Step Toward Building an Affective Computer," Interacting with Computers 14, no. 2 (2002): 93118.

^[14] Jonathan Klein, Youngme Moon, and Rosalind W. Picard, "This Computer Responds to User Frustration: Theory, Design, and Results," Interacting with Computers 14, no. 2 (2002): 119140.

User-Rated Quality Models

More recently, researchers have been attempting to create a grand unified theory of web site quality from a user's perspective. How do users rate web sites? Why do they return to particular web sites and buy products? WebQual, an overall measure of web site quality, is composed of twelve distinct measures derived from existing research.

WebQual can accurately assess the overall perceived quality of web sites. Response time and emotional appeal both play a major role in perceived web site quality. ^[15]

^[15] Eleanor T. Loiacono, Richard T. Watson, and Dale L. Goodhue, "WebQual: A Web Site Quality Instrument," American Marketing Association: Winter Marketing Educators' Conference 13 (Austin, Texas: American Marketing Association, 2002): 432438. A 12-factor web quality super-model from a user's perspective. See also http://www.webqual.net/.

Automated Quality Testing

WebTango researchers have developed an automated web site quality rating tool. ^[16] Their system, which is empirically based, automatically measures web site structure and composition in order to predict how experts will rate sites. Based on web designs judged by experts (Webby Awards), their 157-factor model, which includes page performance, had an average accuracy of 94 percent when quantifying good, average, and poor pages. However, some of the measures of good design are counterintuitive (i.e., more Bobby accessibility errors, see http://bobby.watchfire.com/).

^[16] Melody Y. Ivory and Marti A. Hearst, "Improving Web Site Design," IEEE Internet Computing, Special Issue on Usability and the World Wide Web 6, no. 2 (2002): 5663. Available from the Internet at http://webtango.ischool.washington.edu/.

Essentially a mining tool, WebTango analyzes existing web pages to create profiles of good and bad designs, and then applies this data to the design of new sites. This interactive "quality checker" is analogous to a grammar checker for web sites (see Figure 1.2).

Figure 1.2. Web site structure: From information to experience design.

Set Performance Goals

Usability professionals routinely set usability metrics and goals for particular systems. Web performance is no different. Choose a performance goal for your site, and strive to achieve that goal for all of your pages. Because usability guidelines can be subjective , Shackel suggests quantifying usability in measurable terms. ^[17] Here is an example of a performance goal checklist:

• Effectiveness Display high-traffic pages faster than eight seconds on 56Kbps modems; display useful content within the first two seconds. Other pages should display useful content in no more than 12 seconds on 56Kbps modems.

• Learnability Achieve a 90 percent success rate on finding particular products within 30 seconds.

• Flexibility Give users the ability to find products by browsing or searching.

• Attitude With an attitude questionnaire on a 5-point scale from "very good" to "very bad," score 80 percent in good or above and only 2 percent below neutral.

• Overall usability Meet 75 percent or more of Nielsen's 207-point usability checklist. ^[18]

^[17] Shackel, "Usabilitycontext, framework, definition, design, and evaluation," 27.

^[18] Jakob Nielsen, Rolf Molich, Carolyn Snyder, and Susan Farrell, E-Commerce User Experience (Fremont, CA: Nielsen Norman Group , 2001). This invaluable book revealed the mythical 207 usability design guidelines.