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Editor's Notes
Welcome to Usability News. You may notice that this issue has fewer articles than previous issues. This is because we have decided to publish quarterly rather than twice a year. Look for our next issue in October 2007.
In our 17th issue:
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The Effect of Website Typeface Appropriateness on the
Perception of a Company’s Ethos
Summary. This study investigated the effect of website typeface appropriateness on the perception of the site’s company. Results indicate that typefaces that are high in appropriateness should be used for websites. Neutral and low appropriate typefaces significantly decreased the perception of the company as judged by professionalism, believability, trust, and intent to act on the site.
INTRODUCTION
Type has many important functions in the decoding process. Type should set the mood of a document, reveal the document’s structure, guide readers in navigation, hint at the document’s genre, indicate information about the author’s ethos, and reveal areas of importance (Mackiewicz, 2004; Mackiewicz & Moeller, 2004; Schriver, 1997). Taking into account the diverse roles of typography, Bartram (1982) and Zachrisson (1965) specify two roles for type: a functional role (relating to legibility) and an aesthetic/semantic role, which impacts the “apparent ‘fitness’ or 'suitability’ for different functions, and which imbue it with the power to evoke in the perceiver certain emotional and cognitive response” (p. 38).
Documents inherently
contain both visual and verbal rhetoric. The verbal rhetoric of the document
refers to the actual textual information; verbal rhetoric affects the
ability of the reader to understand the content of the document. On the
other hand, the visual rhetoric pertains to the visual elements of the
document and affects the reader’s initial impression of the document (Brumberger,
2001; Kostelnick & Hassett, 2003; Mackiewicz, 2004). Visual elements can
“activate their own semantic representations” (Childers & Jass, 2002, p. 94)
meaning they can take on their own linguistic meaning separate from that of
the content. According to the renowned typographer, Matthew Carter, letters
on a page should “provide a seamless passage of the author’s thoughts into
the reader’s mind with as much sympathy, style, and congeniality as
possible” (as cited by Boser, 2003, p. 44). The visual rhetoric can also
affect the tone and ethos of a document (Kostelnick and Roberts, 1998).
Ethos refers to a document’s or author’s voice and credibility and is used
to establish trust in the relationship with the reader. Designers are
encouraged to match the typeface to the content to improve ethos (Kostelnick
& Roberts, 1998).
Brumberger (2001) found that typeface had no effect on the perception of the
document in terms of ethos. Shaikh, Fox, & Chaparro (2007) found varying
results regarding the ethos of a variety of onscreen documents. In spite of
limited empirical evidence to support the idea that typeface appropriateness
could affect the perception of the author’s ethos, many typographers and
designers posit this idea. With this in mind, this study attempted to
provide empirical support of the notion that appropriate typeface selections
lead to a better impression of onscreen documents and the author’s ethos.
TYPEFACE APPROPRIATENESS OVERVIEW
Typeface appropriateness was determined in a research study by the author using a paired comparison method as described by Thurstone’s Law of Comparative Judgment (Thurstone, 1927a; Thurstone, 1927b). Based on the law, each typeface evaluated possesses a level of appropriateness for the document being evaluated. Participants were randomly presented two samples of an e-commerce website. The sample website was modeled after an online bookstore, but used nonsense text based on a third order approximation to English (as shown in Figure 1) to remove any effect of context. A small portion of an entire web page was presented but participants were asked to focus on the zoomed portion of the text. The text in the zoomed portion had an x-height of 10 to 11 pixels. Instructions asked the participants to click on the website sample with the typeface they viewed as most appropriate. Eleven typefaces were evaluated resulting in a total of 55 comparisons. Based on the average proportion of times the typeface was chosen as most appropriate, the typefaces were ordered along a continuum to represent the degree of appropriateness each represents for an e-commerce website. Figure 2 shows the proportional results of the paired comparisons for perceived typeface appropriateness for websites.
Figure 1. Sample of the web page used when determining typeface appropriateness. The same image was presented in two typefaces at a time and participants were asked to click on the one with the most appropriate typeface.
Figure 2. The average proportion of times a typeface was chosen as the most appropriate typeface when being compared to one other typeface. Calibri was perceived as the most appropriate with Cambria, Arial, Calisto, and Georgia scoring high as well. Curlz was perceived as the least appropriate.
EFFECT OF TYPEFACE APPROPRIATENESS ON ETHOS
After determining the perceived appropriateness of various typefaces for websites, an additional study was conducted to determine the effect of appropriateness on the perception of the company’s ethos. Ethos is defined by http://www.dictionary.com/ as “the disposition, character, or fundamental values peculiar to a specific person, people, culture, or movement.” The term is commonly used in communications to describe the believability or credibility of the creator of a message.
METHOD
Materials
After determining the relative appropriateness of the 11 typefaces, three were chosen to represent a high, neutral, and low level of appropriateness. Calibri (high), Courier New (neutral), and Curlz (low) were used to construct actual web pages based on the sample used in determining the typeface appropriateness. A book entitled Clear and Simple Thesaurus Dictionary was featured on the website page. The image and the description were taken from http://www.barnesandnoble.com/; the reviews were taken from http://www.amazon.com/ for this book. Menu categories were chosen from various categories on common bookstore websites including those already mentioned and http://www.borders.com/. The images were created in Macromedia/Adobe Fireworks and Microsoft Word XP. The sample website page, which was modeled after http://www.strandbooks.com/ utilized subtle colors and standard clip art available in Microsoft Word XP. For the non-essential text (i.e., header information), the typeface Franklin Gothic Demi was used. The final size of the website page image as viewed by participants was approximately 580 x 300 pixels. An online program was constructed using PHP and mySQL to run the study. Figure 3 provides examples of the final web pages used for this portion of the study.
Figure 3. Samples of the e-commerce websites used to determine the perception of company ethos. Typefaces used include Calibri (top; high in appropriateness), Courier New (middle; neutral in appropriateness), and Curlz (bottom; low in appropriateness).
Procedure
One hundred fifteen participants completed a demographics questionnaire which included a series of questions designed to assess their familiarity and experience with six documents being tested (only website text is discussed in this article). Based on the answers to these questions, participants only saw documents with which they were familiar. Participants viewed the web pages and answered a series of questions assessing their perceived ethos of the company being represented in the web pages. This included questions about the company’s professionalism, believability, and trustworthiness. The questions were measured on a 7-point scale (-3 to +3). In addition to assessing the ethos of the authors, an “intent to act” question was assessed for the website text (“If you were shopping for a new book, how likely would you be to use this website?”). Participants were also asked to indicate the gender of the document’s author or the gender of the intended audience.
RESULTS
The ethos/intent to act questions based on the 7-point scale were investigated using a series of one-way between-subjects ANOVAs. The independent variable being investigated was typeface appropriateness as represented by three typefaces with three levels (high, neutral, and low appropriateness). The dependent variable for the ethos portion was the score on each question on a scale of -3 to +3. In order to control for familywise error, an alpha level was set at α=.021 based on recommendations from Tabachnick and Fidell (2001). Post hoc tests for all ANOVAs were carried out using Tukey HSD pairwise comparisons. Chi-square (χ²) analyses were run to determine the relationship between the typefaces and perceived gender of the author/intended audience and one additional question for the assignment.
Evaluations of typeface appropriateness resulted in a significant difference in the perception of the sponsoring company’s professionalism (F (2, 113) = 57.75, p < .001, partial η² = .50). Post hoc analyses (using Tukey HSD) revealed that the company utilizing the appropriate typeface was perceived as significantly more professional than the companies who used the neutral and inappropriate typefaces. The company using the inappropriate typeface was viewed as significantly less professional than the company represented in both of the other sites (Figure 4).
The believability of the information was also significantly affected by the typeface appropriateness (F (2, 113) = 34.87, p < .001, partial η² = .38). Again, the site using the appropriate typeface (Calibri) was judged to be significantly more believable than the other two sites as shown in Figure 5. Additionally, the site using the inappropriate typeface was viewed as significantly less believable than the other sites.
Similarly, the perception of trustworthiness of the company was also significantly affected by typeface appropriateness (F (2, 112) = 30.26, p < .001, partial η² = .35). The site in the appropriate typeface, as shown in Figure 6, was rated as significantly more trustworthy while the site in the inappropriate typeface was seen as significantly less trustworthy.
As shown in Figure 7, the intent of the participant (“If you were shopping for a new book, how likely would you be to use this website?”) was significantly affected by typeface appropriateness (F (2, 112) = 47.51, p < .001, partial η² = .46). Post hoc analyses revealed that participants were significantly more likely to use the site when it was presented in the appropriate typeface. Participants were also significantly less likely to use the site offered in the inappropriate typeface.
The final question of the ethos section asked
participants to indicate the gender of the intended audience of the ad. The
data for this question failed to meet the assumptions of the k-related
samples χ² test (> 20% of the cells had expected frequencies of less than 5
and one cell had a value of 0). Overall, participants could not tell what
gender the intended audience was for the sites offered in Calibri and
Courier New; however, on the site created with Curlz, participants (73%)
tended to think it was for females.
Figure 4. Perception of the professionalism of the company represented on the website based on typeface appropriateness. The company using the appropriate typeface was perceived as significantly more professional than the companies using the neutral or inappropriate typefaces. The company using the inappropriate typeface was seen as significantly less professional the other two companies.
Figure 5. Perception of the believability of the company represented on the website based on typeface appropriateness. The site with the appropriate typeface was more believable than the other two sites. The site using the inappropriate typeface was scored as significantly less believable than the other two sites.
Figure 6. Perception of the trustworthiness of the company represented on the website based on typeface appropriateness. The company using the appropriate typeface was rated as significantly more trustworthy, and the company using the inappropriate typeface was significantly less trustworthy than the other two sites.
Figure 7. Likelihood of participants to use the website based on typeface appropriateness. The participants were significantly more likely to use the site with the appropriate typeface than the other two sites. They were significantly less likely to use the site with the inappropriate typeface.
DISCUSSION
The web page presented in either a neutral or inappropriate typeface resulted in a decreased perception of the company being represented. Courier New, the neutral typeface, was perceived as comparable to the inappropriate typeface (Curlz) in terms of perception of the company represented in the website. Additionally, participants were more likely to act on the document when the typeface was appropriate. This finding indicates that in addition to creating a more positive ethos, the appropriate typeface might translate to higher returns for companies (more hits on the website). The results of this study indicate that there is a small selection of typefaces that are seen as appropriate. Even a typeface that is perceived as neutral in appropriateness results in decreased trust, professionalism, and believability. Companies should carefully choose typefaces that are judged as highly appropriate for their online presence.
*Note: This article presents only a small portion of findings from a comprehensive study investigating the perceptions of typeface personality by Dawn Shaikh. Please contact Dr. Shaikh for more information.
REFERENCES
Bartram, D. (1982). The perception of semantic quality in type: Differences between designers and non-designers. Information Design Journal, 3, 38-50.
Boser, U. (2003, September 1). A man of letters. U.S. News & World Report, 135, 44-46.
Brumberger, E. R. (2001). The rhetoric of typography: Five experimental studies of typeface personality and its effects on readers and reading. Unpublished Dissertation, New Mexico State University, Las Cruces, NM.
Childers, T. L., & Jass, J. (2002). All dressed up with something to say: Effects of typeface semantic associations on brand perception and consumer memory. Journal of Consumer Psychology, 12(2), 93-106.
Kostelnick, C., & Hassett, M. (2003). Shaping information: The rhetoric of visual conventions. Carbondale, IL: Southern Illinois University Press.
Kostelnick, C., & Roberts, D. D. (1998). Designing visual language: Strategies for professional communicators. Boston: Allyn and Bacon.
Mackiewicz, J. (2004). What technical writing students should know about typeface personality. Journal of Technical Writing and Communication, 34, 113-131.
Mackiewicz, J., & Moeller, R. (2004). Why people perceive typefaces to have different personalities. Paper presented at the International Professional Communication Conference, Minneapolis, MN.
Schriver, K. A. (1997). Dynamics in document design. New York: John Wiley & Sons, Inc.
Shaikh, A. D., Fox, D., & Chaparro, B. S. (2007). The effect of typeface on the perception of email. Retrieved February 15, 2007, from http://psychology.wichita.edu/surl/usabilitynews/91/POF.html
Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Boston: Allyn and Bacon.
Thurstone, L. L. (1927a). A law of comparative judgment. Psychological Review, 34, 273-286.
Thurstone, L. L. (1927b). The method of paired comparisons for social values. Journal of Abnormal and Social Psychology, 21(384-400).
Zachrisson, B. (1965). Studies in the legibility of printed text. Stockholm: Almqvist & Wiksell.
Examining Legibility of the Letter “e” and Number “0” Using Classification Tree Analysis
Summary. This study investigated the legibility of onscreen typefaces and the influence of individual character features on correct identification. Specific attributes of alphanumeric characters and symbols shown to be the least legible were measured and analyzed using a statistical method called classification tree analysis. Results from this analysis for the letter “e” and the number zero are discussed.
INTRODUCTION
Typeface legibility is becoming an important issue as reading shifts from print to onscreen (Shaikh & Chaparro, 2004). The common forms of print reading such as newspapers, books, magazines, etc. are being replaced with websites, electronic books, and ezines. This shift of reading methods has resulted in an increased demand for optimized legibility. Lupton (2004) noted “the rise of the Internet as well as cell phones, hand-held video games, and PDAs have insured the continued relevance of pixel-based fonts as more and more information is designed for publication directly onscreen” (p. 27).
There have been many studies that have focused on the legibility of print (Jha & Daftuar, 1981; Mansfield, Legge, & Bane, 1996; Roethlein, 1912; Sanocki, 1988; Woods, Davis, Scharff, 2005) which have resulted in recommendations for different types of printed material. Unfortunately there has not been much research investigating onscreen legibility. Chaparro, Shaikh, and Chaparro (2006) studied the onscreen legibility of six ClearType™ typefaces, developed by Microsoft, which take advantage of sub-pixel rendering. This study found that two of these typefaces (Cambria and Constantia) were more legible than the popular Times New Roman.
Some suggestions have been made as to what specific features of a typeface contribute to the legibility of the characters themselves. Each character is made up of certain attributes (see Figure 1) that distinguish it from other characters within the same typeface and from the same character in other typefaces. These differences are often very subtle but contribute to the overall theme of the typeface. Few empirical studies have been done to determine how these features influence legibility.
Figure 1. Features that are used for the design of characters (http://gmunch.home.pipeline.com/typo-L/faq/anat.htm).
Tinker (1928) suggested that the size, simplicity of outline, serif style, shading, area of whitespace, and delineation of distinguishing characteristics influence the legibility of lowercase characters. Benjamin Bauemeister developed a program called PANOSE as a guide to measuring typeface attributes including family type, serif style, weight, proportion, contrast, stroke variation, arm style, letterform, midline, and x-height (http://www.panose.com/ProductsServices/pan2.aspx).
Pelli, Burns, Farell, & Moore-Page (2006) state that we have commonly based letter identity on visual detection of independent features. However, Pelli et al. (2006) argue that it is much more than just feature detection and the notion of complexity is what actually predicts whether a letter is legible or not. Complexity is measured as a character's inside-and-outside perimeter which is then squared and divided by the “ink” area. For stroke characters complexity is measured by taking four times the length of the stroke divided by the width of the stroke. Pelli et al. (2006) chose complexity as a measure because “it tends to capture how convoluted a character is, and is easily computed, independent of size” (p. 4648).
The purpose of this study was to determine what features of alphanumeric characters and symbols contribute to their onscreen legibility. First, legibility was measured for 47 characters from 20 different typefaces using a classification technique. Participants were asked to identify each character after a very brief exposure time. From this, confusion matrices were created to identify those characters with the poorest legibility. Then, features were measured for each of these characters (see Table 1) and their influence on legibility was analyzed using a statistical method called classification tree analysis.
This article reviews the results of this analysis for two characters, the letter “e” and number zero. The character “e” is commonly confused for other characters such as the letter “c” or “o” (Roethlein, 1912). The zero is one of the most commonly confused numerical characters due to its resemblance to the letter “o”. However, there are some typefaces where these characters are confused more than others. Thus, it is important to consider what features of these two characters contribute most to their legibility.
Table 1. Features used in the study and their definitions.
|
Feature |
Definition |
|
|
area |
Character width multiplied by character height; represents the total space occupied by a single character. |
|
|
complexity |
Inside-and-outside perimeter2 divided by "ink" area; for stroked characters it is roughly four times the length of the stroke divided by the width of the stroke or four times the aspect ratio of the untangled stroke. |
|
|
contrast |
Ratio between the thickest point on the stroke and the narrowest point the narrowest stroke weight divided by the widest stroke weight |
|
|
height |
Vertical space covered by a character; measured from the top to bottom of a character including ascenders and descenders. |
|
|
midline* |
Ratio of the height of the baseline to the center horizontal of the character to the overall height of the character |
|
|
perimeter |
This measures the length of the boundary between black and white (the ‘perimeter’). Perimeter squared divided by black area is complexity.
|
|
|
stroke variation |
A more detailed measurement of contrast that by describing the kind of transition that occurs as the stem thickness changes on rounded glyph shapes. |
|
|
weight |
Letter height over the stem thickness taken from a stem at the letter's midpoint. Weight in general is the darkness (blackness) of a typeface, independent of its size (Bringhurst, 1992). |
|
|
width |
Horizontal space covered by a character; measured from outside pixels on both sides of the character and includes both the strokes and the whitespace. |
|
*this measure only pertained to the “e”
METHOD
Participants
Ten participants (6 male, 4 female) between the ages of 18-25 volunteered for this study. All participants had at least 20/20 vision. All were compensated $50 for their participation.
Materials
A Dell Core 2 Duo laptop with a TrueLife™ display and ClearType™ font rendering was used. The screen resolution was set to 1920 x 1080 with a 60 Hz and 147 dpi. A program was written in C# to display the character in 10-point font size, and the laptop was positioned at a distance so that the characters, regardless of typeface, were viewed at a visual angle of .08°. Participants used a chinrest to stabilize their head and maintain a constant distance from the monitor. The 20 typefaces investigated are shown in Table 2.
Table 2. The 20 typefaces examined in this study.
Procedure
Twenty-six lowercase letters were used in combination with the digits 0-9 and 11 symbols frequently found in mathematical or scientific documents. Tinker's (1928) study on the relative legibility of letter, numbers, and symbols provided guidance in character selection. The symbols used included: ÷ = + ? % ± $ # @ & !. The chosen symbols had a character height similar to the lowercase letters.
Participants were shown a sample of what the characters looked like before each trial started. Each trial started with a “•” to indicate where the characters were going to appear on the monitor and ended with a “•” to indicate that the trial was over. Each participant participated in four trials for each typeface with the first trial being excluded from data collection as practice. Each trial consisted of all 47 characters being exposed briefly (34 ms) one at a time with a blanking time of 1.5 second between each exposure. The order the characters and the typefaces was randomized. Characters were displayed in black type on a white background. Character identification was read aloud by the participants and accuracy was recorded by the experimenter.
RESULTS
Percent correct for each character in each typeface was calculated for all characters; however, only the results for the letter “e” and zero are discussed here (see Table 3 and Table 4). For the letter “e”, participants performed the worst with the Garamond typeface with only 10% of the “e” presentations correctly identified. Performance was the best with Clearview Text and Verdana, where the letter “e” was correctly identified 100% of the time. The mean percentage correct across all 20 typefaces for the letter “e” was 87.68% (SD=6.96). For the number zero, participants performed the worst with Constantia (6.7% correct identification) and the best with Centaur and Rockwell (both 100% correct identification). The overall mean percentage correct for the number zero across all 20 typefaces was 69.84% (SD=32.36).
Table 3. Percentage of correct identifications for the character “e”.
Table 4. Percentage of correct identifications for the zero.
Classification tree analysis was used in this study to determine which features (IVs) of the characters were the most influential in correct identification. Classification tree analysis is a nonparametric statistical procedure that identifies homogenous subgroups (nodes) to accurately predict a dependent variable (DV) chosen by the researcher. The subgroups created share common characteristics that influence the DV. A unique visual structure (see Figure 2) that links the nodes together is the result of the classification tree analysis. The branching that is made is based on the analysis of all the independent variables (IVs). The IV that creates the most differentiating groups is selected as the branch IV. This procedure is repeated creating more nodes until there are no other IVs that influence the DV. (Lemon, Roy, Clark, Friedmann, & Rakowski, 2003)
In this study, the DV measure was the number of misclassifications; thus, the more times a character was misclassified the less legible it was. The classification tree analyzed all of the features (area, complexity, contrast, height, midline, perimeter, stroke variation, weight, and width) to determine which feature contributed the most to a misclassification.
Figure 2. Example of classification tree (Lemon et al., 2003).
The Letter “e”
The results of the classification tree analysis for character “e” (see Figure 3) suggest that the midline is the feature that influences misclassification the most. Typefaces with a ratio midline value greater than or equal to .54 pixels represent the trials that were more likely to be confused or skipped; conversely, the typefaces that had a ratio midline value of less than .54 pixels represents the trials that were less likely to be confused or skipped. The numbers within the nodes represent the number of incorrect trials and number of correct trials, so for midline values greater than or equal to .54 pixels, there were 49 incorrect trials and 101 correct trials (67% correct identification rate), compared to midline values of less than .54 pixels which contained 25 incorrect trials and 425 correct trials (94% correct identification rate). Figure 4 shows the midline of the worst (Garamond) and best (Verdana) letter “e”. The classification tree analysis did not identify any other feature that influenced misclassification.
Figure 3. Classification tree for the “e”.
Figure 4. The Garamond “e” (left) has a much higher midline ratio since the bottom of the eye is higher than that of the Verdana “e” (right). Classification tree results suggest that “e” characters with a higher midline ratio were confused more.
The Number Zero
The classification tree results for the number zero are a little more complex and contain more nodes (see Figure 5). The primary branch was for height, suggesting that the height of the zero was the most influential feature out of all the IVs. The zeros with heights equal to or greater than 11.5 showed a better classification ratio of only 45 misclassifications to 375 correct identifications (89% correct identification rate) while the typeface zeros with heights less than 11.5 had a ratio of 136 misclassifications to 44 correct identifications (24% identification rate) (see Figure 6).
When the height was greater than or equal to 11.5 pixels then weight was the next most influential feature. When weight was greater than or equal to 2.82 there was a higher correct identification rate of 24 misclassifications to 336 correct identifications (93% correct identification rate) while a weight less than 2.82 had 21 misclassifications to 39 correct identifications (65% correct identification rate).
When the height was less than 11.5 pixels then the perimeter was the next most influential feature. When perimeter was greater than or equal to 179 there was a higher ratio of correct identifications with 4 misclassifications to 26 correct identifications (87% correct identification rate). If the perimeter was less than 179 there was a ratio of 132 misclassifications to 18 correct identifications (12% correct identification rate). There were no other influential features for the zero according to the classification tree results.
Figure 5. Classification tree for the zero.
Figure 6. The Constantia zero (left) has a height that is below 11.5 pixels while Rockwell zero (right) has a height above 11.5 pixels.
DISCUSSION
Results from the classification tree analysis show that the midline was an important feature for the legibility of the character "e". The “e” characters that had a ratio midline of .54 or greater were less legible than those with a ratio midline less than .54. This is supported further by the rank order of percentage correct identifications (see Table 5). Midline is the ratio of the height of the baseline to the center horizontal of the character to the overall height of the character (see Figure 4). The measure of the center horizontal to baseline is affected by the bottom part of the eye of the “e”; the higher the bottom line of the eye is, the greater the midline ratio. Notice that the Garamond (least legible) “e” bottom line of the eye is much higher than that of Verdana (most legible) “e”.
Table 5. Rank order of the “e” based on percentage correct. The typefaces above .54 tended to be the least legible.
For the character zero, height was found to be the most influential feature for correct identification. A zero that had a height equal to or greater than 11.5 pixels was more likely to be identified correctly than a zero with a height less than 11.5 pixels (see Table 6). The shorter zeros (commonly associated with old style numerals) were more likely to be confused with the letter “o”. While not surprising, the classification tree analysis provides designers with a specific cutoff of how much height is necessary to improve legibility.
Table 6. Rank order of the zero based on percentage correct. Each typeface above the bold line were the least legible and had a height measure of less than 11.5 pixels.
In addition to height, the classification tree analysis showed that the weight of the zero also influenced the legibility of the taller zeros. For zero heights greater than 11.5 pixels, weight values greater than or equal to 2.82 resulted in better legibility (see Table 7). This implies that the darker the stroke of the zero, the better it was identified.
Table 7. Rank order of the zero based on percentage correct. Each typeface above the bold line were the least legible and had a weight measure of less than 2.82.
For the shorter zeros (less than 11.5 pixels) the classification tree analysis identified the perimeter to influence legibility. Perimeter values greater than or equal to 179 resulted in better legibility (see Table 8). This was interesting because the perimeter is one of the measures that Pelli et al. (2006) suggests is influential to legibility. (It should be noted that the exceptions to this rule, Centaur and Garamond, were characters with a height > 11.5 pixels.)
Table 8. Rank order of the zero based on percentage correct. Each typeface above the bold line were the least legible and had a perimeter measure of less than 179.
The use of classification tree analysis appears to be a promising method of determining which features of a character influence legibility. In addition, these results can be used for creating recommendations on specific design elements. While this article only addressed the results for the letter "e" and the number zero, this technique can be used to analyze any character which tends to be easily confused. Optimizing the legibility of individual characters is not only important for general onscreen reading but also for settings in which users must identify codes or single characters to complete a task; such as an air traffic controller reading symbols on a display.
Acknowledgment: The authors would like to thank Kevin Larson, Ph.D., for his comments on this article. This study was funded by a grant from the Advanced Reading Technology team at Microsoft Corporation.
REFERENCES
Bringhurst, R. (1992). The elements of typographical style. Vancouver: Hartley & Marks, Publishers.
Chaparro, B. S., Shaikh, A. D., & Chaparro, A. (2006).
The legibility of two new ClearType fonts. Usability News, 8(1). Retrieved
June 30, 2007, from
http://psychology.wichita.edu/surl/usabilitynews/81/legibility.htm
Jha, S. S. & Daftuar, C. N. (1981). Legibility of type faces. Journal of Psychological Researchers, 25(2), 108-110.
Lemon, S. C., Roy, J., Clark, M. A., Friedmann, P. D., & Rakowski, W. (2003). Classification and regression tree analysis in public health: Methodological review. Annals of Behavioral Medicine, 26(3), 172-181.
Lupton, E. (2004). Thinking with type: A critical guide for designers, writers, editors, & students. New York: Princeton Architectural Press.
Mansfield, J. S., Legge, G. E. & Bane, M. C. (1996). Psychophysics of reading: XV. Font effect in normal and low vision. Investigative Ophthalmology and Visual Science, 37(8), 1492-1501.
Pelli, D. G., Burns, C. W., Farell, B., & Moore-Page, D. C. (2006). Feature detection and letter identification. Vision Research, 46, 4646-4674.
Roethlein, B. E. (1912). The relative legibility of different faces of printing types. The American Journal of Psychology, 23(1), 1-36.
Sanocki, T. (1988). Font regularity constraints on the process of letter recognition. Journal of Experimental Psychology, 14(3), 472-480.
Shaikh, A. D., & Chaparro, B. S. (2004). A survey of online reading habits of Internet users. Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting, 875-879.
Tinker, M. A. (1928). The relative legibility of the letters, the digits, and of certain mathematical signs. Journal of General Psychology, 1, 472-496.
Woods, R. J., Davis, K., & Scharff, L. F. V. (2005). Effects of typeface and font size on legibility for children. American Journal of Psychological Research, 1(1), 86-102.
Top Ten Mistakes of Shopping Cart Design Revisited:
A
Survey of
500 Top E-Commerce Websites
Summary: A list of common mistakes with e-commerce shopping cart design were identified in a previous issue of Usability News. This article revisits that list and reviews how 500 of the top Internet retail sites of today implemented their shopping cart design.
INTRODUCTION
Designers of e-commerce websites know that the user interaction with a site before a purchase is more critical to a site’s success than the purchase itself. Users frustrated with the online shopping process seldom get to the point of actual buying. Five years ago, we discussed the “Top Ten Mistakes of Shopping Cart Design” (Chaparro, 2002, Usability News 4.2). Since this time, we have evaluated many e-commerce websites and have observed many users as they shop online. We thought it would be interesting to review whether our Top Ten still hold true.
Abandoning a shopping cart before purchase is still a common occurrence in online shopping. MarketingSherpa’s study in 2007 (as cited by Baker, 2007) found that, out of a survey of 1,923 online users, there was an average shopping cart abandonment rate of 52.1%. In another report, Goldwyn (2003) reported an abandonment rate before checkout of 75%. Primary reasons for abandonment include high shipping charges, high cost of items, price comparison with other sites, saving items for purchase later, and cumbersome checkout processes that required too much personal information.
In this study, we evaluated the shopping carts of top e-commerce sites. We chose the websites from Internet Retailer’s Top 500 Guide for the year 2006. Their top 500 sites were based on web traffic and web sales and accounted for approximately 61% of total online retail sales (Brohan, 2007). From this list of 500 sites, 454 of the sites were included in the analysis. Fourty-six sites were excluded because they represented parent companies (e.g., Limited Brands is the parent of Express Fashion, Victoria’s Secret, Bath & Body Works, and The White Barn Candle Company) or because they used online order forms rather than a shopping cart and an online checkout system.
The following discusses each of the 2002 Top Ten Mistakes (in italics) and the 2007 comparison results.
Top Ten Mistakes of Shopping Cart Design
1. (2002) Calling a Shopping Cart anything but a Shopping Cart. Calling a shopping cart anything other than a shopping cart only causes confusion. Users are accustomed to the cart terminology and while certain domains may find it ‘cute’ to use a term specific to their product line (i.e., bookbag, order, basket) it is best to maintain consistency and stick with the ‘cart.’ Adding a graphic of a shopping cart also helps quick access.
(2007) Our international friends have reminded us that this guideline really applies to the U.S. and other countries that actually use the term shopping ‘cart’ to describe the physical cart used at a store. This guideline should be rephrased to state that the Shopping Cart should be called whatever is appropriate for the target users of that site’s location. In the United States, this is a shopping cart. In the UK, it may be a shopping basket or trolley. Regardless, users are typically accustomed to one term. Any other term will result in longer search times and potential confusion. We still maintain that an internationally accepted graphic helps (Figure 1). In our review of the top e-commerce sites, we found that 62% of the sites used the term “shopping cart”. The remaining sites used terms like shopping basket, basket, My Account, shopping bag, and My Gear (Figure 2).
Figure 1. Example of an Add to Cart link.
Figure 2. Terminology used to describe the shopping cart on the websites analyzed. Other terms used included shopping basket, My Account, shopping bag, and My Gear.
2. (2002) Requiring users to click a “BUY” button to add an item to the shopping cart. Adding Items to the shopping cart should be effortless and noncommittal. After all, the user is putting items into the cart for possible future purchase. When users are required to click a BUY button to add an item to the cart it is often unsettling since they are not necessarily ready to buy the item at this point – they just want to place it in the shopping cart. Buying is the final step in the shopping experience and it should not be presumed that adding an item to the cart is a commitment to buy. Users in our studies are very hesitant to click the BUY button and search for an Add to Cart button on the page instead.
(2007) While not as prevalent, we still found a few sites (6%) that require clicking a "Buy" button to add an item to the cart (Figure 3). While the savvy users no longer hesitate to do this, less experienced users still balk at this stage if they simply want to put an item aside for future consideration. Some sites now offer an Add to Wish List or Add to Shopping List button for shoppers. These terms suggest less commitment from the user. Other terminology used includes “Order”, “Add to Order”, “Purchase”, and “Place Order”.
Figure 3. Examples of various types of Buy Now buttons used on sites.
3. (2002) Giving little to no visual feedback that an item has been added to the cart. Some sites do not automatically take users to the shopping cart page when an item is added. This allows them to continue shopping without interruption. Generally, these sites have a shopping cart indicator somewhere on each page that updates and summarizes the cart content. A problem with this method, however, occurs when the visual feedback of the change to the cart’s content is too subtle or nonexistent, or is not in the users’ current browser view. In all cases, users do not believe anything has been added to the cart. As a result, they click on the Add to Cart button again and add the item a second time (and maybe again for a third time). Users end up having to go to the shopping cart page anyway just to see if the item has been added. Often times, they are surprised with multiple quantities of the same item.
(2007) Shopping Cart content status has improved significantly on most sites. Approximately 65% of sites now take the user to the shopping cart page when an item is added (Figure 4). Some sites also provide both options when adding an item to the cart, e.g., the user may both add an item to the shopping cart and view it, or they may simply add the item and continue shopping (Figure 5). Others still leave the user in the dark as to their running total or number of items currently in the cart.
Figure 4. Feedback provided by site on addition of item to shopping cart.
Figure 5. Example of options for viewing shopping cart after adding an item.
4. (2002) Forcing the user to view the Shopping Cart every time an item is placed there. As long as there is adequate visual feedback of the cart’s content, there is really no need to take the user to the shopping cart page every time an item is added. In fact, it is disruptive for multi-item shoppers, requires extra mouse clicks to continue shopping, and potentially limits how many items a person buys (they may be more inclined to checkout if they are already at the shopping cart page).
(2007) The key design issue here is providing adequate feedback of the cart content and total cost. If this information is provided (and is noticeable) on the product pages as items are added (e.g., Amazon.com), then it is not necessary to take the user to a separate Shopping Cart page. If this information is not clearly provided, then the user should be taken to a Shopping Cart page so they can confirm the item was added, view shipping charges and availability. Providing the cart status information on the site at all times is the most efficient method (Figure 6).
Figure 6. Example of site which shows the cart status, including total cost and an estimated ship date.
5. (2002) Asking the user to buy other related items before adding an item to the cart. This is the online equivalent to “do you want fries with your order?” and is not only irritating to users but also disorienting. After clicking a button or link to add an item to the cart, users are ready for some kind of feedback that the item has been added. Asking them to make a decision about other items makes them second-guess whether they actually pressed the correct button or link to add the desired item, or it aggravates them by soliciting items they do not want. A better approach is to place related items (i.e., batteries) on the item page or on the shopping cart page so they have the option to purchase them before checkout. Placing the control on the users makes them more willing to purchase.
(2007) Improvements in technology have allowed website designers to become more intelligent in their solicitation efforts. However, the more successful sites allow users to place items in the shopping cart before they suggest other products. Users appreciate being reminded of critical accessories that accompany a product (such as batteries) but do not like being interrupted before they can confirm that the item they really want is actually in the cart. Suggestions for related products are also helpful as long as the user can control whether they want to see them or not. From the sites evaluated, it was apparent that there were two major ways of addressing this issue: (1) do not offer any suggestions of additional items and accessories or (2) show users what other customers bought when purchasing the selected item. We have observed in our usability studies that forcing the user down a path of viewing related products is perceived very negatively.
6. (2002) Requiring a user to REGISTER before adding an item to the cart. Some sites we have tested require a user to register with personal information before an item can even be placed into the cart! This is a turn-off to users who may be browsing or comparison-shopping. They may or may not purchase the items, but they definitely do not want to commit personal information just to fill the shopping cart and will leave the site because of it.
(2007) Users still encounter this and hate it! In a recent SURL usability study of a high tech corporate website, users complained bitterly of having to register on the site before they could read a company white paper. Most said they would rather search the web for another way to access the same information rather than register with their personal information. Even requesting an email address (and not personal address info) is a deterrent. Users are afraid of getting on a list and receiving more junk email. Fortunately, the number of such sites was small (2%) in this study. These sites were predominantly sites that sold their merchandise through online downloads (e.g., online games, movies, software). Other such sites were ones that offered home deliveries (i.e., online grocery stores).
7. (2002) Requiring a user to change the quantity to zero to remove an item from the cart. Updating the shopping cart’s content can be tricky to program but should be seamless to the user. Many sites still require a user to enter ‘0’ in the quantity field and click an Update button or link to delete the item (Figure 7). Use of a Remove or Delete button next to an item is a far more intuitive way to achieve this.
(2007) Sites today offer several ways to update
the Shopping Cart content. The two most popular methods are a
“Remove/Delete” link (42%) under or next to the item on the shopping cart or
a “Remove/Delete” button (33%) next to the items
(Figure 7 and 8).
Unfortunately, 15% of our sample still required the user to manually change
the quantity to zero (Figure 9). Other sites display a graphical icon such as a trash
can or an “X” icon to delete the item. These icons work well when the symbol
is easily recognized but can be confusing when it is more obscure (see
Figure 10).
Figure 7. The four major ways of updating shopping cart content.
Figure 8. Terminology used to remove an item from the shopping cart.
Figure 9. Example of a shopping cart that requires users to change the quantity to zero to delete.
Figure 10. Unique graphical symbols used to remove an item from the shopping cart. The minus sign (cdw.com), the “X” symbol (simondelivers.com), and the trash can (solidsignal.com).
8. (2002) Including written instructions to update the items in the cart. Requiring users to read instructions on how to update the shopping cart is, in itself, a sign of poor design. First of all, users do not read such instructions. Second, if instructions are required, then the shopping cart interface design must not be intuitive. Users should be able to figure out how to remove or change the number of items desired from viewing the cart itself.
(2007) We surveyed some sites that still provide lengthy instructions (16%) on how to use the shopping cart. Users generally ignore this text even when having difficulty on the site. The instructions tended to be in plain text and in full sentences. This gives the user the impression that the information is simply “fine print” and not very important.
9. (2002) Requiring a user to scroll to find an Update cart button. Most carts offer an Update button or link to update changes made to the shopping cart (such as quantity). This function should be located such that it is always visible and clearly distinct from the rest of the shopping cart, regardless of the number of items in the cart.
(2007) With screen resolutions increasing over the past 5 years, users are typically able to see more on a web page than they used to. However, many sites still position the Update Cart button exclusively below the list of items. If users can add multiple items to the cart they have to scroll to see the Update Cart button. Providing this button above and below the cart allows users to quickly edit their cart without scrolling. We found some sites displayed an image of the item along with the shopping cart detail, thus making the page longer. We found only 6% of sites in our evaluation had the Update button both above and below the shopping cart. Most sites still follow the traditional method of placing the Update button at the bottom of the shopping cart, along with the Checkout button. Eighteen percent of the sites used a link or button other than Update Cart or offered no update capability at all (Figure 11).
Figure 11. Placement of Update Cart link in relation to the list of items.
10. (2002) Requiring a user to enter shipping, billing, and all personal information before knowing the final costs including shipping and tax. Shipping costs and taxes (if applicable) are a big factor in whether or not users complete their online orders. Users cannot access whether their purchase is truly a ‘deal’ or not until they have the final cost. Many sites require users to enter all shipping, billing, and credit card information before a final cost is provided. Access to shipping rates and tax from the shopping cart or item pages (before the user ventures down the purchasing path) is critical (Figure 12).
Figure 12. Users prefer to know shipping and tax costs before filling out final payment information.
(2007) Online shoppers today look for the words “Free Shipping”. Many sites offer this during peak buying season or for certain dollar amounts. Shipping costs are still one of the major deterrents of shopping online, especially for large or heavy items. Knowing these costs before a user enters his/her personal address and billing information is a must. More sites are now offering the option of opening a separate window that contains information on shipping costs. Unfortunately, too many sites still require a customer’s personal information (44%) before showing the final total after shipping and tax (Figure 13).
Figure 13. Percent of sites requiring personal information before revealing shipping charges.
What's New in 2007?
In addition to the issues above, we observed two other important aspects of shopping cart design.
1. Security, security, security.
Users today are very afraid of identity theft and have become aware of the
typical symbols sites use to show whether they are secure or not. We have
observed some users who would not even enter their email address on a site
without first viewing the site privacy policy. Some sites use CAPTCHA text
to insure a human is entering the requested information (see Figure 14). We
have observed several problems with CAPTCHAs:
There is a fine line between a good CAPTCHA and a
poor CAPTCHA. One that is very easy to read satisfies the user but
defeats its real purpose as it can also be read electronically. One that
is truly secure is often so unreadable, users make errors when trying to
decipher it. We have observed some users spend more time figuring out
the CAPTCHA than they do checking out.
There are still some users who are unfamiliar with
CAPTCHAs and consequently ignore them on the page. This results in a
page error which, if not explained properly, leads the user to believe
that they entered something in the shipping or billing information
incorrectly rather than the CAPTCHA. Even if users are familiar with a
CAPTCHA, many do not know that it is called this.
CAPTCHAs are often not accessible to screen readers.
Figure 14. Sample of a CAPTCHA used on a website. Note that this CAPTCHA is accessible by screen readers (through the speaker icon).
Security certificates from third party companies are also another means of ensuring that potential online customers are not anxious when it comes to entering their credit card and personal information during checkout (Figure 15). Companies like VeriSign and ControlScan offer (for a fee) software packages to websites ensuring that they are secure. Secure Sockets Layer (SSL) technology is another way of protecting personal information in online stores. SSL technology encrypts sensitive and personal information for transfer across networks thereby “hiding” the information from public view.
Figure 15. Security logos typically found on the bottom of the screen ensuring customers of the trustworthiness of the site.
2. Out of Stock Items.
We have observed that many sites do not let users know if an item is in stock until they reach the checkout stage. We’ve also seen some confusion as to whether backordered items were included in the total cost. Users should be notified an item is out of stock on the main product page and asked if they still want to include backordered items in their order.
Conclusion
If an e-commerce site is to succeed, designers must consider the usability of the entire shopping experience for its users. Probably the most critical part of this process is the shopping – finding items, adding them to the cart, understanding total costs – and not the final purchasing. In this article we reviewed our 2002 list of mistakes in shopping cart design and surveyed how 500 top e-commerce sites designed their shopping cart. We found that all of the 2002 issues remain usability concerns in today’s websites. Proper attention to these issues can only improve a sites usability and, in turn, users’ willingness to stay online to purchase.
References
Baker, C. (2007). Shopping cart abandonment
benchmarks. February 26, 2007. Retrieved 6/7/07:
http://usabilitynotes.typepad.com/usabilitynotes/2007/02/shopping_cart_a.html
Chaparro, B. (2002). Top ten mistakes of shopping cart design, July, 2002. Retrieved 7//7/07: http://psychology.wichita.edu/surl/usabilitynews/42/shoppingcart.htm
Goldwyn, C. (2003). The art of the cart: Why people
abandon shopping carts.
http://visibility.tv/tips/shopping_cart_abandonment.html
Brohan, J. (2007). The Top 500 Guide. June, 2007.
Retrieved 6/7/07:
http://www.internetretailer.com/article.asp?id=22579
A Review of MoraeTM 2.0 for Usability Testing
Summary: TechSmith’s recent release, MoraeTM 2.0, features a new graphing tool, integrated satisfaction survey, and embedded task definitions. The editable marker log in Observer and the improved timeline controls in the Manager improve operator efficiency. This article highlights these and other new features of the new 2.0.
INTRODUCTION
In our last issue of Usability News (9.1) we provided a review of the usability testing software called MoraeTM (version 1.3). Since then, a new version (2.0) has been released. This release of Morae 2.0TM addresses many of the issues we raised in our article and has exceeded our expectations. The new release improves upon the existing features as well as adds some new tools that make this a valuable upgrade.
For the uninitiated, MoraeTM is a tool that can record onscreen activity along with camera video and audio. These capabilities give it the muscle to capture every aspect of the user experience and performance while interacting with any interface on the computer, including software interfaces and websites. MoraeTM 2.0 comes with the Recorder, Observer (formerly Remote Viewer), Manager, and Player. The Observer has the ability to remotely connect to the Recorder and observe the user’s onscreen activities along with the camera view (picture-in-picture PIP) and audio. This makes remote viewing very easy. The Manager is used to import the recordings, add and/or edit markers to segment different tasks within a recording, and combine different segments across different recordings to produce highlight videos. The highlight videos can be used to compliment the recommendations suggested on the written report. Player is simply a media player that is capable of playing the rendered highlight videos.
MoraeTM 2.0 offers a set of new features as well as numerous improvements over its previous versions.
The Recorder
The Recorder interface is quite different from the 1.3 version (Figures 1a & 1b). The settings are categorized into study settings, recording settings, and machine settings rather than all being presented on one page. One major difference, other than the layout, is that under the Study Settings the tasks can be defined so that markers can be anchored with the appropriate task while flagging in the Observer. This is a very useful feature although it would be even better if the experimenter could store pre-defined random orders of the tasks by participant. It would also be nice if there was an option to copy and paste the task definitions all at once from Word/Excel. A satisfaction survey (SUS or a customized survey) can also be administered directly from MoraeTM (Figures 1c & 1d). The results from the survey can then be directly graphed using the Manager.
One downside of the new Recorder is that it stores the path where the files are written under the Machine Settings, which is not intuitive to find. This path setting would be more accessible if placed on the top level of the application. Also, the configuration files are now project dependent unlike in the previous version. It would be helpful if MoraeTM stored all the configuration files in one location and allowed the user to choose a configuration previously made or to create a new one from within MoraeTM without having to browse through the Windows file structure to find the configuration file. Saving the configuration file is not as intuitive either since clicking "OK" on the study setup does not save the configuration file (nor is the user prompted to do so). Even though the configuration files are project specific, it would be nice to set up some attributes as defaults for all studies (like the mouse pointer and the mouse click feedback).
Figure 1a. MoraeTM Recorder (Version 1.3)
Figure 1b. MoraeTM Recorder (Version 2.0)
Figure 1c. MoraeTM Recorder – Satisfaction Survey (Version 2.0)
Figure 1d. MoraeTM Recorder – Satisfaction Survey setting (Version 2.0)
The Observer
The Observer is the new application that replaces the 1.3 Remote Viewer (Figures 2a & 2b). It allows observers (or loggers) to remotely view a session and set markers in real time (Figure 2a). Ideally, the start and end task markers should appear in the order set in the task definitions (Figure 2b), but this does not always happen. Sometimes when a new task is logged, it does not use the same order defined in the Recorder. This is particularly annoying if the tasks are randomized. Also if a task is incorrectly logged, the logger cannot go back and change it; it needs to be completely removed. If notes specific to the marker are placed by the logger, the same note propagates down the list to every other marker that follows until it is removed manually.
One feature that would be useful in the Observer would be a “screen snap” feature, which would allow the observer to take a picture of the participant's screen in real time. This would be helpful to experimenters who may want to show a screen shot in a written report of the usability analysis.
Figure 2a. MoraeTM Observer – Marker Log (Version 2.0)
Figure 2b. MoraeTM Recorder – Task Definition (Version 2.0)
The Manager
The primary difference in the new MoraeTM Manager is the presence of a new graph tab (Figure 3a & 3b). Graphs can be made for time on task, mouse clicks, satisfaction survey (SUS), or task score. Data can be graphed by participant or by task. In addition, improvements have been made to the timeline (Figure 3c & 3d) which allow flags to be set more efficiently.
Figure 3a. MoraeTM Manager (Version 1.3)
Figure 3b. MoraeTM Manager (Version 2.0)
Figure 3c. MoraeTM Manager – Timeline (Version 1.3)
Figure 3d. MoraeTM Manager – Timeline (Version 2.0)
The Play button is now a toggle (Figure 3d) between play and pause, and can also be activated by pressing the spacebar. The rewind and forward functions are still missing from the timeline controls. The interval markings have been improved in visual appearance and flags are replaced by easily selectable diamonds. When the mouse is over a marker, the marker still turns green regardless of the marker type. This can be a problem when the markers are very close to each other and they need to be selected. When the marker is deleted, the play head moves to the next marker position on the timeline. This can be a nuisance when the timeline is zoomed. The zoom bar is also difficult to see because it is the same color as the rest of the timeline. This is challenging when the timeline needs to be dragged forward or backward using the zoom bar.
One noteworthy feature is the ability of the new Manager to move a marker to the play head position (current frame that is playing). This is a huge timesaver. The timeline also offers a filter which enables viewing selected marker types, among other criteria. This is useful when creating clips from a segment. However, when a marker is selected and the Set Selection Start button is clicked, both the Set Selection Start and the End are placed on the same marker position. If the Manager would place the Set Selection End on the next marker position then it would save the user from extra mouse clicks.
One feature the Manager is missing is a visual link between the timeline and the list of markers. The chronological list of markers and comments on the search results window should be highlighted according to where the play head is on the timeline (Figure 3b). When the recordings with the markers and comments are imported it is useful to see where on the timeline the comments are located. Also, when those recordings are imported, the task classification (marked by the logger as "Task 1...Task2...etc) is lost and the markers show up only as Start/End Task markers on the Analyze-Project window.
A notable improvement in the Manager is the ability to segment a task into sections. It is not uncommon for users to take breaks within a session or to be temporarily distracted (i.e., a cell phone). In such a scenario, MoraeTM now allows that segment from the timeline to be removed from the task so the time on task can be calculated without the distraction.
Conclusion
MoraeTM 2.0 (now 2.01*) offers significant improvements over the previous version (see Table 1). The new graphing tab in Manager, editable markers in Observer, task definition and built-in/customizable satisfaction survey in the Recorder, and most importantly, the improvements on the timeline functions and interface make this version of MoraeTM a useful upgrade.
Table 1. MoraeTM 2.0 Upgrade features
|
Recorder |
Observer (formerly Remote Viewer) |
Manager |
|
Settings segregated into: Study Details Machine Details and Recording Details Tasks can be defined within Manager Satisfaction survey (SUS or custom) can be defined within manager |
Improved task logging with editable markers Success can also be recorded |
New graphing tab added with flexible graphing ability Timeline interface and look improved Marker flags replaced by easily selectable diamonds Ability of the marker to be moved to the play head position Timeline control has play-pause toggle Timeline control now has keyboard shortcuts Time on task can now be more accurately measured |
*The SURL team highly recommends the new 2.01 upgrade which fixes some serious memory management problems in the 2.0 release.
References
Morae™, TechSmith ©2004 (http://www.techsmith.com/morae.asp)
Contact Doug
Fox or Barbara
Chaparro with questions regarding this site.
Last update:
August 10, 2007
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