Measuring the user experience: collecting, analyzing, and presenting usability metrics
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| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Amsterdam [u.a.]
Elsevier, Morgan Kaufmann
2013
|
| Edition: | 2. ed. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Literaturverz. S. 289 - 295 |
| Physical Description: | XVII, 301 S. Ill., graph. Darst. |
| ISBN: | 9780124157811 |
Staff View
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| 245 | 1 | 0 | |a Measuring the user experience |b collecting, analyzing, and presenting usability metrics |c Tom Tullis ; Bill Albert |
| 250 | |a 2. ed. | ||
| 264 | 1 | |a Amsterdam [u.a.] |b Elsevier, Morgan Kaufmann |c 2013 | |
| 300 | |a XVII, 301 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 500 | |a Literaturverz. S. 289 - 295 | ||
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| 650 | 4 | |a User interfaces (Computer systems) |x Measurement | |
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| adam_text | Contents
PREFACE
TO THE SECOND EDITION
xiii
ACKNOWLEDGMENTS
xv
BIOGRAPHIES
xvii
CHAPTER
1
Introduction
1
1.1
What Is User Experience
4
1.2
What Are User Experience Metrics?
6
1.3
The Value of UX Metrics
8
1.4
Metrics for Everyone
9
1.5
New Technologies in UX Metrics
10
1.6
Ten Myths about UX Metrics
і
:»,
Myth
1:
Metrics Take Too Much lime to Collect
:U,
Myth
2:
UX Metrics Cost Too Much Money
12
Myth
3:
UX Metrics Are Not Useful When Focusing on
Small improvements
12
Myth
4:
UX Metrics Don t Help Us Understand Causes
12
Myth
5:
UX Metrics Are Too Noisy
12
Myth
6:
You Can Just Trust Your Gut
13
Myth
7:
Metrics Don t Apply to New Products
13
Myth
8:
No Metrics Exist for the Type of Issues We Are Dealing with
13
Myth
9:
Metrics Are not Understood or Appreciated by Management
14
Myth
10:
It s Difficult to Collect Reliable Data with a Small
Sample Size
14
CHAPTER
2
Background
15
2.1
Independent and Dependent Variables
16
2.2
Types of Data .in
2.2.1
Nominal Daly
:Ш
2.2.2
Ordinal Data
Xi
2.2.3
Interval Data
№
2.2.4
Ratio Data
¡Л.
2.3
Descriptive Statistics
W
2.3.1
Measures of Central Tendency ;L9
2.3.2
Measures of Variability
21
2.3.3
Confidence Intervals
22
2.3.4
Displaying Confidence intervals as Error Bars
24
2.4
Comparing Means
25
2.4.1
Independent Samples
26
2.4.2
Paired Samples
27
2.4.3
Comparing More Than Two Samples
29
2.5
Relationships Between Variables
30
2.5.1
Correlations
30
2.6
Nonparametric Tests
31
2.6.1
The
χ2
Test
31
2.7
Presenting your Data Graphically
32
2.7.1
Column or Bar Graphs
33
2.7.2
Line Graphs
35
2.7.3
Scatterplots
36
2.7.4
Pie or
Donut
Charts
38
2.7.5
Stacked Bar or Column Graphs
39
2.8
Summary
40
CHAPTER
3
Planning
41
3.1
Study Goals
42
3.1.1
Formative Usability
42
3.1.2
Summative Usability
43
3.2
User Goals
44
3.2.1
Performance
44
3.2.2
Satisfaction
44
3.3
Choosing the Right Metrics: Ten Types of Usability Studies
45
3.3.1
Completing a Transaction
45
3.3.2
Comparing Products
47
3.3.3
Evaluating Frequent Use of the Same Product
47
3.3.4
Evaluating Navigation and/or Information Architecture
48
3.3.5
Increasing Awareness
48
3.3.6
Problem Discovery
49
3.3.7
Maximizing Usability for a Critical Product
50
3.3.8
Creating an Overall Positive User Experience
51
3.3.9
Evaluating the Impact of Subtle Changes
51
3.3.10
Comparing Alternative Designs
52
3.4
Evaluation Methods
52
3.4.1
Traditional (Moderated) Usability Tests
53
3.4.2
Online (Unmoderated) Usability Tests
54
3.4.3
Online Surveys
56
3.5
Other Study Details
57
3.5.1
Budgets and Timelines
57
3.5.2
Participants
58
3.5.3
Data Collection
60
3.5.4
Data Cleanup
60
3.6
Summary
61
CHAPTER
4
Performance Metrics
63
4.1
Task Success
65
4.1.1
Binary Success
66
4.1.2
Levels of Success
70
4.1.3
Issues in Measuring Success
73
4.2
Time on Task
74
4.2.1
Importance of Measuring Time on Task
75
4.2.2
How to Collect and Measure Time on Task
75
4.2.3
Analyzing and Presenting Time-on-Task Data
78
4.2.4
Issues to Consider When Using Time Data
81
4.3
Errors
82
4.3.1
When to Measure Errors
82
4.3.2
What Constitutes an Error?
83
4.3.3
Collecting and Measuring Errors
84
4.3.4
Analyzing and Presenting Errors
84
4.3.5
Issues to Consider When Using Error Metrics
86
4.4
Efficiency
86
4.4.1
Collecting and Measuring Efficiency
87
4.4.2
Analyzing and Presenting Efficiency Data
88
4.4.3
Efficiency as a Combination of Task Success and Time
90
4.5
Learnability
92
4.5.1
Collecting and Measuring Learnability Data
94
4.5.2
Analyzing and Presenting Learnability Data
94
4.5.3
Issues to Consider When Measuring
Leamabïlïty
96
4.6
Summary
96
CHAPTER
5
Issue-Based Metrics
99
5.1
What Is a Usability Issue?
100
5.1.1
Real Issues versus False Issues
101
5.2
How to Identify an Issue
102
5.2.1
In-Person Studies
102
5.2.2
Automated Studies
103
5.3
Severity Ratings
103
5.3.1
Severity Ratings Based on the User Experience
104
5.3.2
Severity Ratings Based on a Combination of Factors
105
5.3.3
Using a Severity Rating System
106
5.3.4
Some Caveats about Rating Systems
107
5.4
Analyzing and Reporting Metrics for Usability Issues
107
5.4.1
Frequency of Unique Issues li.QU
5.4.2
Frequency of Issues Per Participant
i.Oý
5.4.3
Frequency of Participants
.1.09
5.4.4
Issues by Category
і
10
5.4.5
Issues by Task ILL
5.5
Consistency in Identifying Usability issues 111
5.6
Bias in Identifying Usability Issues
113
5.7
Number of Participants
115
5.7.1
Five Participants Is Enough
115
5.7.2
Five Participants Is Not Enough
117
5.7.3
Out Recommendation
118
5.8
Summary
119
CHAPTER
6
Self-Reported Metrics
121
6.1
Importance of Self-Reported Data
123
6.2
Rating Scales
123
6.2.1
Likért
Scales
123
6.2.2
Semantic Differential Scales
124
6.2.3
When to Collect Self-Reported Data
125
6.2.4
How to Collect Ratings
125
6.2.5
Biases in Collecting Self-Reported Data
126
6.2.6
General Guidelines for Rating Scales
126
6.2.7
Analyzing Rating-Scale Data
127
6.3
Post-Task Ratings
131
6.3.1
Ease of Use
131
6.3.2
After-Scenario Questionnaire (ASQ)
132
6.3.3
Expectation Measure
132
6.3.4
A Comparison of Post-task Self-Reported Metrics
133
6.4
Postsession
Ratings
137
6.4.1
Aggregating Individual Task Ratings
137
6.4.2
System Usability Scale
137
6.4.3
Computer System Usability Questionnaire
140
6.4.4
Questionnaire for User Interface Satisfaction
141
6.4.5
Usefulness, Satisfaction, and Ease-of-Use Questionnaire
142
6.4.6
Product Reaction Cards
144
6.4.7
A Comparison of
Postsession
Self-Reported Metrics
145
6.4.8
Net Promoter Score
146
6.5
Using
SUS
to Compare Designs
147
6.6
Online Services
147
6.6.1
Website Analysis and Measurement Inventory
148
6.6.2
American Customer Satisfaction Index
148
6.6.3
OpinionLab
149
6.6.4
Issues with Live-Site Surveys
152
6.7
Other Types of Self-Reported Metrics
154
6.7.1
Assessing Specific Attributes
154
6.7.2
Assessing Specific Elements
156
6.7.3
Open-Ended Questions
158
6.7.4
Awareness and Comprehension
159
6.7.5
Awareness and Usefulness Gaps
160
6.8
Summary
161
CHAPTER
7
Behavioral and Physiological Metrics
163
7.1
Observing and Coding Unprompted Verbal Expressions
163
7.2
Eye Tracking
165
7.2.1
How Eye Tracking Works
165
7.2.2
Visualizing Eye-Tracking Data
167
7.2.3
Areas of Interest
170
7.2.4
Common Eye-Tracking Metrics
172
7.2.5
Eye-Tracking Analysis Tips
174
7.2.6
Pupillary Response
175
7.3
Measuring Emotion
176
7.3.1
Affectiva and the Q-Sensor
176
7.3.2
Blue Bubble Lab and Emovision
179
7.3.3 Seren
and
Emotiv
180
7.4
Stress and Other Physiological Measures
182
7.4.1
Heart Rate Variance
182
7.4.2
Heart Rate Variance and Skin Conductance Research
183
7.4.3
Other Measures
183
7.5
Summary
185
CHAPTER
8
Combined and Comparative Metrics
187
8.1
Single Usability Scores
187
8.1.1
Combining Metrics Based on Target Goals
188
8.1.2
Combining Metrics Based on Percentages
189
8.1.3
Combining Metrics Based on
Z
Scores
196
8.1.4
Using Single Usability Metric
1.98
8.2
Usability Scorecards
200
8.3
Comparison to Goals and Expert Performance
204
8.3.1
Comparison to Goals
204
8.3.2
Comparison to Expert Performance
206
8.4
Summary
208
CHAPTER
9
Special Topics
209
9.1
Live Website Data
209
9.1.1
Basic Web Analytics
210
9.1.2
Click-Through Rates
213
9.1.3
Drop-Off Rates
215
9.1.4
A/B Tests
216
9.2
Card-Sorting Data
218
9.2.1
Analyses of Open Card-Sort Data
219
9.2.2
Analyses of Closed Card-Sort Data
224
9.2.3
Tree Testing
227
9.3
Accessibility Data
228
9.4
Return-On-lnvestment
öaïa
Я32
9.5
Summary
2Ш
CHAPTER
10
Case Studies
10.1
Net Promoter Scores
muí
the
Уаіію
of a wood User
f
ЈфегѕоГаео
10.1.1
Methods
239
10.1.2
Results
240
10.1.3
Prioritizing Investments in Interface Design
241
10.1.4
Discussion
242
10.1.5
Conclusion
243
References
244
Biographies
244
10.2
Measuring the Effect of Feedback on Fingerprint Capture
244
10.2.1
Methodology
245
10.2.2
Discussion
252
10.2.3
Conclusion
253
Acknowledgment
253
References
253
Biographies
254
10.3
Redesign of a Web Experience Management System
254
10.3.1
Test Iterations
255
10.3.2
Data Collection
256
10.3.3
Workflow
257
10.3.4
Results
261
10.3.5
Conclusions
262
Biographies
262
10.4
Using Metrics to Help Improve a University Prospectus
263
10.4.1
Example
1:
Deciding on Actions after Usability Testing
264
10.4.2
Example 2 Site-Tracking Data
267
10.4.3
Example
3: Triangulation
for Iteration of
Personas
269
10.4.4
Summary
270
Acknowledgments
Ά7Ό
References
270
Biographies
270
10.5
Measuring Usability Through Biometrics
271
10.5.1
Background
271
10.5.2
Methods
272
10.5.3 Biometrie
Findings
273
10.5.4
Qualitative Findings
274
10.5.5
Conclusions and Practitioner Take-Aways
275
Acknowledgments
276
References
276
Biographies
277
CHAPTER
11
Ten Keys to Success
279
11.1
Make Data Come Alive
279
J.1.2 Don t Wait to Be Asked to Measure
Ж1
11.3
Measurement Is Less Expensive Than You
іїіінк
Ä82
11.4
Plan Early
28?
11.6
Benchmark Your Products
283
11.6
Explore Your Data
Ш4
11.7
Speak the Language of Business 28S
11.8
Show Your Confidence
Л85
11.9
Don t Misuse Metrics
286
11.10
Simplify Your Presentation
287
REFERENCES
289
INDEX
297
|
| any_adam_object | 1 |
| author | Tullis, Tom 1952- Albert, Bill |
| author_GND | (DE-588)1029801010 (DE-588)1029801681 |
| author_facet | Tullis, Tom 1952- Albert, Bill |
| author_role | aut aut |
| author_sort | Tullis, Tom 1952- |
| author_variant | t t tt b a ba |
| building | Verbundindex |
| bvnumber | BV041261165 |
| classification_rvk | CW 4000 ST 278 |
| classification_tum | DAT 610f |
| ctrlnum | (OCoLC)859394053 (DE-599)BVBBV041261165 |
| discipline | Informatik Psychologie |
| edition | 2. ed. |
| format | Book |
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| id | DE-604.BV041261165 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T00:43:26Z |
| institution | BVB |
| isbn | 9780124157811 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-026234994 |
| oclc_num | 859394053 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-M347 DE-Aug4 DE-83 DE-573 DE-1049 DE-739 DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-20 DE-703 |
| owner_facet | DE-473 DE-BY-UBG DE-M347 DE-Aug4 DE-83 DE-573 DE-1049 DE-739 DE-355 DE-BY-UBR DE-91G DE-BY-TUM DE-20 DE-703 |
| physical | XVII, 301 S. Ill., graph. Darst. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Elsevier, Morgan Kaufmann |
| record_format | marc |
| spelling | Tullis, Tom 1952- Verfasser (DE-588)1029801010 aut Measuring the user experience collecting, analyzing, and presenting usability metrics Tom Tullis ; Bill Albert 2. ed. Amsterdam [u.a.] Elsevier, Morgan Kaufmann 2013 XVII, 301 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Literaturverz. S. 289 - 295 User interfaces (Computer systems) User interfaces (Computer systems) Measurement Measurement Technology assessment Bewertung (DE-588)4006340-9 gnd rswk-swf Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd rswk-swf Mensch-Maschine-Schnittstelle (DE-588)4720440-0 gnd rswk-swf Benutzerfreundlichkeit (DE-588)4005541-3 gnd rswk-swf Datenerhebung (DE-588)4155272-6 gnd rswk-swf Mensch-Maschine-Schnittstelle (DE-588)4720440-0 s Benutzerfreundlichkeit (DE-588)4005541-3 s Bewertung (DE-588)4006340-9 s Datenerhebung (DE-588)4155272-6 s DE-604 Mensch-Maschine-Kommunikation (DE-588)4125909-9 s 1\p DE-604 Albert, Bill Verfasser (DE-588)1029801681 aut Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026234994&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Tullis, Tom 1952- Albert, Bill Measuring the user experience collecting, analyzing, and presenting usability metrics User interfaces (Computer systems) User interfaces (Computer systems) Measurement Measurement Technology assessment Bewertung (DE-588)4006340-9 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Mensch-Maschine-Schnittstelle (DE-588)4720440-0 gnd Benutzerfreundlichkeit (DE-588)4005541-3 gnd Datenerhebung (DE-588)4155272-6 gnd |
| subject_GND | (DE-588)4006340-9 (DE-588)4125909-9 (DE-588)4720440-0 (DE-588)4005541-3 (DE-588)4155272-6 |
| title | Measuring the user experience collecting, analyzing, and presenting usability metrics |
| title_auth | Measuring the user experience collecting, analyzing, and presenting usability metrics |
| title_exact_search | Measuring the user experience collecting, analyzing, and presenting usability metrics |
| title_full | Measuring the user experience collecting, analyzing, and presenting usability metrics Tom Tullis ; Bill Albert |
| title_fullStr | Measuring the user experience collecting, analyzing, and presenting usability metrics Tom Tullis ; Bill Albert |
| title_full_unstemmed | Measuring the user experience collecting, analyzing, and presenting usability metrics Tom Tullis ; Bill Albert |
| title_short | Measuring the user experience |
| title_sort | measuring the user experience collecting analyzing and presenting usability metrics |
| title_sub | collecting, analyzing, and presenting usability metrics |
| topic | User interfaces (Computer systems) User interfaces (Computer systems) Measurement Measurement Technology assessment Bewertung (DE-588)4006340-9 gnd Mensch-Maschine-Kommunikation (DE-588)4125909-9 gnd Mensch-Maschine-Schnittstelle (DE-588)4720440-0 gnd Benutzerfreundlichkeit (DE-588)4005541-3 gnd Datenerhebung (DE-588)4155272-6 gnd |
| topic_facet | User interfaces (Computer systems) User interfaces (Computer systems) Measurement Measurement Technology assessment Bewertung Mensch-Maschine-Kommunikation Mensch-Maschine-Schnittstelle Benutzerfreundlichkeit Datenerhebung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=026234994&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT tullistom measuringtheuserexperiencecollectinganalyzingandpresentingusabilitymetrics AT albertbill measuringtheuserexperiencecollectinganalyzingandpresentingusabilitymetrics |