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Preface to the Second Edition | |
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Acknowledgments | |
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Biographies | |
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Introduction | |
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What Is User Experience | |
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What Are User Experience Metrics? | |
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The Value of UX Metrics | |
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Metrics for Everyone | |
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New Technologies in UX Metrics | |
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Ten Myths about UX Metrics | |
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Metrics Take Too Much Time to Collect | |
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UX Metrics Cost Too Much Money | |
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UX Metrics Are Not Useful When Focusing on Small Improvements | |
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UX Metrics Don't Help Us Understand Causes | |
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UX Metrics Are Too Noisy | |
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You Can Just Trust Your Gut | |
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Metrics Don't Apply to New Products | |
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No Metrics Exist for the Type of Issues We Are Dealing with | |
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Metrics Are not Understood or Appreciated by Management | |
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It's Difficult to Collect Reliable Data with a Small Sample Size | |
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Background | |
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Independent and Dependent Variables | |
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Types of Data | |
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Nominal Data | |
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Ordinal Data | |
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Interval Data | |
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Ratio Data | |
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Descriptive Statistics | |
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Measures of Central Tendency | |
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Measures of Variability | |
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Confidence Intervals | |
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Displaying Confidence Intervals as Error Bars | |
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Comparing Means | |
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Independent Samples | |
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Paired Samples | |
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Comparing More Than Two Samples | |
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Relationships Between Variables | |
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Correlations | |
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Nonparametric Tests | |
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The x<sup>2</sup> Test | |
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Presenting your Data Graphically | |
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Column or Bar Graphs | |
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Line Graphs | |
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Scatterplots | |
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Pie or Donut Charts | |
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Stacked Bar or Column Graphs | |
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Summary | |
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Planning | |
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Study Goals | |
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Formative Usability | |
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Summative Usability | |
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User Goals | |
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Performance | |
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Satisfaction | |
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Choosing the Right Metrics: Ten Types of Usability Studies | |
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Completing a Transaction | |
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Comparing Products | |
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Evaluating Frequent Use of the Same Product | |
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Evaluating Navigation and/or Information Architecture | |
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Increasing Awareness | |
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Problem Discovery | |
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Maximizing Usability for a Critical Product | |
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Creating an Overall Positive User Experience | |
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Evaluating the Impact of Subtle Changes | |
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Comparing Alternative Designs | |
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Evaluation Methods | |
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Traditional (Moderated) Usability Tests | |
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Online (Unmoderated) Usability Tests | |
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Online Surveys | |
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Other Study Details | |
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Budgets and Timelines | |
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Participants | |
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Data Collection | |
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Data Cleanup | |
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Summary | |
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Performance Metrics | |
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Task Success | |
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Binary Success | |
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Levels of Success | |
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Issues in Measuring Success | |
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Time on Task | |
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Importance of Measuring Time on Task | |
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How to Collect and Measure Time on Task | |
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Analyzing and Presenting Time-on-Task Data | |
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Issues to Consider When Using Time Data | |
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Errors | |
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When to Measure Errors | |
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What Constitutes an Error? | |
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Collecting and Measuring Errors | |
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Analyzing and Presenting Errors | |
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Issues to Consider When Using Error Metrics | |
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Efficiency | |
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Collecting and Measuring Efficiency | |
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Analyzing and Presenting Efficiency Data | |
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Efficiency as a Combination of Task Success and Time | |
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Learnability | |
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Collecting and Measuring Learnability Data | |
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Analyzing and Presenting Learnability Data | |
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Issues to Consider When Measuring Learnability | |
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Summary | |
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Issue-Based Metrics | |
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What Is a Usability Issue? | |
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Real Issues versus False Issues | |
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How to Identify an Issue | |
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In-Person Studies | |
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Automated Studies | |
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Severity Ratings | |
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Severity Ratings Based on the User Experience | |
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Severity Ratings Based on a Combination of Factors | |
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Using a Severity Rating System | |
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Some Caveats about Rating Systems | |
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Analyzing and Reporting Metrics for Usability Issues | |
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Frequency of Unique Issues | |
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Frequency of Issues Per Participant | |
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Frequency of Participants | |
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Issues by Category | |
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Issues by Task | |
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Consistency in Identifying Usability Issues | |
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Bias in Identifying Usability Issues | |
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Number of Participants | |
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Five Participants Is Enough | |
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Five Participants Is Not Enough | |
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Our Recommendation | |
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Summary | |
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Self-Reported Metrics | |
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Importance of Self-Reported Data | |
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Rating Scales | |
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Likert Scales | |
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Semantic Differential Scales | |
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When to Collect Self-Reported Data | |
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How to Collect Ratings | |
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Biases in Collecting Self-Reported Data | |
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General Guidelines for Rating Scales | |
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Analyzing Rating-Scale Data | |
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Post-Task Ratings | |
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Ease of Use | |
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After-Scenario Questionnaire (ASQ) | |
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Expectation Measure | |
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A Comparison of Post-task Self-Reported Metrics | |
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Postsession Ratings | |
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Aggregating Individual Task Ratings | |
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System Usability Scale | |
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Computer System Usability Questionnaire | |
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Questionnaire for User Interface Satisfaction | |
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Usefulness, Satisfaction, and Ease-of-Use Questionnaire | |
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Product Reaction Cards | |
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A Comparison of Postsession Self-Reported Metrics | |
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Net Promoter Score | |
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Using SUS to Compare Designs | |
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Online Services | |
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Website Analysis and Measurement Inventory | |
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American Customer Satisfaction Index | |
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OpinionLab | |
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Issues with Live-Site Surveys | |
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Other Types of Self-Reported Metrics | |
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Assessing Specific Attributes | |
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Assessing Specific Elements | |
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Open-Ended Questions | |
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Awareness and Comprehension | |
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Awareness and Usefulness Gaps | |
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Summary | |
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Behavioral and Physiological Metrics | |
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Observing and Coding Unprompted Verbal Expressions | |
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Eye Tracking | |
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How Eye Tracking Works | |
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Visualizing Eye-Tracking Data | |
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Areas of Interest | |
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Common Eye-Tracking Metrics | |
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Eye-Tracking Analysis Tips | |
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Pupillary Response | |
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Measuring Emotion | |
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Affectiva and the Q-Sensor | |
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Blue Bubble Lab and Emovision | |
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Seren and Emotiv | |
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Stress and Other Physiological Measures | |
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Heart Rate Variance | |
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Heart Rate Variance and Skin Conductance Research | |
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Other Measures | |
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Summary | |
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Combined and Comparative Metrics | |
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Single Usability Scores | |
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Combining Metrics Based on Target Goals | |
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Combining Metrics Based on Percentages | |
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Combining Metrics Based on Z Scores | |
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Using Single Usability Metric | |
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Usability Scorecards | |
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Comparison to Goals and Expert Performance | |
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Comparison to Goals | |
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Comparison to Expert Performance | |
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Summary | |
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Special Topics | |
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Live Website Data | |
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Basic Web Analytics | |
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Click-Through Rates | |
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Drop-Off Rates | |
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A/B Tests | |
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Card-Sorting Data | |
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Analyses of Open Card-Sort Data | |
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Analyses of Closed Card-Sort Data | |
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Tree Testing | |
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Accessibility Data | |
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Return-On-Investment Data | |
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Summary | |
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Case Studies | |
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Net Promoter Scores and the Value of a Good User Experience | |
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Methods | |
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Results | |
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Prioritizing Investments in Interface Design | |
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Discussion | |
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Conclusion | |
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References | |
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Biographies | |
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Measuring the Effect of Feedback on Fingerprint Capture | |
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Methodology | |
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Discussion | |
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Conclusion | |
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Acknowledgment | |
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References | |
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Biographies | |
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Redesign of a Web Experience Management System | |
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Test Iterations | |
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Data Collection | |
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Workflow | |
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Results | |
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Conclusions | |
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Biographies | |
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Using Metrics to Help Improve a University Prospectus | |
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Example 1: Deciding on Actions after Usability Testing | |
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Example 2: Site-Tracking Data | |
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Example 3: Triangulation for Iteration of Personas | |
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Summary | |
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Acknowledgments | |
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References | |
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Biographies | |
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Measuring Usability Through Biometrics | |
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Background | |
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Methods | |
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Biometric Findings | |
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Qualitative Findings | |
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Conclusions and Practitioner Take-Aways | |
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Acknowledgments | |
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References | |
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Biographies | |
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Ten Keys to Success | |
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Make Data Come Alive | |
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Don't Wait to Be Asked to Measure | |
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Measurement Is Less Expensive Than You Think | |
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Plan Early | |
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Benchmark Your Products | |
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Explore Your Data | |
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Speak the Language of Business | |
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Show Your Confidence | |
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Don't Misuse Metrics | |
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Simplify Your Presentation | |
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References | |
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Index | |