Task Times

Browse Content by Topic

UX ( 74 )
Methods ( 62 )
Usability Testing ( 55 )
Statistics ( 52 )
Survey ( 41 )
NPS ( 39 )
Benchmarking ( 33 )
Usability ( 32 )
Sample Size ( 32 )
Rating Scale ( 32 )
Customer Experience ( 31 )
User Research ( 29 )
SUS ( 28 )
Net Promoter Score ( 28 )
Usability Problems ( 18 )
Questionnaires ( 18 )
Rating Scales ( 17 )
Metrics ( 17 )
Measurement ( 16 )
User Experience ( 15 )
UMUX-lite ( 15 )
Surveys ( 15 )
Satisfaction ( 14 )
Validity ( 14 )
Usability Metrics ( 13 )
SUPRQ ( 12 )
Market Research ( 12 )
SUPR-Q ( 12 )
Reliability ( 11 )
Qualitative ( 11 )
Navigation ( 10 )
Heuristic Evaluation ( 8 )
Task Time ( 8 )
SEQ ( 8 )
UX Metrics ( 8 )
Research ( 7 )
Task Completion ( 7 )
Questionnaire ( 7 )
Confidence ( 6 )
Confidence Intervals ( 6 )
Mobile Usability Testing ( 6 )
Analytics ( 6 )
Mobile ( 6 )
Unmoderated Research ( 5 )
Visualizing Data ( 5 )
Six Sigma ( 5 )
Usability Problem ( 5 )
Credibility ( 4 )
UX Methods ( 4 )
Moderation ( 4 )
UX Maturity ( 4 )
Task Times ( 4 )
Key Driver ( 4 )
Quantitative ( 4 )
Loyalty ( 4 )
Expert Review ( 4 )
sliders ( 4 )
Lean UX ( 3 )
Customer Segmentation ( 3 )
Card Sorting ( 3 )
Summative ( 3 )
Usability Lab ( 3 )
TAM ( 3 )
ROI ( 3 )
PURE ( 3 )
Desirability ( 3 )
Voice Interaction ( 3 )
Task Metrics ( 3 )
Data ( 3 )
Focus Groups ( 2 )
Correlation ( 2 )
SUM ( 2 )
Excel ( 2 )
Findability ( 2 )
PhD ( 2 )
Errors ( 2 )
Remote Usability Testing ( 2 )
KLM ( 2 )
Salary Survey ( 2 )
Branding ( 2 )
Tree Testing ( 2 )
IA ( 2 )
Tasks ( 2 )
UX Salary Survey ( 2 )
A/B Testing ( 2 )
Personas ( 2 )
slider ( 2 )
Marketing ( 2 )
Sample Sizes ( 2 )
Prototype ( 2 )
LTR ( 2 )
Eye-Tracking ( 2 )
Variables ( 2 )
Sensitivity ( 2 )
Emoji scale ( 2 )
Cognitive Walkthrough ( 2 )
Formative ( 2 )
Star Scale ( 2 )
Carryover ( 1 )
Within-subjects ( 1 )
Visual Analog Scale ( 1 )
Desktop ( 1 )
Linear Numeric Scale ( 1 )
User-Centred Design ( 1 )
Cumulative Graphs ( 1 )
Task Randomization ( 1 )
Test Metrics ( 1 )
Quality ( 1 )
Margin of Error ( 1 )
Meeting software ( 1 )
Polarization ( 1 )
Likert ( 1 )
consumer software ( 1 )
b2b software ( 1 )
Design Thinking ( 1 )
Mean Opinion Scale ( 1 )
Latin Squares ( 1 )
Greco-Latin Squares ( 1 )
Research design ( 1 )
Information Architecture ( 1 )
Site Analytics ( 1 )
Randomization ( 1 )
Report ( 1 )
Single Ease Question ( 1 )
R ( 1 )
t-test ( 1 )
Bias ( 1 )
Contextual Inquiry ( 1 )
Problem Severity ( 1 )
History of usability ( 1 )
MOS ( 1 )
MOS-R ( 1 )
graphic scale ( 1 )
negative scale ( 1 )
Probability ( 1 )
Measure ( 1 )
Mobile Usability ( 1 )
coding ( 1 )
Anchoring ( 1 )
Formative testing ( 1 )
Certification ( 1 )
Top Task Analysis ( 1 )
True Intent ( 1 )
Visual Appeal ( 1 )
Design ( 1 )
Facilitation ( 1 )
User Testing ( 1 )
Effect Size ( 1 )
protoype ( 1 )
Unmoderated ( 1 )
Task Completin ( 1 )
Affinity ( 1 )
Crowdsourcing ( 1 )
Random ( 1 )
Think Aloud ( 1 )
Trust ( 1 )
Sample ( 1 )
Statistical Significance ( 1 )
Z-Score ( 1 )
Performance ( 1 )
Perceptions ( 1 )
Five ( 1 )
Persona ( 1 )
Metric ( 1 )
Conjoint Analysis ( 1 )
Regression Analysis ( 1 )
AttrakDiff2 ( 1 )
UEQ ( 1 )
Hedonic usability ( 1 )
Expectations ( 1 )
MUSiC ( 1 )
RITE ( 1 )
Competitive ( 1 )
CUE ( 1 )
meCUE2.0 ( 1 )
Microsoft Desirability Toolkit ( 1 )
Software ( 1 )
moderated ( 1 )
Moderating ( 1 )
Segmentation ( 1 )
NSAT ( 1 )
Customer effort ( 1 )
PSSUQ ( 1 )
Ordinal ( 1 )
CSUQ ( 1 )
Delight ( 1 )
ISO ( 1 )
A key aspect of usability is efficiency. Users should be able to complete tasks quickly. Efficiency is usually measured as time on task, one of the quintessential usability metrics. For transactional tasks done repeatedly, shaving a couple seconds off a time can mean saving minutes per day and hours per week for users (think Accounting, Contact Management and Order Entry). It can also mean saving

Read More

We already saw how a manageable sample of users can provide meaningful data for discrete-binary data like task completion. With continuous data like task times, the sample size can be even smaller. The continuous calculation is a bit more complicated and involves somewhat of a Catch-22. Most want to determine the sample size ahead of time, then perform the testing based on the results of

Read More