UX Terms Flashcards
What is Thematic Analysis?
Thematic analysis is a qualitative data analysis method that involves reading through a data set (such as transcripts from in depth interviews or focus groups), and identifying patterns in meaning across the data.
Qualitative Data
Consisting of observational findings that identify design features easy or hard to use
- Based on opinions & experiences
- Interviews & observations
- Subjective
- Open-ended questions
- To generate hypothesis or develop ideas
- Answers the “why”
Quantitative Data
In form of one or more metrics (such as task completion rates or task times) that reflect whether the tasks were easy to perform
- Based numbers
- Statistical analysis
- Objective
- Closed-ended questions
- To validate hypothesis
- Answers the “what, where, how, when, and who”
UX benchmarking
Evaluating a product or service’s experience by using UX metrics to gauge its relative performance against a meaningful standard.
Allows us to assess & demonstrate the value of design work.
Can be used to calculate ROI.
UX metric
Numerical data that tells us something about the UX.
Examples: • Average time to make a purchase • Numbers of clicks on a Submit button • Success rate for an application completion • Average
summative evaluations
User research describes how a complete design performs.
Quantitative methods are often used
Benchmarking studies are summative evaluations
summative - I finished my soup, plated it, goes in front of a food critic, writes review, that is a summative review. project is complete. thing that I was forming is done.
formative evaluations
User research informs how the design will evolve, during the design process
Qualitative methods are often used
formative - tasting soup, do I need to modify my approach? how am I doing?
Quantitative methods for benchmarking
Quant usability testing
Analytics
Surveys
Quantitative methods for formative evaluations
A/B testing Tree testing Desirability testing Eyetracking Quant usability testing w/ prototypes
Quantitative usability testing
Participants perform tasks with a design, while researchers collect metrics that describe their performance
analytics
An analytics tool collects metrics that describe how people use a product in real life
Example: MATOMO
surveys
Users respond to questions about what they do or think
happiness
How do our users feel?
Measures of user attitudes or perceptions
Popular metrics:
• Satisfaction rating = How satisfied the participant is with the product
- Ease-of-use = How easy to use the task or product seems to the participant
- Perceived usability = How usable the product seems to the participant
- Subjective success rate = Whether or not the participant thinks they were successful
- Confidence rating = How confident the participant is in their task completion
- Questionnaire scores = Set of questions resulting in a score; like NPS, SUS, SUPR-Q
engagement
How frequently, deeply, or intensely do they use the product?
Level of user involvement
Popular metrics:
• Frequency of return = How often people return (for example: visits per user per week)
- Average time spent = Across all users, how much time is spent in the product
- Average number of sessions per user = Average number of times users return to the product
- Feature usage = How much people use a feature (for example, number of photos uploaded per user per day)
- Conversion rate = What percentage of visitors complete an important goal action (like a purchase/registration)
- Sales, orders, & subscriptions = Count of completed goal actions
adoption
How are we attracting new users?
Initial uptake of a product, service or feature
Popular metrics:
• New accounts/visitors = New people signing up or registering
- Conversion rate = What percentage of visitors complete an important goal action (like a purchase/registration)
- Sales, orders, & subscriptions = Count of completed goal actions
retention
How are we keeping people around?
How existing users return, and remain active in the product
Popular metrics:
• Returning users = People coming back to the product
- Renewal rate = People renewing a subscription / Keeping the service
- Churn rate = Percentage rate at which people leave a group (for example, customers cancelling service or employees leaving a company)
- Repeat purchases = People making more purchases after their first purchase
task
Are users able to complete tasks easily and with little effort?
Efficiency, effectiveness, and errors
Popular metrics:
• Completion rate = Percentage of people who complete a process they started
- Success rate = Percentage of people who can successfully complete a task
- Average time on task = Average amount of time it takes when attempting a task
- Average time on page/view = Average amount of time spent on a page or screen
- Productivity = For example: Number of orders processed per day
- Error counts & error rate= Mistakes or slips users encounter in the product
- Help tickets & support contact (calls, chats, emails) = A measure of how much help customers need
SUPR-Q
Measures usability, appearance, trust
SUS
System Usability Scale; General usability assessment
SEQ
Single Ease Question; Post-task difficulty
UMUX-Lite
Usability Metric for User Experience
NPS
Net Promoter Score; Popular marketing metric
CSAT
Customer Satisfaction; Measures satisfaction w/ product/service
NASA-TLX
Task Load Index; Post-task workload
contextual inquiry
Contextual inquiry is a type of ethnographic field study that involves in-depth observation and interviews of a small sample of users to gain a robust understanding of work practices and behaviors. Its name describes exactly what makes it valuable — inquiry in context:
Context: The research takes place in the users’ natural environment as they conduct their activities the way they normally would. The context could be in their home, office, or somewhere else entirely.
Inquiry: The researcher watches the user as she performs her task and asks for information to understand how and why users do what they do.
