Glossaries
Self Reported Metric
What is a Self-Reported Metric in User Research?
A self-reported metric in user research is a measurement or data point that is directly provided by users about their own experiences, behaviors, or opinions, typically through surveys, interviews, or feedback forms.
Synonyms: User-reported data, Self-assessment metrics, Subjective user metrics, User feedback metrics
Why Self-Reported Metrics are Important in User Research
Self-reported metrics play a crucial role in user research by providing direct insights into users' thoughts, feelings, and experiences. These metrics allow researchers to gather subjective data that may not be observable through other means, helping to paint a more comprehensive picture of user behavior and preferences.
How Self-Reported Metrics are Used in User Research
Researchers employ self-reported metrics in various ways:
- Surveys: Collecting quantitative and qualitative data on user satisfaction, preferences, and demographics.
- Interviews: Gathering in-depth insights on user experiences and motivations.
- Feedback forms: Obtaining quick responses on specific features or interactions.
- Diary studies: Capturing user experiences over time in their natural context.
Examples of Self-Reported Metrics in User Research
- Net Promoter Score (NPS): Measures customer loyalty and satisfaction.
- System Usability Scale (SUS): Assesses the perceived usability of a product or service.
- Customer Effort Score (CES): Evaluates the ease of completing a task or interaction.
- Likert scale responses: Gather opinions on various aspects of a product or experience.
Frequently Asked Questions about Self-Reported Metrics
- What are the advantages of self-reported metrics?: Self-reported metrics provide direct user feedback, are cost-effective to collect, and can reveal insights about user attitudes and perceptions.
- Are there any limitations to self-reported metrics?: Yes, they can be subject to biases such as social desirability bias or recall bias, and may not always accurately reflect actual behavior.
- How can researchers improve the accuracy of self-reported metrics?: By using well-designed questions, combining self-reported data with observational methods, and employing techniques to minimize bias.
- When should self-reported metrics be used in user research?: They are particularly useful when gathering subjective data, exploring user attitudes, or when direct observation is not possible or practical.