Glossaries
Synthetic Metric
What is a Synthetic Metric in User Research?
A synthetic metric in user research is a custom-created measurement that combines multiple data points or metrics to provide a more comprehensive view of user behavior, satisfaction, or performance.
Synonyms: Composite Metric, Derived Metric, Custom Metric, Aggregate Measure, Blended KPI
Why Synthetic Metrics are Important in User Research
Synthetic metrics play a crucial role in user research by providing a more holistic view of user experience. They allow researchers to:
- Combine multiple data points into a single, meaningful measure
- Create custom metrics tailored to specific research goals
- Simplify complex data sets for easier interpretation and decision-making
How Synthetic Metrics are Used in User Research
Researchers employ synthetic metrics in various ways:
- Performance Evaluation: Combining speed, accuracy, and user satisfaction scores to create an overall performance metric.
- User Engagement: Merging metrics like time spent, interaction frequency, and content consumption to measure engagement.
- Product Success: Integrating user adoption rates, retention, and feature usage to assess overall product success.
Examples of Synthetic Metrics in User Research
- User Success Score: Combines task completion rate, time on task, and user satisfaction rating.
- Engagement Index: Merges daily active users, session duration, and feature interaction frequency.
- Customer Health Score: Integrates customer support interactions, product usage, and renewal likelihood.
Frequently Asked Questions about Synthetic Metrics
- What's the difference between a synthetic metric and a regular metric?: A synthetic metric combines multiple regular metrics or data points into a single, more comprehensive measure.
- How do you create a synthetic metric?: To create a synthetic metric, identify the key components you want to measure, assign weights to each component, and combine them using a predetermined formula or algorithm.
- Are synthetic metrics always better than individual metrics?: Not necessarily. While synthetic metrics can provide a more comprehensive view, they may also obscure important details. It's often best to use them in conjunction with individual metrics for a balanced analysis.
- Can synthetic metrics be standardized across different products or companies?: While some synthetic metrics can be standardized, many are custom-created to address specific research goals or product characteristics, making direct comparisons challenging.
