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AI Product Tools / MIF Explorer / Library
Explore the framework
38 curated entries spanning KPIs, governance metrics, value metrics, enablement signals, capability growth, maturity indicators, and AI-aware signals.
Measurement class
Measurement Class
A measurement class tells you what kind of measure something is, not just what topic it covers.
Why it matters: It stops teams from building a stack full of only KPIs while ignoring value, governance, or AI signals.
Example: Governance Metric and AI Signal are two different measurement classes.
Domain
Category
Usability
Task Success Rate
MeaningfulLaggingAI-Sensitive
The percentage of users who complete a defined task without critical errors.
Evaluating whether a redesign improved core workflows
Usability
Time on Task
MeaningfulLeadingAI-Sensitive
The time it takes a user to complete a specific task from start to finish.
Measuring efficiency improvements after a redesign
Usability
Error Rate
MeaningfulLeading
The percentage of user actions that result in an error, mistake, or unintended outcome.
Identifying specific UI elements that cause confusion
Usability
System Usability Scale (SUS)
MeaningfulLagging
A standardized 10-question survey that produces a composite usability score from 0 to 100.
Benchmarking perceived usability over time
Adoption
Activation Rate
MeaningfulLeading
The percentage of new users who complete a key action that signals they have found initial value in the product.
Evaluating onboarding effectiveness
Adoption
Feature Adoption Rate
DirectionalLeadingAI-Sensitive
The percentage of active users who use a specific feature within a given time period.
Evaluating feature launch success
Adoption
Time to First Value
MeaningfulLeading
The time from signup to the moment a user experiences the product’s core value for the first time.
Optimizing onboarding flows
Adoption
Onboarding Completion Rate
DirectionalLeadingVanity Risk
The percentage of new users who complete all required onboarding steps.
Identifying which onboarding steps cause the most drop-off
Engagement
DAU/WAU Ratio
DirectionalLeadingAI-Sensitive
The ratio of daily active users to weekly active users, indicating how many days per week the average user returns.
Understanding how embedded the product is in users’ workflows
Engagement
Average Session Duration
DirectionalVanity RiskAI-Sensitive
The average time users spend in a single session.
Content and media products where longer time indicates consumption
Engagement
Depth of Use
DirectionalLeading
The number of distinct features or meaningful actions a user engages with in a session or time period.
Understanding whether users are discovering the full value of the product
Engagement
Return Visit Rate
MeaningfulLeading
The percentage of users who return to the product within a defined time window after their first visit.
Early indicator of product-market fit
Retention
Day 7 Retention
MeaningfulLeading
The percentage of users who return to the product on day 7 after their first use.
Predicting long-term retention from early user behavior
Retention
Day 30 Retention
MeaningfulLagging
The percentage of users who return to the product on day 30 after their first use.
Evaluating product-market fit
Retention
Churn Rate
MeaningfulLagging
The percentage of users or customers who stop using the product within a given time period.
Measuring overall product health
Retention
Feature Retention
MeaningfulLeading
The percentage of users who continue using a specific feature over time after first trying it.
Evaluating whether a new feature is delivering sustained value
Conversion
Conversion Rate
MeaningfulLagging
The percentage of users who complete a desired business action, such as purchasing, subscribing, or requesting a demo.
Measuring funnel effectiveness
Conversion
Funnel Drop-off Rate
MeaningfulLeading
The percentage of users who leave a multi-step process at each specific step.
Diagnosing conversion bottlenecks
Conversion
Cart Abandonment Rate
MeaningfulLaggingMisused
The percentage of users who add items to a cart but do not complete the purchase.
Optimizing e-commerce checkout flows
Conversion
Free-to-Paid Conversion Rate
MeaningfulLagging
The percentage of free or trial users who convert to a paid plan.
Evaluating freemium or trial model effectiveness
Trust
Net Promoter Score (NPS)
DirectionalLaggingVanity Risk
A survey-based score measuring how likely users are to recommend the product, calculated as the difference between promoters and detractors.
Tracking overall sentiment trends over time
Trust
Customer Satisfaction (CSAT)
MeaningfulLagging
A survey-based score measuring satisfaction with a specific interaction, feature, or experience, typically on a 1-5 or 1-7 scale.
Measuring satisfaction with specific features or support interactions
Trust
Customer Effort Score (CES)
MeaningfulLeading
A survey-based score measuring how much effort a user had to exert to complete a task or interaction.
Measuring effort reduction after UX improvements
Trust
Support Ticket Volume
DirectionalLagging
The number of support tickets or help requests submitted by users in a given period.
Identifying features that cause the most confusion
AI Quality
AI Task Completion Rate
MeaningfulLaggingAI-Sensitive
The percentage of tasks where AI assistance leads to successful completion.
Evaluating whether AI features are effective
AI Quality
AI Suggestion Acceptance Rate
DirectionalLeadingAI-Sensitive
The percentage of AI-generated suggestions that users accept and apply.
Evaluating AI suggestion quality
AI Quality
User Override Rate
MeaningfulLeadingAI-Sensitive
The percentage of AI outputs that users manually modify, correct, or override after initial acceptance.
Evaluating AI output quality and appropriateness
AI Quality
AI Confidence Calibration
MeaningfulLeadingAI-Sensitive
How well the AI’s stated confidence level matches actual outcome accuracy. When the AI says it’s 80% confident, it should be correct 80% of the time.
Evaluating whether AI confidence indicators help or mislead users
Trust
Governance Decision Cycle Time
MeaningfulLeading
The time it takes for a governance question, exception, or standards decision to move from request to final answer.
Measuring design system governance health
Trust
Governance Exception Rate
DirectionalLeadingMisused
The percentage of work that requires an exception to the current system, standards, or operating model.
Evaluating design system governance fit
Conversion
Design System Cost Recovery Ratio
MeaningfulLagging
The ratio between measurable design system value recovered and the annual cost to run the system.
Justifying design system investment
Adoption
Design System Contribution Cycle Time
DirectionalLeading
The time it takes for a team-submitted pattern or improvement to move from proposal to usable system asset.
Measuring whether the design system is collaborative and scalable
Adoption
Engineering Sandbox Adoption Rate
DirectionalLeading
The percentage of eligible engineers actively using the sanctioned sandbox, starter kit, or implementation playground for system work.
Evaluating design system enablement investments
Engagement
Design-to-Code Learning Velocity
DirectionalLeading
The rate at which designers build practical implementation fluency and can apply code-aware knowledge in real workflow decisions.
Measuring hybrid talent development
Engagement
Cross-Training Application Rate
MeaningfulLeading
The percentage of cross-training moments that turn into applied behavior in real delivery work.
Measuring hybrid team growth
Trust
Leadership Measurement Alignment Score
DirectionalLeading
A structured score for how consistently leadership understands, repeats, and supports the current measurement narrative.
Selling a measurement system internally
Adoption
Internal UX Narrative Reuse Rate
DirectionalLeading
How often the approved UX, design system, or AI measurement narrative is reused by partners outside the core team.
Measuring internal buy-in for UX or design system strategy
Retention
AI Pilot-to-Scale Conversion Rate
MeaningfulLaggingAI-Sensitive
The percentage of AI pilots that move from limited experiment to sustained scaled use.
Evaluating AI strategy maturity