Recommendation mode
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MIF
MIF stands for Measurement Intelligence Framework. It is a broader way to organize measurement so teams look beyond a few headline KPIs.
Why it matters: Modern product teams need to measure UX, AI quality, governance, value, enablement, and maturity together.
Example: A healthy stack might combine Task Success Rate, Design System Cost Recovery Ratio, and User Override Rate.
Full MIF mode is on. Recommendations can include KPIs alongside governance, value, enablement, capability, maturity, and AI-aware measures.
Step 1 of 6
What are you trying to improve?
This shapes which measurement classes and signals will actually help. We’ll recommend entries that answer the real decision in front of you.
Step 2 of 6
What kind of product is this?
Different product types have different baseline expectations and measurement strategies.
Step 3 of 6
What are you trying to prove or unlock?
This helps MIF Explorer move beyond classic KPIs and recommend the right measurement class for the job.
Step 4 of 6
What data do you have access to?
We’ll recommend KPIs you can act on with what you have. No point suggesting metrics you can’t measure yet.
Step 5 of 6
Are AI features involved?
AI changes what some metrics mean. If your product uses AI, we’ll flag KPIs where interpretation shifts.
Step 6 of 6
Who needs the answer?
This determines how we frame the output. A design team needs different depth than an executive summary.
Your recommended stack
Based on your answers
Here are the measurement entries most likely to give you the clearest signal.
1 Review the recommendations
Use the reasons to understand why each entry belongs in the stack.
2 Add the entries you want to keep
Save them to the stack so later pages can analyze the mix.
3 Run the Health Check next
See whether the saved stack is balanced enough for the decision in front of you.
