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AI Product Tools  /  MIF Explorer  /  Library  /  UX

Truth Layer

Truth Layer

The Truth Layer is the badge system that tells you how trustworthy, directional, or risky a measure is.

Why it matters: It helps teams separate meaningful signals from vanity, misuse, or AI distortion before they optimize the wrong thing.

Example: A metric can be Meaningful, Leading, or Vanity Risk.

KPI UX MeaningfulLaggingMisused

Cart Abandonment Rate

The percentage of users who add items to a cart but do not complete the purchase.

Category: Conversion
Measurement class: KPI

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.

Frequency: Weekly
Back to library

Evaluation method

(1 - purchases / cart_creations) × 100

Signal type

lagging

What it is best for

Optimizing e-commerce checkout flows

What it tells you +

The gap between purchase intent and purchase completion. Reveals checkout friction.

What it does not tell you +

Distinguish between users who abandoned due to friction versus those who were just browsing.

When to use it +
  • Optimizing e-commerce checkout flows
  • Evaluating the impact of shipping, pricing, or payment changes
When not to use it +
  • For non-e-commerce products
  • Without distinguishing abandonment reasons (price, shipping, friction, comparison shopping)
How leaders misuse it +
  • Treating 70% abandonment as alarming when the industry average is 65-75%
  • Attributing all abandonment to UX problems when pricing or shipping are the real cause
Anti-patterns +
  • Adding urgency dark patterns to reduce abandonment at the cost of trust
Companion entries +

This entry is stronger when paired with:

Conversion Rate Conversion Funnel Drop-off Rate Conversion
Instrumentation or evaluation guidance +

Industry average is 65-75%. Track per step of checkout for actionable diagnostics.

Sample events

cart_created, checkout_started, purchase_completed
Examples +

An e-commerce site has 73% cart abandonment. Exit survey reveals 45% cite unexpected shipping costs. Displaying shipping estimates on the product page reduces abandonment to 64%.

Suggested decisions +
  • If above industry average (75%), focus on checkout UX, unexpected costs, and payment options
  • Add exit-intent surveys to capture abandonment reasons qualitatively