How to Interpret Outputs

Signals, Not Scores

AnswrX outputs are signals, not performance metrics.

They describe:

• What AI systems currently present
• How consistent that presentation is
• Whether the pattern is stable or changing

They are not:

• Targets to optimize
• Scores to maximize
• Judgments of quality

Think of them as instrument readings, not grades.

Presence vs Absence

A signal may indicate:

• Present — your brand appears in relevant AI responses
• Missing — your brand does not appear
• Replaced — another entity appears where you previously did

Presence does not imply endorsement. Absence does not imply failure. It reflects what is being surfaced, not why.

Stability and Change

Not all change is meaningful.

AnswrX distinguishes between:

• Stable patterns — consistent over time
• Directional change — gradual strengthening or weakening
• Structural change — replacement or sustained disappearance

Single observations should not trigger action. Persistent patterns deserve attention.

Confidence Is a Property of the Signal

Every signal includes a confidence indicator.

Confidence reflects:

• Consistency across observations
• Stability over time
• Resistance to noise

High confidence means the signal is reliable. Low confidence means it should be monitored, not acted on. Confidence does not guarantee outcomes.

Risk Is Directional

When risk is shown, it represents:

• Increased likelihood of future change
• Based on observed historical patterns
• Not a prediction of a specific outcome

Risk answers “Should I pay attention?” It does not answer “What should I do?”

When to Check

AnswrX is not designed for constant monitoring.

It is best used to:

• Confirm stability
• Notice meaningful change
• Detect early erosion before lagging metrics move

Most users check periodically — and more closely when a change appears.

What AnswrX Will Never Tell You

• Recommend actions
• Suggest optimizations
• Attribute causation
• Replace human judgment

Interpretation remains your responsibility.