Data interpretation

Data interpretation starts with accepting variance.

AI responses are probabilistic, not deterministic. The same prompt can produce different answers even when nothing obvious changes.

This page explains how to interpret Genwolf data correctly and avoid common mistakes.

Why AI answers vary

Variation is normal.

phrase answers differently
mention brands in a different order
include or exclude marginal alternatives
cite different sources

This happens even with identical prompts. A single response is not a signal. A pattern across many responses is.

Trends matter more than absolutes

AI visibility should be interpreted directionally.

Focus on

  • upward or downward trends
  • changes relative to competitors
  • sustained gains or losses

Avoid overreacting to

  • single-run drops
  • small fluctuations
  • isolated prompt behavior

Relative visibility, not rankings

Genwolf does not expose rankings. AI answers are synthesized, not ordered lists.

whether your brand is included
how consistently it appears
how often competitors are preferred instead

Visibility is comparative, not absolute.

Sources explain the why

When visibility changes, sources often explain it.

newly cited domains
disappearing references
competitor-linked sources

Changes in sources usually precede gains in mentions or losses in visibility.

Common interpretation mistakes

treating single answers as truth
expecting stability at small sample sizes
assuming personalization effects
comparing unrelated prompts

Genwolf is a trend analysis tool, not a prediction engine.

Summary

Correct interpretation requires:

patience
normalization
relative thinking

Genwolf does not show you what happened once.

It shows you what keeps happening.

Documentation