How do I compare model-level results in GeoSnake?

Summary

How to compare performance across different AI models.

What this is and why it matters

Model-level reports help you see where your brand story travels well and where specific systems still describe the company weakly or inconsistently.

Keep the first setup narrow. GeoSnake becomes useful when one organization, one clear prompt set, and one repeatable review habit are in place before you expand coverage.

Recommended setup steps

• Compare the same prompt across multiple models.
• Look at presence, clarity, and recommendation quality together.
• Identify where your story is strongest or weakest.
• Use those patterns to guide follow-up content or training work.

Helpful tips

• Different models often reveal different brand gaps.
• Model-level review helps avoid false confidence from one strong result.
• Use consistency across models as a sign of stronger brand signal quality.

Possible issues and troubleshooting

• If the first setup feels noisy, reduce the scope instead of adding more prompts, markets, or competitors.
• If the dashboard looks empty, confirm that the first scan has finished and that the setup data was saved in the right organization.
• If adoption is weak, the problem is usually ownership or review cadence, not the fact that one more screen is missing.

What to do next

Once this step is stable, move straight to the next highest-value setup action. Momentum matters more than overbuilding the first pass.