Brand perception scores
How GetIntel's knowledge and recommendation scores are calculated from each engine's answers, with the points behind every result.
Brand perception produces two scores out of 100, each averaged across ChatGPT, Perplexity, Gemini and Google AI Overviews. It runs weekly, on Mondays.
Knowledge: does AI know you?
Section titled “Knowledge: does AI know you?”Each engine is asked directly what your product is. Its answer earns points:
| Result | Points |
|---|---|
| Accurately describes you | 100 |
| Partially accurate | 60 |
| Vague / unsure | 30 |
| Describes you wrong | 10 |
| Doesn’t know you | 0 |
Knowledge = the average across engines.
Recommendation: would AI recommend you?
Section titled “Recommendation: would AI recommend you?”Two turns per engine, blended 40% unprompted, 60% when asked.
Unprompted, a category question that never names you:
| Result | Points |
|---|---|
| Named you first | 100 |
| Named you | 65 |
| Named nobody | 40 |
| Named competitors, not you | 20 |
When asked, a follow-up that names you:
| Result | Points |
|---|---|
| Recommends you | 100 |
| Lists you as an option | 60 |
| No clear signal | 30 |
| Points to competitors | 20 |
| Speaks negatively | 0 |
Worked example. One engine names you (65) unprompted, then lists you as an option (60) when asked: 65 × 0.4 + 60 × 0.6 = 62. Recommendation = the average of these per-engine scores.
What moves them
Section titled “What moves them”- Knowledge improves when there is clear, consistent information about what you do across your site and the places AI reads, such as review sites and directories.
- Recommendation improves with the same levers as win rate: comparisons and reviews that show why you are the better choice.