Methodology
How BatSignal measures AI visibility
BatSignal turns crawl signals and ChatGPT answer evidence into a transparent four-pillar score.
Design principles
- Evidence over guesses. Scores come from fetch results and answer outcomes, not vibes.
- Neutral questions. Buyer-intent queries avoid branded stuffing so mention rates stay meaningful.
- Separate crawl from answers. Being crawlable is necessary but not sufficient for citations.
- No outcome guarantees. Measurement helps you improve; it does not promise rankings.
Four pillars and weights
| Pillar | Weight | What it measures |
|---|---|---|
| Crawl access | 25% | Whether major AI crawlers are allowed and can fetch your homepage |
| Content readiness | 20% | Readable HTML, title, meta description, Open Graph, JSON-LD, headings, llms.txt, sitemap |
| ChatGPT search | 50% | Mention and recommendation rates in live ChatGPT answers for buyer-intent questions |
| Training presence | 5% | Whether the domain appears in Common Crawl snapshots when checked |
How questions are scored
Each scan checks about 15 neutral buyer-intent questions for your website via ChatGPT with live web search. You can optionally add up to 10 custom questions. Recommendation rate is weighted more heavily than raw mention rate inside the ChatGPT pillar.
Grades
Composite scores map to letter grades: A (90+), B (80–89), C (70–79), D (60–69), F+ (50–59), and F (below 50). Score deltas compare against the previous completed scan for the same project when available.
FAQ
Why weight ChatGPT search highest?
Live ChatGPT answers are a direct signal of how often your brand appears in AI-mediated buyer journeys, so that pillar is weighted at 50% of the composite score.
Are prompts written to favor my brand?
No. BatSignal uses neutral buyer-intent questions so results reflect organic mention and recommendation rates rather than branded query stuffing.