[unCited]
ProductCitation IndexAI InfluenceBlogBook
[unCited]/Aircall
ProductCitation IndexAI InfluenceBlogBook
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AEO Score

20

Limited Presence

Avg Prompt Score

22

across 370 prompts

AI Share of Voice

20%

across 358 prompts

Critical Issues

2

critical + high

Per-stage performance

🔍Discovery
238 category
Cited18%42/238
Share of voice18%avg
Engine consensus—
Competitors0.0avg/cited
Sentiment—no data
⚖️Evaluation
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data
🛡️Trust
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors5.0avg/cited
Sentiment—no data
💰Conversion
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors4.8avg/cited
Sentiment—no data

Cited rate · share of voice · engine consensus · sentiment, broken out by buyer-journey stage. Sentiment is the net positive−negative skew across engines that cited the brand at this stage.

Executive summary

Aircall is highly likely to be cited by AI engines for evaluation-stage queries because it has strong G2 review volume (1,573 reviews) and transparent, tiered pricing on its own domain. The biggest risk pattern is conversion-stage “pricing schema / machine-readable pricing” and structured evaluation Q&A: the pricing page is crawlable, but no SoftwareApplication/FAQPage/AggregateRating-style structured data was detected in the fetched pricing HTML, limiting rich AI citation.

Based on audit of aircall.io · Jun 8, 2026

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