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

76

Strong Presence

Avg Prompt Score

64

across 16 prompts

Critical Issues

5

critical + high

Per-stage performance

🔍Discovery
1 brand-level
Cited100%1/1
Share of voice100%avg
Engine consensus—
Competitors0.0avg/cited
Sentiment—no data
⚖️Evaluation
7 brand-level
Cited100%7/7
Share of voice100%avg
Engine consensus—
Competitors0.7avg/cited
Sentiment—no data
🛡️Trust
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus—
Competitors0.0avg/cited
Sentiment—no data
💰Conversion
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus—
Competitors0.0avg/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

Veeva is highly likely to be cited by AI engines for life-sciences enterprise software shortlists because it has strong third-party review presence (notably G2) and credible analyst/enterprise signals (Gartner Peer Insights). The biggest AI-citation risk is evaluation-stage “brand vs competitor” and “pricing” queries: Veeva’s first-party comparison and pricing surfaces appear thin/uncrawlable for AI, so models may rely on third parties instead of citing veeva.com.

Based on audit of veeva.com · Jun 8, 2026

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