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

14

Limited Presence

Avg Prompt Score

20

across 144 prompts

AI Share of Voice

20%

across 144 prompts

Critical Issues

5

critical + high

Per-stage performance

🔍Discovery
76 category
Cited30%23/76
Share of voice18%avg
Engine consensus36%of engines
Competitors17.1avg/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.

Categories ProcureDesk is visible in

1
  • Procurement & Sourcingnot yet measured→

Executive summary

ProcureDesk is already cited by AI engines for evaluation-style queries via strong third-party review signals (G2 ~40 reviews and Capterra 38 reviews, plus Gartner Peer Insights presence). The biggest AI citation risk is evaluation-stage “brand-aware comparison” and “pricing” queries: while first-party comparison pages exist (e.g., ProcureDesk vs Ramp / vs Precoro), the site’s structured-data/technical AEO signals (SoftwareApplication/FAQPage/robots/llms.txt) could not be verified via search, and pricing appears to be more marketing/CTA-heavy than clearly tiered. Highest-ROI fix: ensure crawlable, SSR-first pricing + add/verify SoftwareApplication + FAQPage schema on key evaluation pages so AI engines can reliably extract “what it is” and “how much it costs.”

Based on audit of procuredesk.com · May 8, 2026

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