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

74

Strong Presence

Avg Prompt Score

84

across 486 prompts

AI Share of Voice

85%

across 462 prompts

Category Visibility

#3

in Observability & APM · of 44

Critical Issues

3

critical + high

Per-stage performance

🔍Discovery
316 category
Cited95%301/316
Share of voice88%avg
Engine consensus67%of engines
Competitors5.2avg/cited
Sentiment—no data
⚖️Evaluation
13 brand-level
Cited77%10/13
Share of voice77%avg
Engine consensus100%of engines
Competitors1.2avg/cited
Sentiment—no data
🛡️Trust
9 brand-level
Cited78%7/9
Share of voice78%avg
Engine consensus100%of engines
Competitors2.3avg/cited
Sentiment—no data
💰Conversion
8 brand-level
Cited50%4/8
Share of voice50%avg
Engine consensus100%of engines
Competitors1.8avg/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 Dynatrace is visible in

1
  • Observability & APM3 of 44→

Executive summary

Dynatrace is highly likely to be cited by AI engines for evaluation-stage prompts like "How does Dynatrace compare to Datadog?" and "How does Dynatrace compare to New Relic?" because it has first-party comparison pages and publicly crawlable pricing/rate-card content. The single highest-ROI fix is to strengthen Structured Data (SoftwareApplication + FAQPage) and Technical AEO crawlability signals (llms.txt/robots.txt verification) so AI engines can reliably extract product/pricing facts for "How much does Dynatrace cost?" and "What is the best observability platform software for cloud-native application performance monitoring (APM)?".

Based on audit of dynatrace.com · Apr 2, 2026

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