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

66

Strong Presence

Avg Prompt Score

99

across 348 prompts

AI Share of Voice

100%

across 340 prompts

Critical Issues

3

critical + high

Per-stage performance

🔍Discovery
239 category
Cited100%239/239
Share of voice100%avg
Engine consensus—
Competitors0.0avg/cited
Sentiment—no data
⚖️Evaluation
6 brand-level
Cited100%6/6
Share of voice100%avg
Engine consensus—
Competitors3.0avg/cited
Sentiment—no data
🛡️Trust
4 brand-level
Cited100%4/4
Share of voice100%avg
Engine consensus100%of engines
Competitors4.3avg/cited
Sentiment—no data
💰Conversion
2 brand-level
Cited100%2/2
Share of voice100%avg
Engine consensus100%of engines
Competitors3.5avg/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

Konghq.com is highly likely to be cited by AI engines for evaluation-stage queries because it has strong G2 traction (308 reviews, 4.4★) and first-party head-to-head comparison content (e.g., Kong vs MuleSoft, Kong vs Apigee). The single highest-ROI fix is to ensure crawlable, schema-rich conversion content for pricing/cost queries (public, SSR, and structured) so models can answer “How much does Kong cost?” directly from konghq.com rather than deferring to third parties.

Based on audit of konghq.com · Jun 7, 2026

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