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

18

Limited Presence

Avg Prompt Score

44

across 590 prompts

AI Share of Voice

44%

across 590 prompts

Category Visibility

#16

in Product Experience · of 74

Critical Issues

3

critical + high

Shortlist Position

11/80

Niche · Forms Discovery

Per-stage performance

🔍Discovery
388 category
Cited61%235/388
Share of voice54%avg
Engine consensus47%of engines
Competitors6.4avg/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
Competitors5.0avg/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.

Categories Sprig is visible in

3
  • Product Experience16 of 74→
  • Forms & Surveys21 of 70→
  • Product Analytics26 of 55→

Your visibility gap

Sprig surfaces in 11/80 Forms discovery prompts. Claim this profile to see which 69 prompts you're missing and how to win them.

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Executive summary

Sprig is already well-positioned for AI citations in “forms/surveys for user research” discovery and evaluation queries, supported by strong G2 presence (105 reviews, 4.5/5). The biggest AI citation risk is that Sprig is missing (or not strongly indexed for) role-specific forms/surveys use cases like support ticket feedback, HR engagement, sales process surveys, and IT employee feedback—so it won’t reliably appear in those shortlist prompts. Highest-ROI fix: publish and index first-party, role-specific evaluation pages (e.g., “Sprig for Customer Support Feedback Surveys”, “Sprig for HR Engagement Surveys”) with FAQPage + SoftwareApplication schema and clear pricing/implementation blocks so AI can cite them for those exact gap queries.

Based on audit of sprig.com · May 7, 2026

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