Description
This prompt instructs an AI to analyze customer-behavior heatmaps (click, scroll, hover, attention, or blended heatmaps) and convert them into clear insights about how users interact with a webpage or product interface. The AI must interpret what user behavior the heatmap represents, identify high-engagement vs low-engagement zones, detect anomalies such as mis-clicks or dead-zones, and recognize scroll-depth drop-offs or misguided attention patterns. It must translate these behaviors into meaningful explanations of user intent—such as confusion, friction, hesitation, or strong interest—while distinguishing real behavioral signals from noise.
The model must also explain how these behaviors affect usability, conversion, and business outcomes, identifying risks (e.g., missed CTAs, poor layout alignment, misleading affordances) and opportunities for improvement. The AI must then provide specific UX recommendations: adjusting hierarchy, moving content, improving CTA placement, simplifying layout, or clarifying interactions. All conclusions must be grounded in behavioral interpretation rather than color or visual appearance. The final output follows a structured format (context, patterns, interpretation, risks, recommendations) suitable for UX optimization or CRO work.



Education & Learning 
Business & Marketing 
Content Writing 
Coding & Development 

Productivity & Automation 







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