Landing Page Analyzing Agent

Description

Use Cases
Analyze e-commerce product pages for conversion optimization, audit SaaS landing pages for signup improvements, or evaluate marketing campaign pages for better lead generation.

Good to know
At time of writing, Google Gemini API calls have usage costs. See Google AI Pricing for current rates.
The workflow analyzes publicly accessible pages only - pages behind login walls or with restricted access won't work.
Analysis quality depends on page content structure - heavily image-based pages may receive limited text-based recommendations.

How it works
User submits a landing page URL through the form trigger interface.
The HTTP Request node fetches the complete HTML content from the target landing page.
Content is converted from HTML to markdown format for cleaner AI processing and better text extraction.
Google Gemini 2.5 Flash analyzes the page using expert CRO knowledge and 2024 conversion best practices.
The AI generates specific, actionable recommendations based on actual page content rather than generic advice.
Information Extractor processes the analysis into 5 prioritized improvement tips with relevant visual indicators.
Results are delivered through a completion form showing concrete steps to improve conversion rates.

How to use
The form trigger is configured for direct URL submission but can be replaced with webhook triggers for integration into existing websites or apps.
Multiple pages can be analyzed sequentially, though each requires a separate workflow execution.
Recommendations focus on high-impact changes that don't require heavy development work.

Requirements
Google Gemini (PaLM) API account for AI-powered analysis
Publicly accessible landing pages for analysis
N8N instance with proper webhook configuration

Customizing this workflow
CRO analysis can be tailored for specific industries by modifying the AI system prompt - try focusing on e-commerce checkout flows, SaaS trial conversions, or local business lead capture forms.
Add competitive analysis by incorporating multiple URL inputs and comparative recommendations.