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Growing AI search visibility for RealMedVision
I wrote research-led healthcare content built around what patients actually search for, then backed it with clean on-page SEO, internal linking, and proper medical authority signals.
Over 28 days, Google Search Console's AI features report showed 15.9K impressions across RealMedVision pages. The Awiqli insulin price page alone drove 12,789 of them.
The goal was simple: make the content genuinely useful, not just for regular Google, but for the AI-powered search results people are starting to rely on.
healthcareseogeogenerativeaiAI Engineer Medical WritingSearch Engine OptimizationAhrefsGoogle AnalyticsGoogle Search Console
The network for creativity
Join 1.25M professional creatives like you
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Seedance 2.5 is live!
I tested the exact same prompt twice and got two completely different results. It’s interesting to see how much the model can reinterpret the same idea depending on the generation.
Both have their strengths, but I definitely have a favorite.
Which one do you think is better, 1 or 2?
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I will go for option 2. Thank you.
AI Digital Marketing Strategy Architect Design (Draft 1 of Project)
AI Digital Marketing Strategy Architect application. Here is a high-level overview of the project's architecture and features:
Core Functionality: The application is a comprehensive 4-phase digital marketing strategy builder that helps users plan, build, and automate their growth engines. It's designed with an elegant, editorial-style interface featuring high-contrast typography and clean layouts.
Phase 1: Foundation: A module for establishing the product's niche, generating detailed target personas using AI, and setting up the foundational tech stack (analytics, landing pages, email lists).
Phase 2: Content Engine: Focuses on organic reach. It includes an interactive SEO topic cluster generator, a visual ContentMap graph to visualize pillar links, and an AI-powered repurposing studio that transforms a single article into multiple formats (threads, LinkedIn posts, video scripts).
Phase 3: Growth & Acceleration: Built for paid and organic scale. Features a paid ad testing matrix with AI "Scale vs Kill" rules, an organic social winner analysis simulator, and an Answer Engine Optimization (AEO) readiness auditor.
Phase 4: Scale & Automation: Focuses on workflow automation. Includes a visual Zapier/n8n pipeline builder, a live lead simulator for AI-personalized email drafting, and an A/B testing loop optimizer.
Technical Architecture: A full-stack application utilizing React on the frontend and an Express server on the backend to securely manage Gemini API calls. It persists project state locally, includes preset templates (like SaaS or E-commerce), and offers a robust export engine to generate Markdown or Raw JSON blueprints.
Clean work
