AI Native Flow Case Study #9 – n8n – Automated Workflow for Social Media Link Extraction

🔑 AccessLevel
Free

🔗 Source
https://n8n.io/workflows/2315-autonomous-ai-crawler/

🛠️ Testing Environment
Self-hosted; n8n version: 1.66.0

🧠 LLMs Used
gpt-4o-2024-11-20🤖 ModelType
Text-Only;

✅ IsFunctional
Yes

🚀 Performance Rating
Needs Improvement

🌟 Expected Behaviour
When creating a social media marketing strategy for a client, a key step is analyzing the social media activity of target businesses. Currently, this process is manual—employees visit websites, find social media links, and record them individually. This is time-consuming, labor-intensive, and prone to errors. The solution is an automated workflow that can quickly and accurately extract social media links, improving efficiency and reducing mistakes.

📝 Actual Behaviour
After testing, this solution is not recommended due to its cumbersome process and the inability to accurately parse data at times. However, through this logic, we can learn how to analyze and parse web content, as well as how to invoke internal nodes within workflows. Therefore, it is more suitable for use as a teaching process.

📊 Evaluation

AI Native: (6/10) The workflow shows potential with automation and database integration but lacks the precision, scalability, and seamlessness expected in a robust AI Native system.

🔍 Workflow Breakdown
1️⃣ Retrieve Target URLs: Manually input specific target URLs or fetch them automatically from an integrated Supabase database.
2️⃣ Extract Page Text: Use the Text Tool to retrieve all visible text content from the webpage for further analysis and processing.
3️⃣ Extract Links: Utilize the URLs Tool to identify and collect all potential links from the webpage, including social media profiles and other relevant resources.
4️⃣ Store Data: Save the extracted text and link data in a structured format within a custom Supabase database, ensuring easy access for future queries and analysis.

Statement: Evaluation results are generated by AI, lack of data support, reference learning only.

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