HttpRequest Automate

Target Audience

• Marketing Professionals: Those looking to enhance their LinkedIn presence and engagement through automated contributions.
• Content Creators: Individuals who want to generate unique insights and advice for various topics in their industry.
• Social Media Managers: Professionals managing multiple accounts who need to streamline content sharing on platforms like LinkedIn.
• Small Business Owners: Entrepreneurs seeking to maintain a consistent online presence without dedicating excessive time to content creation.

Problem Solved

This workflow addresses the challenge of consistently engaging with LinkedIn content. It automates the process of:

• Finding Relevant Articles: Automatically searches for LinkedIn advice articles based on specific topics.
• Extracting Insights: Pulls valuable information from articles, including titles and contributions from other users.
• Generating Unique Contributions: Uses AI to create personalized advice for each topic, ensuring that the contributions are unique and engaging.
• Posting Efficiently: Shares the generated contributions seamlessly to both Slack and a NocoDB database, saving time and enhancing visibility.

Workflow Steps

1. Scheduled Trigger: The workflow is set to run every Monday at 08:00 AM, ensuring regular updates.
2. Set Topic: A specific topic (e.g., Paid Advertising) is defined for the Google search.
3. Google Search: An HTTP request is made to retrieve articles related to the set topic from LinkedIn.
4. Extract Links: A code node extracts all relevant article links from the search results using a regex pattern.
5. Split Links: The extracted links are split into individual items for further processing.
6. Merge Unique Results: Merges the links to ensure only unique URLs are processed.
7. Fetch Article Content: For each unique article link, an HTTP request retrieves the HTML content.
8. HTML Extraction: Relevant information (title, topics, contributions) is extracted from the HTML content.
9. AI Contribution Generation: The extracted content is sent to an AI model to generate unique contributions for each topic.
10. Post to Slack: The AI-generated contributions are posted to a designated Slack channel for team visibility.
11. Store in NocoDB: The contributions, along with article details, are stored in a NocoDB database for future reference.