Back to Catalog

AI blog generator for Shopify product listings: Using GPT-4o and Google Sheets

Kumar ShivamKumar Shivam
9155 views
2/3/2026
Official Page

🧠 AI Blog Generator for Shopify Products using GPT-4o

The AI Blog Generator is an advanced automation workflow powered by n8n, integrating GPT-4o and Google Sheets to generate SEO-rich blog articles for Shopify products. It automates the entire process β€” from pulling product data, analyzing images for nutritional information, to producing structured HTML content ready for publishing β€” with zero manual writing.


πŸ’‘ Key Advantages

  • πŸ”— Shopify Product Sync
    Automatically pulls product data (title, description, images, etc.) via Shopify API.

  • πŸ€– AI-Powered Nutrition Extraction
    Uses GPT-4o to intelligently analyze product images and extract nutritional information.

  • ✍️ SEO Blog Generation
    GPT-4o generates blog titles, meta descriptions, and complete articles using both product metadata and extracted nutritional info.

  • πŸ—‚οΈ Structured Content Output
    Produces well-formatted HTML with headers, bullet points, and nutrition tables for seamless Shopify blog integration.

  • πŸ“„ Google Sheets Integration
    Tracks blog creation, manages retries, and prevents duplicate publishing using a centralized Google Sheet.

  • πŸ“€ Shopify Blog API Integration
    Publishes the generated blog to Shopify using a two-step blog + article API call.


βš™οΈ How It Works

  1. Manual Trigger
    Initiate the process using a test trigger or a scheduler.

  2. Fetch Products from Shopify
    Retrieves all product details including descriptions and images.

  3. Extract Product Images
    Splits and processes each image individually.

  4. OCR + Nutrition AI
    GPT-4o reads nutrition facts from product images. Skips items without valid info.

  5. Check Existing Logs
    References a Google Sheet to avoid duplicates and determine retry status.

  6. AI Blog Generation
    Creates a blog with headings, bullet points, intro, and a nutrition table.

  7. Shopify Blog + Article Posting
    Uses the Shopify API to publish the blog and its content.

  8. Update Google Sheet
    Logs the blog URL, HTML content, errors, and status for future reference.


πŸ› οΈ Setup Steps

  • Shopify Node: Connects to your Shopify store and fetches product data.
  • Split Out Node: Divides product images for individual OCR processing.
  • OpenAI Node: Uses GPT-4o to extract nutrition data from images.
  • If Node: Filters for entries with valid nutrition information.
  • Edit Fields Node: Formats the product data for AI processing.
  • AI Agent Node: Generates SEO blog content.
  • Google Sheets Nodes: Reads and updates blog creation status.
  • HTTP Request Nodes: Posts the blog and article via Shopify’s API.

πŸ” Credentials Required

  • Shopify Access Token – For retrieving product data and posting blogs
  • OpenAI API Key – For GPT-4o-based AI generation and image processing
  • Google Sheets OAuth – For accessing the log sheet

πŸ‘€ Ideal For

  • Ecommerce teams looking to automate content for hundreds of products
  • Shopify store owners aiming to boost organic traffic through blogging
  • Marketing teams building scalable, AI-driven content workflows

πŸ’¬ Bonus Tip

The workflow is modular. You can easily extend it with internal linking, language translation, or even social media sharing β€” all within the same n8n flow.

AI Blog Generator for Shopify Product Listings using GPT-4o and Google Sheets

This n8n workflow automates the creation of engaging blog posts for your Shopify product listings. It leverages the power of GPT-4o to generate blog content based on product details, then publishes it directly to your Shopify store. The workflow also includes a conditional check to ensure that a blog post is only created if the AI successfully generates content.

What it does:

  1. Manual Trigger: The workflow is initiated manually, allowing you to control when new blog posts are generated.
  2. Generate Blog Content with AI: An AI Agent, powered by an OpenAI Chat Model (likely GPT-4o, given the directory name context), is used to generate blog post content. It utilizes a "Simple Memory" to maintain context during the generation process.
  3. Conditional Check: The workflow checks if the AI successfully generated blog content.
  4. Process Generated Content (if successful):
    • If content is generated, the "Edit Fields" (Set) node prepares the data for Shopify.
    • The "Split Out" node processes the content, likely separating different parts of the blog post (e.g., title, body).
    • The "Shopify" node then publishes the generated blog post to your Shopify store.
  5. No Operation (if unsuccessful): If the AI fails to generate content, the workflow proceeds to a "No Operation" node, effectively ending the process without creating a blog post.

Prerequisites/Requirements:

  • n8n Instance: A running instance of n8n.
  • OpenAI API Key: An API key for OpenAI (likely configured for GPT-4o). This will be used by the "OpenAI Chat Model" and "AI Agent" nodes.
  • Shopify Account: Access to a Shopify store with appropriate API credentials for publishing blog posts.
  • Google Sheets (Implied): While not explicitly present in the provided JSON, the directory name "4735-ai-blog-generator-for-shopify-product-listings-using-gpt-4o-and-google-sheets" strongly suggests that product listings are sourced from Google Sheets. You would likely need a Google Sheets credential configured in n8n for a complete implementation.

Setup/Usage:

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your OpenAI API Key credential for the "OpenAI Chat Model" and "AI Agent" nodes.
    • Configure your Shopify API credentials for the "Shopify" node.
    • (If applicable, based on directory name) Configure your Google Sheets credential if you plan to pull product data from a sheet.
  3. Customize AI Prompt: Adjust the prompt within the "AI Agent" node to guide the AI in generating blog posts tailored to your product listings and brand voice.
  4. Configure Shopify Node: Ensure the "Shopify" node is configured to publish to the correct blog and with the desired settings.
  5. Execute Workflow: Click "Execute workflow" on the "Manual Trigger" node to run the workflow. You will likely need to manually provide input (e.g., product details) to the AI Agent or integrate a preceding node to pull this data (e.g., from Google Sheets).

Related Templates

Generate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax

Spark your creativity instantly in any chatβ€”turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. πŸ“‹ What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing πŸ”§ Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation πŸ”‘ Required Credentials OpenAI API Setup Go to platform.openai.com β†’ API keys (sidebar) Click "Create new secret key" β†’ Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai β†’ Dashboard β†’ API Keys Generate a new API key β†’ Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) βš™οΈ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflowβ€”chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions

Daniel NkenchoBy Daniel Nkencho
601

Automate Dutch Public Procurement Data Collection with TenderNed

TenderNed Public Procurement What This Workflow Does This workflow automates the collection of public procurement data from TenderNed (the official Dutch tender platform). It: Fetches the latest tender publications from the TenderNed API Retrieves detailed information in both XML and JSON formats for each tender Parses and extracts key information like organization names, titles, descriptions, and reference numbers Filters results based on your custom criteria Stores the data in a database for easy querying and analysis Setup Instructions This template comes with sticky notes providing step-by-step instructions in Dutch and various query options you can customize. Prerequisites TenderNed API Access - Register at TenderNed for API credentials Configuration Steps Set up TenderNed credentials: Add HTTP Basic Auth credentials with your TenderNed API username and password Apply these credentials to the three HTTP Request nodes: "Tenderned Publicaties" "Haal XML Details" "Haal JSON Details" Customize filters: Modify the "Filter op ..." node to match your specific requirements Examples: specific organizations, contract values, regions, etc. How It Works Step 1: Trigger The workflow can be triggered either manually for testing or automatically on a daily schedule. Step 2: Fetch Publications Makes an API call to TenderNed to retrieve a list of recent publications (up to 100 per request). Step 3: Process & Split Extracts the tender array from the response and splits it into individual items for processing. Step 4: Fetch Details For each tender, the workflow makes two parallel API calls: XML endpoint - Retrieves the complete tender documentation in XML format JSON endpoint - Fetches metadata including reference numbers and keywords Step 5: Parse & Merge Parses the XML data and merges it with the JSON metadata and batch information into a single data structure. Step 6: Extract Fields Maps the raw API data to clean, structured fields including: Publication ID and date Organization name Tender title and description Reference numbers (kenmerk, TED number) Step 7: Filter Applies your custom filter criteria to focus on relevant tenders only. Step 8: Store Inserts the processed data into your database for storage and future analysis. Customization Tips Modify API Parameters In the "Tenderned Publicaties" node, you can adjust: offset: Starting position for pagination size: Number of results per request (max 100) Add query parameters for date ranges, status filters, etc. Add More Fields Extend the "Splits Alle Velden" node to extract additional fields from the XML/JSON data, such as: Contract value estimates Deadline dates CPV codes (procurement classification) Contact information Integrate Notifications Add a Slack, Email, or Discord node after the filter to get notified about new matching tenders. Incremental Updates Modify the workflow to only fetch new tenders by: Storing the last execution timestamp Adding date filters to the API query Only processing publications newer than the last run Troubleshooting No data returned? Verify your TenderNed API credentials are correct Check that you have setup youre filter proper Need help setting this up or interested in a complete tender analysis solution? Get in touch πŸ”— LinkedIn – Wessel Bulte

Wessel BulteBy Wessel Bulte
247

Auto-reply & create Linear tickets from Gmail with GPT-5, gotoHuman & human review

This workflow automatically classifies every new email from your linked mailbox, drafts a personalized reply, and creates Linear tickets for bugs or feature requests. It uses a human-in-the-loop with gotoHuman and continuously improves itself by learning from approved examples. How it works The workflow triggers on every new email from your linked mailbox. Self-learning Email Classifier: an AI model categorizes the email into defined categories (e.g., Bug Report, Feature Request, Sales Opportunity, etc.). It fetches previously approved classification examples from gotoHuman to refine decisions. Self-learning Email Writer: the AI drafts a reply to the email. It learns over time by using previously approved replies from gotoHuman, with per-classification context to tailor tone and style (e.g., different style for sales vs. bug reports). Human Review in gotoHuman: review the classification and the drafted reply. Drafts can be edited or retried. Approved values are used to train the self-learning agents. Send approved Reply: the approved response is sent as a reply to the email thread. Create ticket: if the classification is Bug or Feature Request, a ticket is created by another AI agent in Linear. Human Review in gotoHuman: How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Set up credentials for gotoHuman, OpenAI, your email provider (e.g. Gmail), and Linear. In gotoHuman, select and create the pre-built review template "Support email agent" or import the ID: 6fzuCJlFYJtlu9mGYcVT. Select this template in the gotoHuman node. In the "gotoHuman: Fetch approved examples" http nodes you need to add your formId. It is the ID of the review template that you just created/imported in gotoHuman. Requirements gotoHuman (human supervision, memory for self-learning) OpenAI (classification, drafting) Gmail or your preferred email provider (for email trigger+replies) Linear (ticketing) How to customize Expand or refine the categories used by the classifier. Update the prompt to reflect your own taxonomy. Filter fetched training data from gotoHuman by reviewer so the writer adapts to their personalized tone and preferences. Add more context to the AI email writer (calendar events, FAQs, product docs) to improve reply quality.

gotoHumanBy gotoHuman
353