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Generate AI ecommerce ads from product page and images with Claude and NanoBanana

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1. Workflow Overview

Generate AI Ecommerce Ads from Product Page and Images with Claude + NanoBanana Who is this for? This workflow is designed for ecommerce brands, marketers, agencies, and content teams who want t...

Best for

  • Content Creation automation workflows
  • Multimodal AI automation workflows
  • advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.markdown, n8n-nodes-base.aggregate, n8n-nodes-base.googledrive, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.lmchatanthropic, n8n-nodes-base.converttofile, n8n-nodes-base.set, n8n-nodes-base.extractfromfile

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Blumpo.

Original n8n.io source

1.1 Workflow description

Title
Generate AI ecommerce ads from product page and images with Claude and NanoBanana
Workflow name
Generate AI ecommerce ads from product page and images with Claude and NanoBanana

Generate AI Ecommerce Ads from Product Page and Images with Claude + NanoBanana

πŸ‘₯ Who is this for?

This workflow is designed for ecommerce brands, marketers, agencies, and content teams who want to generate static product ads faster from minimal product input.

It works especially well if you already have:

  • a product page URL
  • a logo
  • a product image
  • a need to turn that into a more structured ecommerce ad concept and final creative without building everything manually

🧩 What problem is this workflow solving? / Use case

Creating decent ecommerce ad creatives usually takes more than just prompting an image model.

You need to:

  • understand what the product actually is
  • extract the real use cases and customer needs
  • identify the most important product features and benefits
  • pull proof points, pricing, or offer context from the page
  • decide what visual direction makes sense for the product
  • then generate the final ad

This workflow solves that by automating the full process from product page + brand assets β†’ product insights β†’ ad concept β†’ generated image.

βš™οΈ What this workflow does

  • Collects a product URL, logo, and product image through a form
  • Analyzes the uploaded product image with Claude to understand what kind of product visual it is
  • Fetches the product page
  • Extracts and cleans product page text into one usable source
  • Builds structured product insights such as:
  • product name
  • product summary
  • product category
  • customer group
  • use cases
  • problems / needs
  • key product features
  • key benefits
  • proof / trust signals
  • offer / pricing
  • brand voice
  • Creates an ecommerce ad concept with Claude
  • Generates a static ecommerce ad creative with NanoBanana through OpenRouter
  • Converts the output into a file and uploads it to Google Drive

πŸ”Œ Setup

Connect your accounts:

  • Anthropic API for product insight extraction and ad concept generation
  • OpenRouter for image analysis and final image generation
  • Google Drive if you want to store the final output

Set your credentials in the respective nodes.

Make sure your form accepts:

  • .jpg
  • .png
  • .webp

If you do not want file export, disable the Upload file node.

πŸ› οΈ How to customize this workflow to your needs

Product analysis: Adjust the product insight prompt if you want different fields, such as ingredients, materials, objections, bundle logic, or audience segments.

Ad concept style: Edit the concept generation prompt to control tone, structure, and creative direction.

Visual output: Update the image generation prompt to make outputs more minimal, more premium, more editorial, more offer-led, or more product-shot focused.

Copy structure: Change the allowed copy structures if you want more offer-first, testimonial-first, or badge-led ecommerce ads.

Export flow: Replace Google Drive with your own storage, CMS, or downstream creative workflow.

πŸ” How it works

The workflow starts with a form submission containing a product URL, logo, and optional product image. The uploaded assets are processed first: the logo is prepared for generation, while the product image is analyzed to understand whether it is a product shot, packaging, illustration, object, or another kind of asset.

Next, the workflow fetches the product page and converts it into readable text. That content is then cleaned and turned into one usable source. Claude uses it to build structured product insights, including product summary, category, customer group, problems or needs, use cases, features, benefits, trust signals, pricing or offer, and brand voice.

Based on that, Claude creates one ecommerce ad concept with the copy structure, main text, optional supporting text, badges or microcopy, CTA, visual direction, layout direction, and style direction.

Finally, the concept and uploaded assets are passed to the image model to generate the final ecommerce ad creative, which can then be exported automatically.

βœ… Result

With this workflow, you go from product page + assets β†’ product insights β†’ ad concept β†’ generated ecommerce creative in one flow, with much less manual prompting and much more structure.

This is also close to the idea behind Blumpo: better ads come from better context first, not just better prompting.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Text extract

Type / Role
n8n-nodes-base.markdown - markdown
Config choices
Version 1

Block 2 - Aggregate1

Type / Role
n8n-nodes-base.aggregate - aggregate
Config choices
Version 1

Block 3 - Upload file

Type / Role
n8n-nodes-base.googleDrive - googleDrive
Config choices
Version 3

Block 4 - Structured Output Parser2

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 5 - Anthropic Chat Model1

Type / Role
@n8n/n8n-nodes-langchain.lmChatAnthropic - lmChatAnthropic
Config choices
Version 1.3

Block 6 - Convert to File2

Type / Role
n8n-nodes-base.convertToFile - convertToFile
Config choices
Version 1.1

Block 7 - set outputfile

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 8 - Anthropic Chat Model3

Type / Role
@n8n/n8n-nodes-langchain.lmChatAnthropic - lmChatAnthropic
Config choices
Version 1.3

Block 9 - Structured Output Parser3

Type / Role
@n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices
Version 1.3

Block 10 - User Asset Base64

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 11 - If

Type / Role
n8n-nodes-base.if - if
Config choices
Version 2.3

Block 12 - User Asset Base

Type / Role
n8n-nodes-base.extractFromFile - extractFromFile
Config choices
Version 1

Block 13 - Call Claude - Photo Evaluation

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 14 - Merge

Type / Role
n8n-nodes-base.merge - merge
Config choices
Version 3.2

Block 15 - Edit Fields

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.4

Block 16 - Sticky Note

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 17 - Sticky Note1

Type / Role
n8n-nodes-base.stickyNote - stickyNote
Config choices
Version 1

Block 18 - Form Input

Type / Role
n8n-nodes-base.formTrigger - formTrigger
Config choices
Version 2.2

Block 19 - Split Uploaded Files

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 20 - Fetch Homepage

Type / Role
n8n-nodes-base.httpRequest - httpRequest
Config choices
Version 4.2

Block 21 - Base inputs

Type / Role
n8n-nodes-base.set - set
Config choices
Version 3.3

Block 22 - Extract Website Copy

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.2

Block 23 - Clean text

Type / Role
n8n-nodes-base.code - code
Config choices
Version 2

Block 24 - Build Brand Insights

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2.2

Showing the first 24 of 29 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow Generate AI ecommerce ads from product page and images with Claude and NanoBanana
Complexity advanced
Nodes 29
Categories Content Creation, Multimodal AI
Author Blumpo
Published 30 Apr 2026

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/15405/15405.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

    Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.

  4. 4. Test with sample data

    Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.

  5. 5. Activate and monitor

    Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Frequently asked questions

What does Generate AI ecommerce ads from product page and images with Claude and NanoBanana do?

Generate AI Ecommerce Ads from Product Page and Images with Claude + NanoBanana Who is this for? This workflow is designed for ecommerce brands, marketers, agencies, and content teams who want t...

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Content Creation, Multimodal AI use case.