Pre-requisite
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Introduction
Researching Amazon products can be surprisingly time-consuming. Whether you’re comparing prices, analyzing reviews, scouting competitors, validating a niche, or gathering data for affiliate content, the process usually involves jumping between product pages, copying details into a spreadsheet, scanning ads, and trying to make sense of it all manually. But what if you could automate that entire workflow from scraping product information to generating meaningful insights and storing everything neatly for later use?
That’s exactly what this n8n workflow enables. By combining the scraping power of Decodo with the analytical capabilities of OpenAI, and finishing with automatic export into Google Sheets, this automation transforms a tedious research process into a streamlined, intelligent, repeatable system. With a single click, it collects data, interprets it, and organizes it so you can focus on decision-making instead of data gathering.
This post walks you through a powerful n8n workflow that automates the entire process:
- Scrapes Amazon product data using Decodo
- Extracts product details, ads, and metadata
- Uses OpenAI to analyze, summarize, and compare
- Generates structured insights based on a defined schema
- Automatically stores results into Google Sheets
What This Workflow Helps You Do
With a single Amazon product URL, the workflow performs a full analysis that can be used for:
- affiliate product write-ups
- competitive price evaluation
- marketplace product quality assessment
- SEO and content briefing
- product comparison frameworks
- sourcing and dropshipping decisions
- market positioning validation
Instead of digging through listings, reviews, ads, and price patterns yourself, the automation collects the information, interprets it, and stores it in a usable format for you.
Scraping the Product Page with Decodo
The workflow starts by triggering manually and feeding in an Amazon product link.
Decodo then fetches the information that would normally require:
- scrolling
- expanding sections
- parsing ad placements
- checking pricing variations
- identifying ASIN clusters
It extracts:
- product title
- pricing and discounts
- review counts and rating values
- images and product identifiers
- related ads and sponsored placements
Because Decodo handles rendering and dynamic content, you avoid the headaches of browser automation and blocked scrapers.
Extracting Relevant Data
Once the raw scrape is complete, the workflow filters and separates useful information into focused feeds. It pulls out:
- product details
- advertisement listings
- structured attributes
- customer review signals
This ensures that the AI components receive clean data, rather than unfiltered bulk HTML or nested response blobs.
AI-Powered Multi-Stage Analysis
This workflow does more than summarize it performs three different forms of AI evaluation in parallel.
Descriptive Product Summary
This creates a clear narrative overview, useful for:
- product descriptions
- editorial copy
- feature highlights
Competitive Positioning Analysis
This identifies:
- strengths and weaknesses
- pricing stance in the marketplace
- differentiating characteristics
- how it compares to similar items
Structured Product Insight Engine
This part is especially compelling the workflow uses a strict JSON schema to extract measurable insights, such as:
- how many items appear in the listing results
- how many ASINs repeat
- average and minimum pricing
- review averages
- best value item
- most reviewed item
- pricing spread
- Prime eligibility ratios
- metadata about product types and listing sources
- recommended actions like pricing strategy or listing improvement
Because the output follows a schema, it can:
- be charted
- be compared
- feed dashboards
- populate reports
- train future automations
No guesswork. No free-form text blobs.
Merging and Preparing the Output
Once all three AI results are generated, the workflow merges them into a single combined dataset. This makes the insights easier to store, reference, export, and use elsewhere.
Exporting Automatically to Google Sheets
The final stage pushes the combined result to a Google Sheet.
The workflow intelligently:
- appends a new row if the product is new
- updates an existing one if it already exists
- preserves historical data
- avoids duplication
This makes it ideal for:
- tracking multiple product URLs
- running daily or weekly data refreshes
- monitoring competitor listings over time
- building affiliate product catalogs
- preparing comparison content at scale
What You Need to Configure
Decodo Credentials
- Used to scrape Amazon product pages.
OpenAI Credentials
- Used to generate insights and analysis.
Google Sheets Connection
Used to store results in a spreadsheet.
Each can be added easily through the n8n Credentials panel.
Ways You Can Extend This Workflow
Here are some ideas to evolve it into a full product research engine:
- Process multiple URLs from a spreadsheet
- Scrape entire category pages automatically
- Generate comparison summaries between top items
- Alert when pricing drops or reviews spike
- Push insights into Notion, Airtable, or dashboards
- Auto-generate blog posts for affiliate websites
- Trigger on schedule instead of manually
Conclusion
This workflow shows how powerful automation becomes when scraping, AI analysis, and structured data handling are combined into a single seamless process. Instead of manually digging through Amazon listings, collecting product specs, comparing pricing, reviewing ratings, or trying to interpret positioning and value, you can now generate all of that insight instantly with one execution in n8n.
By leveraging Decodo for reliable product extraction, OpenAI for intelligent interpretation, and Google Sheets for clean storage and tracking, the workflow turns what used to be a repetitive research task into an effortless, repeatable system. It not only saves time but also produces richer, more consistent results than manual research ever could.
Whether you're an affiliate marketer, product researcher, content creator, marketplace seller, or someone exploring a new niche, this automation gives you a smarter and more scalable way to evaluate products and turn raw marketplace data into meaningful understanding.
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