n8nworkflows.xyz/workflows/Prioritize Amazon competitor gaps using Bright Data and Google Sheets-13588/readme-13588.md

Prioritize Amazon competitor gaps using Bright Data and Google Sheets

https://n8nworkflows.xyz/workflows/prioritize-amazon-competitor-gaps-using-bright-data-and-google-sheets-13588

Prioritize Amazon competitor gaps using Bright Data and Google Sheets

This document provides a technical breakdown and reconstruction guide for the Competitive Assortment & Pricing Gap Intelligence Engine workflow in n8n.

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1. Workflow Overview

This workflow automates the process of competitive benchmarking for Amazon products. It scrapes product data, uses AI to identify market gaps (missing variants, pricing weaknesses, and bundle opportunities), scores these opportunities based on potential impact, and logs the results into a structured Google Sheets dashboard.

Logical Blocks:

1. Input & Configuration: Defines the target Amazon URL.
2. Data Collection & Normalization: Extracts raw data via Bright Data and cleans it into a standard format.
3. AI Intelligence Engine: Uses an LLM to analyze the product against competitive standards and output structured JSON.
4. Gap Scoring & Prioritization: Applies logic to quantify the "opportunity" level of the detected gaps.
5. Multi-Channel Reporting: Routes data to specific Google Sheet tabs based on priority and category (Missing Variants, Bundles, or Pricing Gaps).

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2. Block-by-Block Analysis

2.1 Input & Configuration

Initializes the process by defining which product needs to be analyzed.

• Nodes Involved: Run Competitive Analysis, Set Target URL.
• Node Details:
  • Run Competitive Analysis: Manual trigger for on-demand execution.
  • Set Target URL: Defines a string variable URL containing the full Amazon product link.

2.2 Data Collection & Normalization

Fetches live data and prepares it for AI processing.

• Nodes Involved: Scrape Product Data (Bright Data), Normalize & Structure Product Data, Format Scraping Error Log, Log Scraping Failure.
• Node Details:
  • Scrape Product Data (Bright Data): Uses the Amazon Products dataset (gd_l7q7dkf244hwjntr0). It is configured to "Continue on Fail" to allow the Error Log branch to capture timeouts or blocking issues.
  • Normalize & Structure Product Data: A JavaScript Code node that extracts brand, price (buybox, final, or initial), variations (ASIN, price, currency), and categories.
  • Error Branch: If scraping fails, the workflow captures the error message and logs it to a dedicated "log error" sheet.

2.3 AI Intelligence Engine

Analyzes the cleaned data to find strategic opportunities.

• Nodes Involved: AI Competitive Gap Analyzer, Competitive Gap Analyzer (OpenRouter), Validate AI Structured Output.
• Node Details:
  • AI Competitive Gap Analyzer (Agent): Orchestrates the prompt. It asks the AI to cluster the product, detect missing variants, and suggest bundle opportunities.
  • Competitive Gap Analyzer (LM Chat): The model provider (OpenRouter) used by the agent.
  • Validate AI Structured Output: A LangChain parser ensuring the AI response strictly follows a JSON schema with keys: productName, competitor, cluster, missingVariants, bundleOpportunity, and positioningGap.

2.4 Gap Scoring & Prioritization

Evaluates the AI's findings to determine the urgency of the opportunity.

• Nodes Involved: Score Pricing & Assortment Gap, Is High-Priority Opportunity?.
• Node Details:
  • Score Pricing & Assortment Gap: A Code node that calculates a pricingGapScore.
    • +40 points for "Premium" or "High" positioning gaps.
    • +30 points if missing variants are identified.
    • +30 points if bundle opportunities are found.
  • Is High-Priority Opportunity?: An IF node that checks if the pricingGapScore is greater than 50.

2.5 Multi-Channel Reporting

Logs insights into different sheets for stakeholders.

• Nodes Involved: Format High-Priority Record, Log Missing Variants, Log Bundle Opportunities, Log Pricing & Positioning Gaps, Format Standard Opportunity Record, Log All Standard Opportunities.
• Node Details:
  • Format Nodes: Standardize field names (e.g., adding a "Priority" label) before sending to Google Sheets.
  • Google Sheets Nodes: Use the Append operation. High-priority items are split across three specialized tabs; lower-priority items go to a general "Standard Opportunities" log.

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3. Summary Table

Node Name	Node Type	Functional Role	Input Node(s)	Output Node(s)	Sticky Note
Run Competitive Analysis	Manual Trigger	Entry point	None	Set Target URL	Initial configuration block...
Set Target URL	Set	Config	Run Competitive Analysis	Scrape Product Data	Initial configuration block...
Scrape Product Data (Bright Data)	Bright Data	Data Retrieval	Set Target URL	Normalize Data / Error Log	Scrapes and prepares competitor product data...
Normalize & Structure Product Data	Code (JS)	Formatting	Scrape Product Data	AI Gap Analyzer	Scrapes and prepares competitor product data...
AI Competitive Gap Analyzer	AI Agent	Analysis	Normalize Data	Score Pricing & Assortment	Analyzes competitor products using AI...
Validate AI Structured Output	Output Parser	Schema Control	None	AI Gap Analyzer	Analyzes competitor products using AI...
Competitive Gap Analyzer	OpenRouter	LLM Provider	None	AI Gap Analyzer	Analyzes competitor products using AI...
Score Pricing & Assortment Gap	Code (JS)	Scoring	AI Gap Analyzer	Is High-Priority?	Analyzes competitor products using AI...
Is High-Priority Opportunity?	IF	Routing	Score Pricing	Format High / Format Standard	Filters prioritized opportunities...
Format High-Priority Record	Set	Formatting	Is High-Priority?	Log Variants / Bundles / Pricing	Formats and logs high-priority competitive...
Log Missing Variants	Google Sheets	Reporting	Format High-Priority	None	Formats and logs high-priority competitive...
Log Bundle Opportunities	Google Sheets	Reporting	Format High-Priority	None	Formats and logs high-priority competitive...
Log Pricing & Positioning Gaps	Google Sheets	Reporting	Format High-Priority	None	Formats and logs high-priority competitive...
Format Standard Opportunity Record	Set	Formatting	Is High-Priority?	Log All Standard	Filters prioritized opportunities...
Log All Standard Opportunities	Google Sheets	Reporting	Format Standard	None	Filters prioritized opportunities...
Format Scraping Error Log	Set	Error Handling	Scrape Product Data	Log Scraping Failure	Scrapes and prepares competitor product data...
Log Scraping Failure	Google Sheets	Error Handling	Format Scraping Error	None	Scrapes and prepares competitor product data...

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4. Reproducing the Workflow from Scratch

1. Preparation:

   • Create a Google Sheet with 5 tabs: Missing Variants, Bundle Opportunities, Pricing & Positioning Gaps, All Standard Opportunities, and log error.
   • Add headers to Row 1 as specified in Section 5.

2. Configuration:

   • Add a Manual Trigger node.
   • Connect a Set node named "Set Target URL". Create a string value named URL with an Amazon product link.

3. Bright Data Integration:

   • Add the Bright Data node. Connect your Bright Data credentials.
   • Set Resource to "Web Scrapper" and select the "Amazon products" dataset.
   • In the URL field, use the expression {{ $json.URL }}.
   • Set "On Error" to Continue (populate error output).

4. JS Normalization:

   • Add a Code node. Map the raw Bright Data output to a clean JSON object containing category, competitor, productName, price, and variants.

5. AI Setup:

   • Add an AI Agent node.
   • Connect an LM Chat Model (OpenRouter) and an Output Parser (Structured).
   • In the Parser, define the JSON schema (Properties: productName, competitor, cluster, missingVariants [array], bundleOpportunity, positioningGap).
   • In the Agent's "Text" prompt, pass the product data and instruct the AI to respond only in the defined JSON format.

6. Scoring Logic:

   • Add a Code node. Create a variable score. Use logic to increment score based on the length of the missingVariants array and keywords in positioningGap.

7. Routing & Logging:

   • Add an IF node: {{ $json.pricingGapScore }} > 50.
   • True Branch: Use a Set node to add the "High" priority label, then connect three Google Sheets nodes (Append) for the specific tabs.
   • False Branch: Use a Set node to add the "Moderate/low" label, then connect one Google Sheets node for the "All Standard Opportunities" tab.

8. Error Handling:

   • Connect the error output of the Bright Data node to a Set node that captures errorMessage and status, then log it to the "log error" sheet.

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5. General Notes & Resources

Note Content	Context or Link
Credential: Bright Data	Required for Amazon web scraping. brightdata.com
Credential: OpenRouter	Required for AI classification. openrouter.ai
Credential: Google Sheets OAuth	Required for dashboard logging.
Sheet Setup: Missing Variants	Category, Competitor, Product, Missing Variants, Priority
Sheet Setup: Bundle Opportunities	category, product, recommendedVariants, bundleOpportunity, priority
Sheet Setup: Pricing Gaps	category, competitor, product, price, pricingGapScore, positioningGap
Sheet Setup: Standard Ops	productName, competitor, cluster, missingVariants, bundleOpportunity, positioningGap, pricingGapScore, Priority
Sheet Setup: Error Log	error, errorSource, errorMessage, status