n8n Competitor Intelligence Workflow: Multi-Engine SERP Monitoring with AI Summaries

Input search query → multi-engine SERP scraping → AI extraction of competitor insights and keywords → structured JSON output to Google Sheets

Who

Marketing analysts, SEO specialists, and growth teams with n8n experience who need to monitor search results at scale

You get

Automatically transform Google/Bing/Yandex/DuckDuckGo SERP data into structured competitor intelligence—domains, rankings, keyword opportunities, topic clusters, and content gaps—with optional export to Google Sheets

You need

n8n · google-sheets · thordata-scraper

Steps

1. Trigger and set search query

   Manually trigger the workflow in n8n (When clicking 'Execute workflow'), then replace the search_query in the 'Set the Input Fields' node with your target keyword, e.g.: 'Google Search for Top SEO strategies for e-commerce in 2025'.

2. AI Agent multi-engine SERP fetch

   The AI Agent node invokes four HTTP Request tools (Bing Search, Google Search, Yandex Search, DuckDuckGo Search) to call the Thordata Scraper API (https://scraperapi.thordata.com/request) with Bearer Auth, returning SERP results from each engine as JSON. The agent aggregates multi-engine results and passes them downstream for analysis.

   Execution prompt · Source text。AI Agent node text parameter (promptType=define)

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   ={{ $json.search_query }}

3. SEO Analyst structured competitor analysis

   The 'SEO Analyst' Information Extractor node uses GPT-4.1-mini to parse SERP results against a predefined JSON Schema, outputting: competitor domains, page titles, content types, ranking positions, keyword overlap rates, estimated traffic share, strengths and weaknesses, keyword opportunities, topic clusters, content gap analysis, SEO strength score (0–100), and an AI summary.

   Execution prompt · Source text。SEO Analyst node text parameter

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   =Analyze the following SERP results for competitor insights and keyword opportunities:\n\n {{ $json.output }}

   Execution prompt · Source text。SEO Analyst node options.systemPromptTemplate parameter

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   You are an SEO analyst. Extract primary keywords, competitor names, content tone, and summarize SEO strength from SERP data.

4. Content summarization

   The 'Summarize the content' LLM Chain node uses GPT-4.1-mini to generate a concise summary of the agent output, constrained by the Structured Output Parser into comprehensive_summary and abstract_summary fields.

   Execution prompt · Source text。Summarize the content node text parameter

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   =Summarize the following content  {{ $json.output }}.
   
   Output just the summary. Do not provide your own suggestions or recommendations

5. Keyword and topic analysis

   The 'Keyword and Topic Analysis' Information Extractor node uses GPT-4.1-mini to extract: primary and secondary keywords, keyword metrics (search volume, competition, difficulty, trend), focus topics, topic clusters (with search intent), SEO strength score, content gap summary, competitor insights, and an AI summary. Output is structured per JSON Schema.

   Execution prompt · Source text。Keyword and Topic Analysis node text parameter

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   =Perform Keyword and Topic Analysis of the following  {{ $json.output }}

6. Merge results and export to Google Sheets

   The Merge node combines outputs from the SEO Analyst, Summarize the content, and Keyword and Topic Analysis branches, then passes to the 'Append or update row in sheet' node which appends or updates rows in Google Sheets using autoMapInputData mode. Requires pre-configured googleSheetsOAuth2Api credentials and a target document/sheet.

You are setting up the n8n Competitor Intelligence workflow (template ID 10252). First confirm: 1) you have an n8n instance; 2) you have a Thordata Scraper API Key and have configured HTTP Bearer Auth credentials; 3) you have configured OpenAI API credentials; 4) if exporting to Google Sheets, you have OAuth2 credentials configured. After importing the template JSON, modify the search_query in the 'Set the Input Fields' node, verify the Thordata credential name matches across all 4 Search nodes, then execute and validate the output structure.