Clean company names in Google Sheets with n8n + GPT-4 Mini for better cold email personalization

Input: Google Sheet URL with a Company column → Process: LLM auto-removes suffixes, taglines, and formatting issues → Output: New "Cleaned Companies" sheet with polished company names

Who

Sales or marketing ops running cold email outreach

You get

Turn messy company names like "Techwave Solutions LLC" into natural, professional short forms like "Techwave", reducing template feel and improving reply rates

You need

n8n · google-sheets

Steps

1. Configure credentials and prepare the Google Sheet

   Add Google Sheets OAuth2 and OpenAI API credentials in n8n. Create a new Google Sheet with a header row containing a "Company" column, and fill in the leads below.

2. Trigger the workflow and create the destination sheet

   Run the workflow, then submit the Sheet URL via the n8n Form. The workflow automatically creates a new sheet named "Cleaned Companies" (green tab) in the same spreadsheet for results.

3. Read lead data

   The workflow reads all lead data from the first sheet (sheet ID "0") of the submitted URL.

4. Clean company names with LLM

   Feed the Company column into an LLM Chain. The model uses GPT-4.1-mini (switchable to gpt-4.1 or gpt-4 in n8n), with a Structured Output Parser, following the system prompt rules: remove LLC/Inc. suffixes, redundant words like Systems/Solutions, taglines and descriptive phrases; apply title case; preserve recognizability. Batch size is 5.

   Execution prompt · Source text。Clean Company Name node messages.messageValues[0].message (system prompt)

   Copy prompt

   **Situation** 
   You are processing a lead list for a cold email campaign where company names  will be used as personalization variables. The raw company names in the dataset contain various formatting inconsistencies, unnecessary suffixes, taglines, and casing issues that make them unsuitable for professional, natural, personalized outreach.  
   
   **Task** 
   Clean and standardize company names from a lead list to create professional, polished variables suitable for cold email personalization. For each company name provided, you must: 
   1. Remove common business suffixes (LLC, Inc., Corp., Corporation, Ltd., Limited, Co., Company, etc.) 
   2. Remove common words that are in the formal company name but that a human likely wouldn't include when identifying the company in an email (Systems, Solutions, Communications, Agency, Group, Partners, etc.)
   3. Remove taglines, slogans, or descriptive phrases (typically found after dashes, pipes, or "the" statements) 
   4. Apply proper title case formatting 
   5. Shorten names to their most recognizable form when possible while maintaining professionalism 
   6. Ensure the result maintains the company's professional identity and recognizability  
   
   **Objective** 
   Transform formal, cluttered company names into clean, professional versions that will make cold emails feel more natural, personal and polished, ultimately improving engagement rates and response likelihood in the outreach campaign.
   
   **Knowledge** 
   - Business suffixes to remove include: LLC, Inc., Corp., Corporation, Ltd., Limited, Co., Company, LP, LLP, PC, PLLC, and their variations with different punctuation 
   - Taglines often appear after symbols like: dash (-), pipe (|), colon (:), or phrases starting with "the," "your," "we," etc. 
   - Proper title case means capitalizing the first letter of each major word, but keeping articles, prepositions, and conjunctions lowercase unless they start the name. Acronyms should remain in all caps.
   - Maintain professional tone 
   - Keep established business names recognizable (e.g., "Microsoft Corporation" becomes "Microsoft") 
   - Avoid over-shortening if it makes the company unrecognizable or unprofessional 
   - Service descriptions and taglines should be completely removed (e.g., "ExtraSlice, LLC - Workspace as a Service" becomes "ExtraSlice")  
   
   <examples> 
   Input: "ExtraSlice, LLC - Workspace as a Service" 
   Output: "ExtraSlice"  
   
   Input: "ACRE Solutions" 
   Output: "ACRE"  
   
   Input: "MRP Capital Group" 
   Output: "MRP"  
   
   Input: "Paul & Associates Real Estate Services" 
   Output: "Paul & Associates"  
   
   Input: "Global Valuation & Consulting, LLC." 
   Output: "Global Valuation & Consulting"  
   
   Input: "Agent Career Education | Ace" 
   Output: "Agent Career Education"  
   
   Input: "PROPERTY AGENTS" 
   Output: "Property Agents"  
   
   Input: "Agently - Agent Success Platform for Brokerages" 
   Output: "Agently"  
   
   Input: "Monserrate Premium Home Agents" 
   Output: "Monserrate"  
   
   Input: "Belmont Howard Group, LLC."
   Output: "Belmont Howard"  
   
   Input: "BruZiv Partners, LLC" 
   Output: "BruZiv"  
   
   Input: "Van Vlissingen and Co." 
   Output: "Van Vlissingen" 
   </examples>
   
   It's critical that the company's professional recognizability while removing all unnecessary suffixes and taglines - the cleaned name must sound natural and professional when used in a business email context.

5. Merge original data and save results

   Merge the LLM output cleanCompanyName with original lead data by position, add a "Clean Company Name" column, drop intermediate fields, and append to the "Cleaned Companies" sheet.

You are reproducing n8n template #5647: clean company names in Google Sheets with GPT-4 Mini. First confirm prerequisites: 1) n8n instance ready; 2) Google Sheets OAuth2 and OpenAI API credentials configured; 3) target sheet has a "Company" column. Then import workflow.json or build manually: Form trigger → Create destination sheet → Get leads → LLM Chain cleaning (with the system prompt above) → Merge → Save. Test with a small batch first to verify output format before full run.