Google Reviews to Google Sheets, instant VOC insights
You finally find a business with tons of useful Google reviews. Then you realize you have to copy, paste, and summarize them by hand. Thirty reviews doesn’t sound like much until you’re three tabs deep, your notes are messy, and you still don’t have a single clean “angle” you can use in an ad.
This Google reviews automation hits marketing managers the hardest, but founders and brand strategists feel it too. You need real customer language (fast), not another “we think our audience cares about…” brainstorm. This workflow turns raw reviews into organized VOC themes and ready-to-steal quotes in a Google Sheet.
Below, you’ll see how the workflow runs, what it produces, and what you can tweak so the insights match your brand voice and your offers.
How This Automation Works
The full n8n workflow, from trigger to final output:
n8n Workflow Template: Google Reviews to Google Sheets, instant VOC insights
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The Problem: Turning Reviews Into Messaging Is Slow
Google reviews are marketing gold, but they arrive as an unstructured wall of text. You can read them and “get the vibe,” sure. The problem is getting from vibe to usable output: angles, motivations, objections, product opportunities, and quotes you can drop into a landing page without rewriting everything. After a few businesses, you end up with scattered screenshots, half-finished notes, and a doc nobody trusts because it’s impossible to trace insights back to real customer words.
It adds up fast. Here’s where it usually breaks down.
- Pulling even 30 reviews manually can eat about an hour once you include cleanup and formatting.
- You lose the best quotes because they’re buried, so your copy ends up “polished” but not persuasive.
- Insights aren’t consistent across teammates, which means briefs change depending on who read the reviews.
- Nothing is reusable, so you repeat the same research every time you build a new ad, page, or pitch deck.
The Solution: Auto-Extract VOC Themes and Quotes into Sheets
This workflow takes a simple input (business name + Google Place ID) and does the annoying part for you. Once triggered, it fetches the top 30 Google reviews via an API request, separates and aggregates the review text, then sends that combined content to GPT-4 through an AI Agent. The model doesn’t just summarize. It classifies what customers are actually saying into categories you can use right away: marketing angles, motivations, frictions and barriers, product opportunities, and VOC snippets. Finally, it writes the structured results into a Google Sheet so you can build a living insight library across brands, locations, or competitors.
The workflow starts when you submit the business name and Place ID through a form-style trigger. Then Dumpling AI retrieves reviews, and n8n consolidates them into clean input for the AI step. GPT generates structured insights, and Google Sheets receives a neat row you can sort, filter, and reuse.
What You Get: Automation vs. Results
| What This Workflow Automates | Results You’ll Get |
|---|---|
|
|
Example: What This Looks Like
Say you’re researching three competitors before writing a new landing page. Manually, pulling 30 reviews each, skimming them, and turning notes into angles is usually about 2 hours per competitor, so you’re looking at roughly 6 hours. With this workflow, you submit three Place IDs (maybe 5 minutes total), wait for the reviews to fetch and the AI to process (often around 10 minutes per business), and your Google Sheet fills with themes and quotes. Same research, but now it’s organized and reusable.
What You’ll Need
- n8n instance (try n8n Cloud free)
- Self-hosting option if you prefer (Hostinger works well)
- Dumpling AI for Google review retrieval via API.
- OpenAI (GPT-4 or GPT-4o) to extract structured VOC insights.
- Google Sheets to store your insight library.
- Dumpling AI API key (get it from your Dumpling AI dashboard).
Skill level: Beginner. You’ll connect credentials and paste in your Sheet ID and tab name.
Don’t want to set this up yourself? Talk to an automation expert (free 15-minute consultation).
How It Works
You submit a business name and Google Place ID. That input is the trigger, using a simple form-style step in n8n. No spreadsheets to pre-fill just to get started.
Reviews are fetched and cleaned up. n8n calls Dumpling AI through an HTTP request, then splits the response into individual review items. After that, it aggregates the review text into a single “packet” the AI can analyze without missing context.
GPT extracts insights in a structured format. The AI Agent and GPT-4 chat model analyze the combined reviews and generate clear categories: marketing angles, customer motivations, frictions and barriers, product opportunities, plus quotable VOC snippets. This is the part that turns raw feedback into something a team can actually use.
Everything lands in Google Sheets. The workflow parses the response into predictable fields and writes a clean row to your Sheet, so you can filter by business, compare competitors, or build a swipe file for future campaigns.
You can easily modify the insight categories to match your framework (for example, “jobs to be done” or “objection clusters”) based on your needs. See the full implementation guide below for customization options.
Step-by-Step Implementation Guide
Step 1: Configure the Form Trigger
Set up the workflow entry point to collect the business name and Google Place ID.
- Add the Collect Business & Place Info node as your trigger.
- Set Form Title to
Google Review. - Under Form Fields, add two fields labeled
Business nameandPlace ID. - Save the form and copy the public URL for testing submissions.
Tip: Test the form once to ensure both fields appear and the JSON output includes Business name and Place ID.
Step 2: Connect the Review Retrieval Service
Fetch Google reviews using the Place ID collected from the form trigger.
- Add the 🔎 Review Retrieval Request node and connect it after Collect Business & Place Info.
- Set URL to
https://app.dumplingai.com/api/v1/get-google-reviews. - Set Method to
POSTand enable Send Body with Specify Body set toJSON. - Set JSON Body to
{ "placeId": "{{ $json['Place ID'] }}", "reviews": "30" }. - Credential Required: Connect your httpHeaderAuth credentials.
⚠️ Common Pitfall: If the API returns empty data, verify the Place ID is valid and that your httpHeaderAuth header includes the correct token.
Step 3: Aggregate Review Text for Analysis
Split the review items and aggregate the review text into a single dataset for analysis.
- Add 🧮 Separate Review Items after 🔎 Review Retrieval Request.
- Set Field to Split Out to
items. - Add 📦 Combine Review Text after 🧮 Separate Review Items.
- Set Include to
Specified Fieldsand Fields to Include toreview_text. - Keep Aggregate set to
aggregateAllItemDatato compile the text for the AI prompt.
Step 4: Set Up AI Insight Extraction
Use the AI agent to analyze reviews and structure the output for reporting.
- Add 🤖 GPT Insight Extractor after 📦 Combine Review Text.
- Set Prompt Type to
Defineand use the provided prompt text with the expression{{ JSON.stringify($json.data) }}embedded in the prompt. - Ensure Has Output Parser is enabled for structured output.
- Connect 🔌 GPT-4 Chat Engine as the language model, with Model set to
gpt-4o. - Credential Required: Connect your openAiApi credentials on 🔌 GPT-4 Chat Engine.
- Attach 📊 Structure Insight Output as the output parser and keep the schema as provided.
- Note: 🧠 Agent Toolset and 📊 Structure Insight Output are AI sub-nodes; credentials should be added to the parent nodes (🔌 GPT-4 Chat Engine for LLM access).
Tip: The system message in 🤖 GPT Insight Extractor helps keep output consistent. Keep it as-is to reduce variance in marketing insights.
Step 5: Configure the Output to Google Sheets
Append or update the structured insights into your reporting spreadsheet.
- Add 📄 Update Insight Sheet after 🤖 GPT Insight Extractor.
- Set Operation to
appendOrUpdate. - Select the target document and sheet (e.g., Document
Marketing Insightsand SheetSheet1). - Map columns using expressions such as
{{ $('Collect Business & Place Info').item.json['Place ID'] }}and{{ $json.output.MarketingInsights.MarketingAngles.join('\n\n') }}. - Credential Required: Connect your googleSheetsOAuth2Api credentials.
Step 6: Test and Activate Your Workflow
Validate each step and enable the workflow for ongoing use.
- Click Execute Workflow and submit the form from Collect Business & Place Info.
- Confirm that 🔎 Review Retrieval Request returns review items and that 📦 Combine Review Text aggregates
review_text. - Verify 🤖 GPT Insight Extractor outputs structured insight fields from 📊 Structure Insight Output.
- Check that 📄 Update Insight Sheet appends or updates a row with marketing insights.
- When successful, toggle the workflow to Active for production use.
Common Gotchas
- Dumpling AI credentials can expire or need specific permissions. If things break, check your Dumpling AI dashboard key status and the HTTP Request header auth in n8n first.
- If you’re using Wait nodes or external processing, timing varies. Bump up the wait duration if downstream nodes fail on empty responses after the review retrieval step.
- Default prompts in AI nodes are generic. Add your brand voice and “what good looks like” inside the GPT Insight Extractor prompt early or you will be editing outputs forever.
Frequently Asked Questions
About 30 minutes if your APIs and Google Sheet are ready.
No. You’ll connect credentials and paste in your Google Sheet details. The rest is configuration, not code.
Yes. n8n has a free self-hosted option and a free trial on n8n Cloud. Cloud plans start at $20/month for higher volume. You’ll also need to factor in OpenAI API usage (often a few cents per run) and whatever Dumpling AI charges for review retrieval.
Two options: n8n Cloud (managed, easiest setup) or self-hosting on a VPS. For self-hosting, Hostinger VPS is affordable and handles n8n well. Self-hosting gives you unlimited executions but requires basic server management.
Yes, but you’ll want to swap the trigger and add a small loop. Replace the manual “Collect Business & Place Info” trigger with a Google Sheets list of Place IDs, then use Split in Batches to run each business on a schedule. Common customizations include adding sentiment scoring, tagging insights by category, and saving the “top quotes” into a separate sheet tab for quick copy paste.
Usually it’s OAuth permissions or an expired token. Reconnect Google Sheets in n8n, then confirm the Sheet document ID and tab name match what you created. Also check sharing settings: if the account you authenticated with can’t access that Sheet, updates will fail even though the workflow looks fine.
This version is built around the top 30 reviews per run.
Often, yes, because this workflow relies on a more “custom logic” flow than a simple two-step zap. In n8n, you can split review items, aggregate them, and run a structured AI agent without fighting platform limits. Self-hosting also matters if you plan to run a lot of research jobs and don’t want every extra step to cost more. Zapier or Make can still be fine for light usage, especially if you’re already paying and just want a quick prototype. If you’re unsure, Talk to an automation expert and you’ll get a straight recommendation.
Once this is running, you stop “reading reviews” and start collecting proof. The workflow handles the repetitive stuff, and your team gets a growing library of angles and quotes you can use whenever you need to ship copy fast.
Need Help Setting This Up?
Our automation experts can build and customize this workflow for your specific needs. Free 15-minute consultation—no commitment required.
