Extract Marketing Insights from Google Reviews Using Dumpling AI and GPT-4

🧠 Why This Automation Is Powerful

Google reviews are full of customer emotions, complaints, praise, and real-life experiences. But reading and analyzing them manually takes hours — and most of the time, you miss the marketing gold hiding between the lines.

This automation solves that.

With just the business name and Google Place ID, this workflow pulls in up to 30 recent Google reviews, analyzes them using GPT-4 via LangChain, and breaks them down into:

• Marketing angles
  
• Customer motivations
  
• Frictions and hesitations
  
• Product improvement ideas
  
• Real review quotes you can use in copy
  

Then it logs everything neatly into a Google Sheet — ready for your team to use in campaigns, product roadmaps, or strategy decks.

🧩 Tools Used

• n8n: to orchestrate the flow
  
• Dumpling AI: to fetch Google reviews
  
• LangChain + GPT-4: to analyze review text
  
• Google Sheets: to store all insights for easy reference
  

✅ Step-by-Step Setup

🔹 Step 1: Form Trigger – Submit Business Name and Place ID

The workflow starts with a simple form where you enter the:

• Business Name (for your reference)
  
• Place ID (Google’s unique identifier for the business)
  

This step is ideal for marketers or team members who don’t want to open n8n directly. They just enter the business info, and the workflow does the rest.

🔹 Step 2: Use Dumpling AI to Fetch Reviews

Once the form is submitted, n8n sends the Place ID to Dumpling AI’s API:

https://app.dumplingai.com/api/v1/get-google-reviews

This API pulls up to 30 of the latest public Google reviews. Each review includes:

• Review text
  
• Rating
  
• Review timestamp
  
• Reviewer name
  

This saves time on scraping and avoids needing Google’s restricted Places API.

🔹 Step 3: Split the Review List

The reviews come back as a list. Using a Split Out node, each review is split into individual items so we can process them cleanly.

🔹 Step 4: Aggregate Review Texts

Now we merge all the review texts into a single block of text. This lets GPT-4 see everything in one go, so it can look for patterns, common phrases, and themes.

🔹 Step 5: Analyze with GPT-4 (LangChain Agent)

Here’s where the magic happens. The full review text is sent to GPT-4 using a LangChain Agent with a very specific prompt:

I want you to analyze the following Google reviews and return insights specifically for marketing and product strategy.

Your deliverables should include:

– Marketing angles  

– Customer motivations  

– Frictions & barriers  

– Product opportunities  

– Voice of customer (3-5 quotes)

Review Data: {{ reviews }}

GPT-4 is instructed to act like a senior marketing strategist, not just a text summarizer. That means the output is practical, structured, and useful.

🔹 Step 6: Parse the AI Output into Structured Format

Once the AI agent returns the insights, a LangChain structured output parser turns them into well-formatted sections like:

• marketingAngles: list of angles you can use in campaigns
  
• customerMotivations: why people buy or visit
  
• frictionsAndBarriers: complaints or concerns
  
• productOpportunities: ideas for improving services
  
• voiceOfCustomerSnippets: memorable quotes you can reuse

🔹 Step 7: Save Results to Google Sheets

Finally, all structured insights are logged into a connected Google Sheet. Each row includes:

• Business Name
  
• Place ID
  
• Insights (each section in its own column)
  

The automation checks if the Place ID already exists. If it does, it updates the row. Otherwise, it adds a new one.

💡 Use Cases for This Automation

• Marketing Teams: Use real quotes and triggers in your ads
  
• Product Managers: Discover what frustrates or delights users
  
• Customer Success: Proactively address common concerns
  
• Agencies: Create fast VOC analysis for clients
  

🧠 Final Thoughts

This automation turns raw, messy reviews into clear, actionable strategy in just a few clicks. Instead of reading through hundreds of reviews manually, you get an organized dashboard of what your customers feel, say, and want — straight from their own words.

It’s not just automation. It’s marketing research on autopilot.