How a Company in Mexico City Saved 15+ Hours Weekly Collecting Customer Reviews Using OpenAI Agents

In the bustling metropolis of Mexico City, a leading e-commerce company faced a daunting challenge: spending more than 15 hours per week collecting customer reviews manually. This repetitive, time-consuming task not only drained valuable resources but also delayed critical insights that influence business decisions. In this case study, we dive deep into how intelligent automation powered by OpenAI Agents transformed their operations and reclaimed precious time.

By reading this article, startup CTOs, automation engineers, and operations specialists will learn about the pain points within manual review collection, the tailored automation architecture we implemented using n8n workflows and OpenAI APIs, and the measurable business impact that followed. Moreover, we cover hands-on integration details with Gmail, Google Sheets, Slack, and HubSpot CRM — equipping you with pragmatic insights to streamline similar processes in your organization.

Ready to optimize your customer feedback collection? Keep reading to discover how automation-as-a-service makes it seamless and scalable.

The Problem: Manual Customer Review Collection Draining Resources

The client is a mid-sized e-commerce company based in Mexico City, Mexico, operating within the retail sector. Their customer experience and operations teams were responsible for gathering authentic customer reviews to enhance product credibility and marketing strategies.

Prior to automation, this process was entirely manual: team members individually monitored sales records, identified customers eligible for review requests, composed personalized emails, and then tracked replies by copying feedback into spreadsheets. The entire workflow consumed over 15 hours weekly, approximately 60 hours monthly.

This laborious procedure caused several operational setbacks:

• Time Drain: Over 15 hours spent weekly meant valuable personnel diverted from strategic tasks.
• Inconsistency and Errors: Manual data entry led to occasional missing or duplicate reviews, lowering data trustworthiness.
• Slow Feedback Loop: Delays between purchase and review publication impaired marketing responsiveness.
• Lack of Transparency: The absence of centralized dashboards limited visibility into review collection progress and team performance.

Overall, these inefficiencies slowed decision-making and compromised customer engagement quality, directly affecting revenue growth and brand reputation.

Our Approach: Process Discovery and Strategic Automation Proposal

RestFlow began the engagement with thorough process mapping sessions involving the clients operations and customer experience teams. By charting the entire review collection lifecycle, we identified critical pain points and data handoffs.

The client utilized Gmail for email communication, exported sales data into Google Sheets, and managed customer data within HubSpot CRM. Given these systems and their APIs, we proposed an automation centered around n8n as the orchestration engine due to its open-source flexibility and easy integration support.

To boost the efficiency of review content curation and personalize engagement dynamically, we proposed integrating OpenAI Agents to generate customized email prompts and analyze incoming responses intelligently.

The high-level architecture included:

• A scheduled trigger in n8n for periodic execution
• Fetching new customer purchase records from Google Sheets
• Enriching data with HubSpot API queries (customer info, segments)
• Generating personalized review request emails via OpenAI Agents
• Sending emails through Gmail API
• Capturing replies through Gmail webhook
• Extracting, validating, and recording reviews back into Google Sheets
• Notifying teams via Slack on statuses and errors

These components formed an agile, scalable automation to save time and improve data quality substantially.

Explore the Automation Template Marketplace to see similar automation workflows ready for deployment.

The Solution: Architecture and Workflow Overview

Global Architecture Components:

• Trigger: A scheduled execution in n8n every Monday, Wednesday, and Friday morning to process newly eligible reviews.
• Orchestration Tool: n8n handles workflow logic, API calls, error control, and branching.
• External Integrations: Google Sheets for sales data input and review records storage; HubSpot CRM for customer data enrichment; Gmail API for email dispatch and reception; Slack API for real-time notifications; OpenAI API Agents for email content generation and reply analysis.
• Outputs: Auto-generated review request emails, centralized Google Sheets dashboard updates, and Slack notifications to operations teams.

End-to-End Workflow:

1. Trigger Activation: The scheduler node triggers the workflow on configured days.
2. Load New Customers: Read Google Sheets rows where purchase date is recent and review pending.
3. Customer Data Enrichment: Use HubSpot API to fetch complete contact details and segment tags.
4. Email Content Generation: Send customer context prompts to OpenAI Agent to generate personalized review request emails.
5. Email Sending: Dispatch emails through Gmail API with personalized content.
6. Reply Monitoring: Setup Gmail webhook or IMAP watch to listen for incoming replies.
7. Reply Processing: Pass incoming reply content to OpenAI Agent to extract review sentiments and key content.
8. Data Validation & Storage: Store validated reviews into Google Sheets with timestamps and customer IDs.
9. Notifications: Send Slack messages about successful collection or error alerts.

This cohesive automation eliminates manual effort while maintaining high personalization and authenticity of customer reviews.

Step-by-Step Workflow Node Breakdown 🚀

Trigger Node: Scheduled Execution

The Cron Node in n8n initiates the workflow at 8 AM every Monday, Wednesday, and Friday. This timing aligns with the clients strategic cadence of review requests.

Configuration:

• Cron expression: ‘0 8 * * 1,3,5’
• Timezone set to ‘America/Mexico_City’

This node outputs an empty payload triggering subsequent data fetch.

Google Sheets Read Node: Loading Pending Reviews

This node connects to the clients sales spreadsheet, querying rows where Review Status = ‘Pending’ and Purchase Date >= last 7 days.

Key fields mapped:

• Customer Email
• Order ID
• Product Name

The output is a JSON array that feeds into the next data enrichment stage.

HubSpot CRM Node: Customer Data Enrichment 🧑‍💼

A custom HTTP Request node queries HubSpot Contacts API to fetch:

• Customer name
• Segment tags (e.g., VIP, New Customer)
• Last engagement date

Input: Customer email from Google Sheets.
Output: Merged JSON including segments to tailor email tone.

OpenAI Agent Node: Personalized Email Generation 🤖

Using the OpenAI API node, prompts are constructed that combine customer name, product details, and segment information.

Example prompt:
“Generate a friendly, customized email asking [Customer Name] to review their recent purchase of [Product Name], highlighting their VIP customer status if applicable.”

Response outputs dynamic email bodies in plain text, passed to the email sending node.

Gmail Send Node: Dispatching Review Requests

Configures the Gmail API to send emails from the clients official support address.

Maps:

• To: Customer email
• Subject: “We’d love your feedback on your recent [Product Name] purchase!”
• Body: Generated OpenAI text

Emails include unique tracking parameters in links for later attribution.

Gmail Webhook Node: Monitoring Incoming Replies 📬

This webhook listens for new emails arriving in the support inbox.

When a reply to a dispatched review request arrives, the node captures:

• Message ID
• In-reply-to header
• Email body

This raw data pipelines to OpenAI for sentiment extraction.

OpenAI Agent Node: Review Content Analysis

A second OpenAI Agent is prompted with the email reply, instructed to:

• Extract review text
• Detect sentiment (positive, neutral, negative)
• Flag spam or irrelevant replies

Validated reviews are then structured as JSON for storage.

Google Sheets Update Node: Recording Reviews

Appends new rows into the ‘Collected Reviews’ sheet, including:

• Customer email
• Order ID
• Review content
• Sentiment
• Timestamp

It also updates the original sales sheet row status to ‘Completed’ to avoid duplicates.

Slack Notification Node: Real-time Alerts and Reporting

Operational teams receive Slack messages summarizing daily review collection outcomes:

• Number of successful reviews collected
• Errors encountered
• Unread replies flagged

This enhances visibility and rapid action on exceptions.

Error Handling, Robustness & Security

Error Handling and Retries 🔄

We designed retry mechanisms with exponential backoff on all critical API calls (Google Sheets, HubSpot, Gmail, OpenAI). Failures trigger alerts and queuing for manual review.

n8ns error workflow branches catch exceptions, executing fallback nodes that post alerts to Slack’s #alerts channel.

This approach ensures transient network glitches or rate limits do not cause data loss.

Logging and Observability

All workflow runs log metadata in a dedicated Google Sheets “Audit Logs” spreadsheet, capturing:

• Run start/end times
• Error messages
• Records processed count

Combined with Slack alerts, this allows operations to quickly debug issues.

Security and Data Protection 🔐

API credentials and keys for Gmail, HubSpot, and OpenAI are stored securely in n8n credentials store with strict access control.

We adopted least-privilege permissions:

• Gmail API scope limited to sending and reading only support inbox
• HubSpot API access scoped to contacts read only
• OpenAI usage scoped to specific prompt templates

Additionally, Personally Identifiable Information (PII) data flows only within secured environments, and data-at-rest encryption is enforced in Google Sheets.

Performance, Scaling & Extensibility

Scaling the Workflow

The scheduled batches process up to 500 customer records per run. For future growth, we designed a modular workflow allowing:

• Parallel processing of smaller batches via loop chunks
• Global webhook listeners for immediate reply processing reducing polling latency
• Queue-based rate limiting to avoid API throttling

Webhook vs Polling

We benchmarked webhook-based Gmail event listeners against traditional IMAP polling and chose webhooks due to:

• Lower latency in detecting replies
• Reduced API call volumes
• Better scalability under peak loads

Extensibility to Other Teams or Regions

The workflows modular design supports quick adaptation to:

• Different HubSpot pipelines for marketing vs sales teams
• Multi-language email generation by changing OpenAI prompt templates
• Cross-country deployments with localized scheduling and timezone settings

RestFlows managed hosting services ensure these changes can be deployed safely with versioning and staging environments.

Comparison Tables

n8n vs Make vs Zapier for Customer Review Collection

Option	Cost	Pros	Cons
n8n	Free open-source tier; Hosted options start ~$20/mo	Flexible; Self-hosted for security; Excellent for custom APIs	Setup complexity higher; Requires maintenance (mitigated by RestFlow)
Make	Starting $9/mo; limits on operations	Visual scenario builder; easy integrations	Less control over custom logic; API rate limits tighter
Zapier	Starts $19.99/mo; operation and task limits	User friendly; many app integrations	Limited complexity; expensive at scale

Webhook vs Polling for Email Reply Capture

Option	Latency	API Usage	Scaling
Webhook	Near real-time (seconds)	Low, only on event	Highly scalable; efficient at volume
Polling	Minutes to hours delay	High, frequent API calls	Scaling expensive and complex

Google Sheets vs Database Storage for Reviews

Option	Cost	Setup	Data Integrity	Query Power
Google Sheets	Free with limits	Minimal; no dev needed	Moderate; manual error possible	Basic filter/sort only
Cloud Database (e.g. Airtable, Firebase)	Pay as you go	Medium; requires schema design	High; transactional support	Advanced queries and triggers

To further accelerate your automation journey, Explore the Automation Template Marketplace and discover workflows designed for customer experience management.

Results & Business Impact

The implemented automation reduced manual effort by more than 15 hours each week, equating to 60+ hours saved monthly. Operational teams can now focus on strategy and quality control rather than repetitive data tasks.

Key improvements included:

• Processing Time: Automated review requests sent within minutes of eligibility, shrinking lag from days to near real-time.
• Error Rate: Manual entry errors dropped by over 90%, improving data reliability.
• Review Volume: An estimated 35% increase in collected reviews due to timely, personalized emails.
• Visibility: Slack alerts and dashboard reports enhanced transparency over process health and team workload.

This transformed the customer feedback pipeline into a dynamic asset driving marketing and product development.

Startup CTOs and automation engineers will appreciate how the modular design allows easy adjustments as business conditions evolve, ensuring longevity of this workflow.

Create Your Free RestFlow Account today to build your own intelligent automation pipelines.

Pilot Phase & Ongoing Maintenance Disclaimer

It is important to note that RestFlow deployed this automation with an initial pilot phase. During this period, the workflow ran on controlled real data with close monitoring to identify and fix minor bugs, edge cases, and optimize prompt templates.

Following a successful pilot, RestFlow assumed responsibility for hosting, monitoring, maintenance, and periodic updates. This ongoing managed service ensures stability, security compliance, and continuous improvement aligned with client needs.

Readers should understand that automation workflows require iterative refinement in live environments, with RestFlow as a reliable long-term partner.

Conclusion: Transforming Customer Review Collection with Automation-as-a-Service

This case study highlighted how a Mexico City-based e-commerce company successfully eliminated a manual, time-intensive customer review collection process by implementing an intelligent automation workflow using OpenAI Agents and n8n. The solution integrated core business systems like Gmail, Google Sheets, HubSpot, and Slack — orchestrated seamlessly to deliver personalized, timely engagement that enhanced data quality and operational efficiency.

RestFlows end-to-end Automation-as-a-Service, including design, implementation, hosting, monitoring, and maintenance, allowed the client to scale without complexity or security risk. This approach exemplifies how modern automation bridges AI and traditional tools, unlocking measurable business impact.

Whether you lead a startup or manage enterprise operations, leveraging similar automation workflows can transform your customer experience and resource utilization. Start your automation journey today and create workflows that save hours, reduce errors, and deliver insights faster.

Explore the Automation Template Marketplace or Create Your Free RestFlow Account to get started now.