## Introduction
In the fast-paced SaaS industry, having timely and accurate metrics is crucial for data-driven decision-making. However, extracting, transforming, and loading (ETL) raw data from multiple sources into a centralized analytics platform can be time-consuming and error-prone when done manually. Automation can streamline this process, reduce manual effort, and increase data reliability.
This tutorial guides Data & Analytics teams on how to build an automated ETL workflow for SaaS metrics using n8n, an open-source workflow automation tool. By integrating key SaaS APIs (e.g., Stripe, HubSpot, Google Sheets), you can automate the entire ETL pipeline: extract data, perform transformations, and load cleaned data to a target destination such as a database or analytics tool.
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## What Problem Does This Automation Solve?
SaaS companies often rely on multiple platforms for billing, CRM, support, and product usage data. Consolidating this data manually leads to delayed insights and potential errors. Automating ETL for SaaS metrics:
– Saves manual effort by automating data collection from different APIs
– Ensures data freshness with scheduled workflows
– Standardizes and transforms raw data for easier analysis
– Centralizes data in a single repository or dashboard
Beneficiaries include data engineers, analytics teams, product managers, and business intelligence specialists relying on accurate and timely metrics.
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## Tools and Services Integrated
– **n8n:** For building the automation workflow
– **Stripe API:** Extract subscription and billing data
– **HubSpot API:** Extract customer and marketing data
– **Google Sheets:** Optional intermediate storage and simple transformations
– **PostgreSQL or other databases:** Target data warehouse for loading transformed metrics
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## Step-by-Step Technical Tutorial
### Prerequisites
– n8n instance (cloud or self-hosted)
– API credentials for Stripe and HubSpot
– Access to a PostgreSQL database (or your preferred destination)
– Basic familiarity with JSON and HTTP requests
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### Step 1: Set Up Your n8n Environment
1. Install n8n or use n8n.cloud.
2. Create necessary credentials in n8n for:
– Stripe (API key)
– HubSpot (OAuth or API key)
– PostgreSQL (connection details)
3. Create a new workflow in the n8n editor.
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### Step 2: Define the Workflow Trigger
– Use the **Cron** node to schedule the workflow (e.g., run daily at midnight) to ensure metrics stay up-to-date.
Example:
– Set Cron node to trigger at 00:00 every day.
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### Step 3: Extract Data from Stripe
1. Add an **HTTP Request** node or the **Stripe node** (if available).
2. Configure the node to fetch:
– Subscription data
– Payment history
3. Use the Stripe API endpoints such as `/v1/subscriptions` and `/v1/charges`.
4. Paginate through results if data exceeds the single-page limit.
Example configuration:
– Method: GET
– URL: `https://api.stripe.com/v1/subscriptions`
– Authentication: Bearer token with your Stripe API key
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### Step 4: Extract Data from HubSpot
1. Add the **HubSpot node** or an HTTP Request node with HubSpot API.
2. Fetch CRM contacts, deals, or marketing events relevant to your metrics.
3. Example endpoints: `/crm/v3/objects/contacts`, `/crm/v3/objects/deals`.
4. Use OAuth credentials or API key for authentication.
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### Step 5: Optional – Store Raw Data in Google Sheets
– Use the **Google Sheets node** to dump extracted raw data for manual inspection or backup.
– Map extracted JSON fields to sheet columns.
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### Step 6: Transform Data
– Use the **Function node** in n8n to:
– Normalize dates and timestamps to a standard format
– Calculate MRR (Monthly Recurring Revenue) from subscriptions
– Segment customers by plan type or status
– Merge datasets (e.g., join Stripe subscription data with HubSpot contact data by email or customer ID)
Example snippet inside a Function node:
“`javascript
// Normalize timestamps and calculate MRR
return items.map(item => {
const subscription = item.json;
subscription.normalizedDate = new Date(subscription.current_period_start * 1000).toISOString();
subscription.MRR = subscription.plan_amount / 100; // assuming amount in cents
return { json: subscription };
});
“`
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### Step 7: Load Data into PostgreSQL
1. Use the **Postgres node** to insert or upsert transformed records into your analytics database.
2. Set up the SQL query to insert data into a staging table or update existing metrics.
Example query:
“`sql
INSERT INTO saas_metrics (customer_id, mrr, plan_type, normalized_date) VALUES (:customer_id, :mrr, :plan_type, :normalized_date) ON CONFLICT (customer_id) DO UPDATE SET mrr = EXCLUDED.mrr, normalized_date = EXCLUDED.normalized_date;
“`
3. Map parameters using values from transformed data.
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### Workflow Summary
1. Cron trigger runs daily.
2. Stripe and HubSpot API nodes extract raw SaaS data.
3. Optional Google Sheets node stores raw data.
4. Function node performs data transformation and merging.
5. Postgres node loads the processed data for analysis.
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## Common Errors and Tips for Robustness
– **API Rate Limits:** Use pagination and rate limiting logic to avoid hitting API limits. Implement retries with exponential backoff.
– **Data Inconsistencies:** Validate data formats in the Function node; exclude or flag corrupted or missing data.
– **Authentication Expiry:** Monitor and refresh OAuth tokens periodically if applicable.
– **Error Handling:** Add **Error Trigger nodes** or conditional error handling in n8n to retry failed nodes or alert on failure.
– **Data Duplication:** Use upsert queries or unique keys in your database to prevent duplications.
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## How to Adapt or Scale the Workflow
– **Add More Data Sources:** Integrate usage data from product analytics or support platforms like Intercom.
– **Parallel Processing:** Split workflow branches to run independent extraction nodes simultaneously.
– **Incremental Loads:** Extract only data changed since the last run by storing timestamps in a database or using n8n’s workflow data.
– **Advanced Transformations:** Move complex logic to external scripts invoked inside n8n via **Execute Command** nodes or connect to cloud functions.
– **Alerting & Monitoring:** Add Slack or email notifications for workflow failures or unusual metric changes.
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## Conclusion and Bonus Tip
Automating your ETL for SaaS metrics using n8n empowers your Data & Analytics team to build reliable, scalable data pipelines without writing extensive code. This improves metric accuracy, frees up engineering resources, and accelerates business insights.
**Bonus Tip:** Use n8n’s version control and environment variables to manage API keys and workflow versions safely. This approach enables agile experimentation and smoother maintenance as your data ecosystem evolves.
Start building your SaaS metrics ETL workflow today to unlock faster, consistent insights that drive smarter decisions.