A Complete Guide to Stripe Analytics: Understanding Your Payment Data
Learn how to leverage your Stripe data to make informed business decisions and drive growth.
In this guide:
Understanding Key Metrics
Natural Language Queries
Customer Insights
AI-Powered Analysis
Understanding Stripe Analytics
Stripe Analytics is more than just tracking payments—it's about understanding your business's financial pulse and customer behavior patterns. With Hunchbank's natural language processing capabilities, you can transform raw Stripe data into actionable insights without writing complex queries.
Key Metrics You Should Track
Revenue Metrics
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Monthly Recurring Revenue (MRR)
Predictable revenue component from subscriptions
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Annual Recurring Revenue (ARR)
Yearly perspective of recurring revenue
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Revenue Growth Rate
Month-over-month and year-over-year growth
Customer Metrics
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Customer Lifetime Value (CLV)
Total revenue expected from a customer
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Churn Rate
Rate at which customers stop subscribing
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Customer Acquisition Cost (CAC)
Cost to acquire new customers
Natural Language Queries
Hunchbank transforms how you interact with your Stripe data through natural language processing. Instead of writing complex queries, simply ask questions in plain English:
Example Queries
"Show me MRR growth over the last 6 months"
"Who are my top 10 customers by revenue?"
"What's my churn rate trend this quarter?"
AI-Powered Analytics
Hunchbank's AI agents continuously monitor your Stripe data, providing proactive insights and automating responses to key events.
Churn Prevention
Automatically identifies at-risk customers and triggers retention workflows
Revenue Optimization
Suggests pricing optimizations based on customer behavior patterns
Fraud Detection
Monitors transactions for suspicious patterns and potential fraud
Best Practices for Stripe Analytics
1
Regular Monitoring
Set up daily or weekly review routines for key metrics. Use Hunchbank's automated alerts to stay informed of significant changes.
2
Segment Analysis
Break down data by customer segments, product lines, and geographic regions to identify specific trends and opportunities.
3
Automated Responses
Configure AI agents to automatically respond to specific triggers, such as failed payments or churn risks.
Getting Started with Hunchbank Analytics
Ready to transform your Stripe data into actionable insights? Follow these steps:
1
Connect Your Stripe Account
Securely link your Stripe account to Hunchbank using our guided setup process
2
Configure AI Agents
Set up automated monitoring and response workflows based on your business needs
3
Start Asking Questions
Use natural language queries to explore your data and generate insights
Natural Language Queries: Exploring Stripe Data in Plain English
Learn how to analyze your Stripe data using simple, conversational questions instead of complex queries.
What you'll learn:
Query Structure & Patterns
Common Query Examples
Advanced Query Techniques
Best Practices & Tips
Understanding Natural Language Queries
Natural language queries allow you to interact with your Stripe data using everyday language instead of technical query syntax. Hunchbank's AI understands context, intent, and common business terminology to deliver accurate insights from your questions.
Basic Query Patterns
Revenue Queries
"What was my total revenue last month?"
"Show me MRR growth trend this year"
"Compare revenue between Q1 and Q2"
Common Query Categories
Customer Analysis
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"Who are my top 10 customers by spend?"
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"Show me customers at risk of churning"
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"List customers who upgraded this month"
Subscription Metrics
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"What's my current MRR?"
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"Show churn rate over last 6 months"
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"List all canceled subscriptions"
Advanced Query Techniques
Hunchbank's natural language processing can handle complex queries that combine multiple metrics, timeframes, and conditions.
Advanced Query Examples
Comparative Analysis
"Compare revenue from enterprise customers vs SMBs in Q1"
Multi-metric Analysis
"Show me customers with high LTV but declining usage in last 3 months"
Trend Analysis
"Analyze payment failure patterns by card type and region"
Query Tips & Best Practices
1
Be Specific with Time Periods
Instead of "recent sales", use "sales in the last 30 days" or "Q1 2024 sales"
2
Use Business Metrics
Reference common metrics like MRR, ARR, churn rate, and LTV in your queries
3
Include Context
Add relevant segmentation (e.g., by plan type, region, or customer segment)
Query Templates
Growth Analysis
"Show [metric] growth [timeframe] by [segment]"
Customer Behavior
"Find customers who [action] in [timeframe] with [condition]"
Comparative Analysis
"Compare [metric] between [segment1] and [segment2] in [timeframe]"
Automating Insights
Hunchbank allows you to save and schedule your most important queries for regular monitoring.
Saved Queries
Save frequently used queries for quick access and consistency
Scheduled Reports
Set up automated reports to run at regular intervals
Smart Alerts
Get notified when metrics cross specified thresholds