If you're a SaaS founder or ecommerce operator tracking MRR, churn, LTV, and cohorts manually — this guide is for you.
You launched your SaaS or ecommerce store. You have Stripe, Paddle, or BigCommerce connected. But when someone asks "What's your MRR this month?" or "Which plan has the lowest churn?" — you have to:
- Log into your payment dashboard
- Export a CSV
- Open a spreadsheet
- Write formulas manually
- Hope the numbers are right
- Do it all again next week
This is not a workflow. This is a time sink.
You need to know your Monthly Recurring Revenue (MRR), growth rate, and revenue breakdown by plan — but your payment dashboard only shows raw transactions.
| Tool | What You Use It For | The Problem |
|---|---|---|
| Stripe Dashboard | See total payments | No MRR tracking, no growth trends, no cohort view |
| Google Sheets | Build MRR calculator manually | Must export CSV every time, formulas break, not real-time |
| Excel | Advanced revenue modeling | Manual, static, no live data sync |
| Baremetrics | SaaS metrics | Expensive ($108+/mo), overkill for early-stage founders |
| ChartMogul | Subscription analytics | Complex setup, steep learning curve, costly at scale |
The typical workflow:
- Export transactions from Stripe → CSV
- Clean the data in Excel/Sheets
- Write SUMIF formulas to group by plan
- Calculate MRR manually (active subscriptions × price)
- Create a chart manually
- Repeat every single month
Connect your Stripe or Paddle account once. Chartsy automatically calculates MRR, ARR, revenue by plan, and growth trends — updated in real-time. No exports, no formulas, no data analyst required.
→ Start your free trial with Chartsy
Churn is the silent killer of SaaS businesses. Knowing who churned, when, and why requires deep data analysis that most tools simply don't offer out of the box.
| Tool | What You Use It For | The Problem |
|---|---|---|
| Stripe Radar / Dashboard | See cancellations | Shows events, not churn rate, no trend analysis |
| Google Sheets | Track churned customers manually | Error-prone, labor-intensive, not scalable |
| Mixpanel | User behavior analytics | Tracks events, not billing churn — requires dev setup |
| Amplitude | Product analytics | No native payment/billing data integration |
| ProfitWell (now Paddle) | Churn metrics | Limited if you're not on Paddle; limited customization |
The typical workflow:
- Pull list of cancelled subscriptions from Stripe
- Calculate total active subs at start of period
- Divide cancelled / total → get churn %
- Try to segment by plan, geography, or acquisition channel
- Build a chart in Looker Studio with manual data connection
- Set up weekly reminders to redo this process
Chartsy tracks churn rate automatically — segmented by plan, time period, and customer cohort. See which pricing tier loses the most customers and take action before it becomes a crisis.
→ See your churn data clearly with Chartsy
LTV is one of the most important metrics for knowing how much you can spend on customer acquisition — but calculating it accurately requires combining subscription history, upgrade/downgrade data, and payment records.
| Tool | What You Use It For | The Problem |
|---|---|---|
| Stripe Dashboard | See total customer spend | No LTV metric, no prediction, no segmentation |
| Google Sheets | LTV formula (ARPU / Churn Rate) | Oversimplified, doesn't account for expansions |
| Tableau | Data visualization | Requires data engineer, expensive ($70+/user/mo) |
| Power BI | Business intelligence | Complex setup, requires SQL knowledge |
| Looker Studio | Free BI from Google | No native Stripe integration, needs manual connectors |
The typical workflow:
- Export all customer transactions from Stripe
- Group by customer ID in Excel
- Calculate total revenue per customer
- Average across all customers
- Segment manually if needed (by plan, country, etc.)
- Build a pivot table and visualize
- Repeat every quarter
Chartsy computes LTV automatically, segmented by plan and cohort. Understand which customer segments generate the most long-term value so you can double down on what works.
→ Discover your best customers with Chartsy
Cohort analysis reveals whether your product is getting better or worse at retaining customers over time. Without it, you're optimizing blindly.
| Tool | What You Use It For | The Problem |
|---|---|---|
| Google Analytics | Web traffic cohorts | Not tied to billing data, doesn't show revenue retention |
| Mixpanel | Behavioral cohorts | Requires event tracking setup, no payment data |
| Python + Pandas | Custom cohort scripts | Needs developer, maintenance overhead, not real-time |
| SQL + Metabase | Query-based cohorts | Requires database access, SQL knowledge, complex setup |
| Excel PivotTables | Manual cohort tables | Extremely tedious to build, breaks with new data |
The typical workflow:
- Write a SQL query to group customers by sign-up month
- Join with subscription activity table
- Pivot the data to show retention by cohort
- Export to Excel for formatting
- Manually color-code retention percentages
- Present to stakeholders (then redo it next month)
Chartsy generates cohort retention tables automatically from your Stripe or Paddle data. See how each signup month's customers behave over time — no SQL, no spreadsheets, no manual work.
→ Unlock cohort insights with Chartsy
BigCommerce's built-in reports are basic. Knowing your top-performing products, average order value (AOV) trends, and customer segments requires jumping between multiple reports.
| Tool | What You Use It For | The Problem |
|---|---|---|
| BigCommerce Reports | Basic sales data | No advanced segmentation, no cross-metric analysis |
| Google Analytics 4 | Traffic & conversion | No revenue detail, complex event setup required |
| Klaviyo | Email + revenue tracking | Limited to email-driven revenue, not full store analytics |
| Triple Whale | Ecommerce analytics | Expensive, focused on ad attribution |
| Looker Studio + BigCommerce connector | Custom dashboards | Requires 3rd-party connector ($), manual setup |
The typical workflow:
- Export orders from BigCommerce → CSV
- Import into Google Sheets
- Create pivot tables for product revenue
- Calculate AOV manually
- Segment by category or time period
- Build charts, format, share with team
Chartsy connects directly to BigCommerce and gives you top products, revenue by category, AOV trends, and customer segments — all in one real-time dashboard with AI-powered insights.
→ Analyze your BigCommerce store with Chartsy
Every time you need to share metrics with your co-founder, team, or investors — you manually export data, format a report, and send a static PDF that's outdated the moment it's sent.
| Tool | What You Use It For | The Problem |
|---|---|---|
| Google Slides | Investor deck | Manual updates, static numbers, time-consuming |
| Notion | Metric tracking page | No live data, manual entry required |
| Airtable | Collaborative data tracking | No native payment integration, complex automations |
| Loom | Screen recording metrics | Not interactive, not shareable as a live dashboard |
| Email with CSV attached | Send data to team | Outdated instantly, no context, unprofessional |
The typical workflow:
- Screenshot your dashboards
- Paste into Google Slides or Notion
- Update numbers manually
- Export to PDF
- Email to stakeholders
- Get questions → go back to step 1
Chartsy lets you export dashboards as PDF or PNG, or share a live dashboard link — so your team and investors always see real-time data. Professional, interactive, always up to date.
→ Share live dashboards with Chartsy
| Metric | Old Way (Manual) | With Chartsy |
|---|---|---|
| MRR | CSV export + Sheets formula | Automatic, real-time |
| Churn Rate | Manual calculation monthly | Live, segmented by plan |
| LTV | Custom Excel model | Auto-calculated by cohort |
| Cohort Analysis | SQL + pivot tables | One-click visual table |
| Revenue by Plan | Manual pivot table | Built-in breakdown |
| Report Sharing | Static PDF/email | Live shareable dashboard |
| Time Required | 2–8 hours/week | Minutes |
| Skill Required | SQL, Excel, data analyst | None — ask in plain English |
Chartsy is built specifically for founders doing everything alone — no data team, no analyst, no time to waste.
What makes it different:
- 🔗 Native integrations with Stripe, Paddle Billing, Paddle Classic, and BigCommerce
- 🤖 AI-powered analytics — ask questions in plain English, get instant charts
- 📊 All SaaS metrics in one place — MRR, ARR, LTV, churn, cohorts, revenue by plan
- 🔄 Real-time sync — no more stale data or manual exports
- 📤 Export & share — PDF, PNG, or live shareable dashboards
- 🎯 No code required — connect your account and get answers in minutes
- 💸 Free trial — no credit card required to get started
- Indie hackers & solo founders running SaaS products on Stripe or Paddle
- Ecommerce operators on BigCommerce who want deeper product insights
- Small startup teams that can't afford a data analyst
- Bootstrapped founders who want institutional-grade analytics at indie prices
Ready to stop wasting hours in spreadsheets?
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- Chartsy Official Website
- Understanding MRR for SaaS Founders
- What Is Customer Churn and How to Reduce It
- SaaS Cohort Analysis: Why It Matters
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