Software-as-a-service (SaaS) businesses depend on data. Every subscription, upgrade, cancellation, and payment tells a story about how your product is performing and where your business is headed. But without the right tools and metrics, it's easy to miss important signals and get buried in less-than-helpful numbers.

Below, we'll explain what SaaS analytics looks like in action: which metrics matter, how to work with them, and how Stripe Sigma can turn raw data into real insight.

What's in this article?

• What is SaaS analytics, and why is it important?
  
• What are the most important SaaS analytics metrics to track?
  
• How can Stripe Sigma help with SaaS analytics?
  
• What are the benefits of using Stripe Sigma over other SaaS analytics tools?
  
• How do top SaaS businesses use Stripe Sigma to grow?
  
• How do you get started with Stripe Sigma for SaaS analytics?
  

What is SaaS analytics, and why is it important?

SaaS businesses generate a constant stream of data: signups, upgrades, cancellations, usage patterns, payments, and more. SaaS analytics is the process of turning that data into insight about how your business works and where it's going. This matters because subscription models rely on long-term relationships and repeatable revenue. To grow sustainably, you need to understand what's working, what's not, and why. Revenue in the global SaaS market is projected to exceed $428 billion in 2025.

Here's how SaaS analytics can help subscription businesses:

• See where your growth is coming from: Maybe most of your customers with high customer lifetime value (LTV or CLTV) come from a specific channel. Maybe users who adopt a certain feature early are more likely to stick around. Good analytics show you what happened and tell you what to pay attention to next.
  
• Spot problems before they become losses: Churn builds over time. If you know what early signals predict it, such as a drop in engagement or missed payments, you can act faster and retain more customers.
  
• Get different teams on the same page: When product, ops, finance, and leadership are all making decisions from the same dataset, you avoid second-guessing and conflicting priorities.
  
• Measure what matters: Tracking topline revenue without understanding retention, customer acquisition cost (CAC), or LTV gives you an incomplete (and often misleading) view. SaaS analytics helps you focus on the metrics that drive your business.
  

At its core, SaaS analytics is a decision-making engine. It gives you the clarity to move faster, invest smarter, and scale with more confidence.

What are the most important SaaS analytics metrics to track?

SaaS business performance tends to hinge on a few core metrics. These are the signals that tell you how well your model is working, how efficiently you're growing, and where your biggest risks or opportunities lie.

Here's what to track and why it matters:

Monthly recurring revenue (MRR)

MRR is the total predictable revenue you earn each month from active subscriptions. It's one of the fastest ways to assess growth trends, especially if you break it down by source (e.g. new business, upgrades). Even small shifts in MRR can reveal early signs of product momentum or market saturation.

Annual recurring revenue (ARR)

ARR gives you the zoomed-out version of MRR. It helps balance out monthly volatility and is especially useful for annual planning and investor reporting. ARR can help contextualise seasonal trends that might otherwise skew your MRR view. Think of MRR as your speedometer and ARR as your long-range compass.

CAC

CAC measures how much you're spending to acquire a new customer, including ad spend and sales salaries. It's a signal of business efficiency. When CAC climbs, it often means you're targeting harder-to-convert segments or your sales funnel needs a tune-up. High CAC is fine if your customer stays long enough to justify it.

Customer churn rate

Churn is what happens when customers leave. A 5% churn rate might not seem like much, but over time, it erodes your recurring revenue and drags down LTV. There are two main ways to track churn:

• Customer churn: Percentage of users who cancel
  
• Revenue churn: Percentage of revenue lost from cancellations
  

Tracking both helps you see whether you're losing a few big accounts or a wide swath of smaller ones. The more granular your churn analysis (by cohort, plan, life-cycle stage), the more useful it becomes.

LTV or CLTV

LTV is the total revenue you expect to earn from a customer during the relationship. It's a key metric that tells you how much value you're capturing, not just how many customers you've signed. LTV becomes more powerful when paired with CAC: if LTV is 3x or more than CAC, your growth is probably sustainable. If not, you're probably overpaying to acquire short-lived users.

Conversion rates

Every funnel can contain leaks. Your conversion rate, from free trial to paid or from signup to activation, shows where prospects lose momentum. A weak conversion rate can mean misaligned messaging, confusing onboarding, or a value gap between what's promised and what's delivered. To get the full picture, break down conversion by stage and segment: how many website visitors are starting free trials? How many free trial users are converting to paid users? How many first-time users are staying on long term? Tracking each step helps you identify friction points and fine-tune accordingly.

Other metrics

Depending on your stage and model, you might also want to look at:

• Net revenue retention (NRR): This tells you how much revenue you retain and expand over time, factoring in churn, upgrades, and downgrades. It signals product-market fit and upsell success.
  
• Daily/monthly active users (DAU/MAU): These metrics track engagement and can often predict churn. They're especially useful for usage-driven products.
  
• Burn rate: This rate shows how quickly you're using cash, and the metric is especially important for early-stage or venture-backed SaaS businesses.
  

You don't need a hundred metrics to run a smart business. But you do need to consistently track the ones that tie directly to revenue, retention, and customer value. The best SaaS businesses use these numbers to guide where to double down, where to fix gaps, and where to experiment.

How can Stripe Sigma help with SaaS analytics?

SaaS analytics usually means juggling multiple tools, exporting spreadsheets, or waiting on a data team. Stripe Sigma is a structured query language (SQL)- and AI-powered analytics layer built into the Stripe platform that gives you the data analysis you need. If you're using Stripe to handle subscriptions, payments, and billing, Stripe Sigma lets you analyse that data inside your Stripe Dashboard. Sigma makes it easy to ask questions of that data and get answers in seconds.

You can work with Sigma in a few ways:

• Use SQL if you're comfortable writing queries.
  
• Start with prebuilt templates for common SaaS questions, such as "What's our monthly recurring revenue?” or "How many active subscriptions do we have?”
  
• Ask the Sigma Assistant your question in plain English, and let it generate the query for you.
  

No matter how you use Sigma, you're querying live data. It's fast, flexible, and accessible across teams.

What are the benefits of using Stripe Sigma over other SaaS analytics tools?

There are plenty of analytics platforms on the market. But for SaaS businesses using Stripe, Sigma offers a different kind of advantage: your data is already there, and you don't need to move it around to get answers.

Here's how Sigma stands out:

Live, integrated data

Sigma works directly off your Stripe data, inside your Stripe Dashboard. There's no syncing, importing, or waiting for pipelines to refresh. You're always looking at live, up-to-date numbers, whether you're checking this month's MRR or reviewing last quarter's churn.

Flexible analysis tools

With Sigma, you're not locked into rigid dashboards or black-box reports. You can write custom SQL to answer specific questions, start with prebuilt templates and tweak them as needed, or ask the Sigma Assistant. If you want to slice MRR by product, filter churn by signup cohort, or find customers with failed payments in the past seven days, you can. Sigma gives you the flexibility to explore the data in whatever way is most helpful to you.

Collaborative design

Saved queries can be shared across your team. When someone builds a useful report – for example, churn by signup cohort or active subscriptions by plan – others can run it. Product managers, finance leads, and operations teams can get what they need without waiting on an analyst. It's easy to reuse and adapt queries without starting from zero.

No tool-hopping

Because Sigma is built into Stripe, you don't have to leave the platform where your billing and payments already live. You can go from looking at a customer's transaction history to running a business-wide revenue report without switching systems.

Automation that saves time

You can schedule reports to hit your inbox (or your team's) on a recurring basis. That way, key metrics, such as weekly upgrades or late payments by geography, show up without reminders or manual pulls.

How do top SaaS businesses use Stripe Sigma to grow?

High-performing SaaS teams build habits around using their metrics. Stripe Sigma offers the flexibility to ask better questions and move faster when the answers matter.

Here's how teams across functions use it to stay sharp and scale smarter:

Ops teams track daily performance

Operations leaders use Sigma to stay close to what's happening in the business right now. They'll track:

• Daily signups
  
• Monthly subscription changes
  
• Unexpected drops in payment volume or spikes in refunds
  

By checking these numbers in real time, they can catch issues early.

Finance teams close faster and forecast better

Sigma speeds up reporting for finance teams without compromising accuracy. Instead of exporting CSVs and stitching data together, they use Sigma to:

• Reconcile revenue, fees, and payouts
  
• Track cash flow across time and geography
  
• Pull live MRR, ARR, and collections for reporting
  

Zoom, for example, uses Sigma to gather important information for revenue recognition, reconciliation, and reporting, and the video communications platform uses this info to address challenges. Sigma makes monthly close faster and gives leadership better visibility into how revenue is trending.

Analysts dig into retention, usage, and value

Data teams at businesses such as the messaging platform Slack use Sigma to explore cohort behaviour, lifetime value, and product engagement patterns. For example:

• How does churn differ by pricing tier or signup month?
  
• Which customer segments have the highest LTV?
  
• Where do cancellations tend to cluster in the life cycle?
  

These insights shape road map decisions, pricing experiments, and more.

Growth teams surface new opportunities

Because Sigma supports ad-hoc queries, growth teams use it to explore questions as they come up, such as:

• What's the upgrade rate from basic to pro plans over the past six months?
  
• Are customers who use Feature X more likely to renew?
  
• Which acquisition channels bring in the highest-paying users?
  

Sigma gives them the data to validate instincts and the agility to turn insight into action quickly.

How do you get started with Stripe Sigma for SaaS analytics?

If you're using Stripe for billing, you're most of the way there. Stripe Sigma taps into the data you already have, so getting started is relatively simple.

Here's how to get up and running:

Enable Sigma in your Stripe Dashboard

Sigma is an add-on feature. You can start with a 30-day free trial, and setup takes just a few clicks in the left-hand menu of your Dashboard.

Explore the query template library

Stripe includes prebuilt queries for common use cases, such as active subscriptions, MRR trends, churned customers, and failed payments. These templates are a fast way to start seeing real data without writing any SQL.

Use the Sigma Assistant for natural language queries

If you're not a SQL user, the Sigma Assistant lets you ask questions in plain English. You might type: "Show monthly recurring revenue by product for the past 6 months.”

Sigma writes the SQL for you, and you can run, tweak, or save the query from there.

Run and refine your core reports

Start with foundational metrics:

• MRR and ARR over time
  
• Churn by sign-up cohort
  
• Upgrade/downgrade patterns by plan
  
• Trial-to-paid conversion
  

You'll see the results instantly in your Dashboard and can adjust filters, time frames, and groupings as needed.

Save, schedule, and share your reports

Once you've built a report you'll reuse – for example, "Churned customers by sign-up month” – save it in Sigma. You can:

• Schedule it to email yourself or your team automatically
  
• Visualise results with built-in charts
  
• Share a link to the query inside Stripe
  

It's an easy way to keep important metrics visible without extra overheads.

Use Sigma as a jumping-off point for deeper analysis

Sigma covers many of the day-to-day analytics SaaS teams use. But if you need to join Stripe data with usage or marketing metrics, consider extending it with Stripe Data Pipeline to your warehouse.