How to See Stripe MRR and Churn by Customer Segment
Definite Team
Stripe can tell you your MRR is $53K and your churn rate is 33%. Useful numbers. But when the board asks "which customer segment is driving that churn?" or "which industries are we actually retaining?", Stripe has no answer. That data lives in your CRM.
In the video above, we connect Stripe and Salesforce to Definite and use Fi (our AI agent) to build a revenue dashboard with segment-level breakdowns. This post walks through what we built, what the numbers revealed, and why this kind of cross-source analysis is nearly impossible to get anywhere else.
The Problem: Stripe Metrics Are Flat
Stripe's built-in analytics give you top-line subscription metrics: MRR, ARR, churn rate, active subscribers. These are accurate for what they measure, but they only segment by Stripe-native dimensions: product, price, currency, and coupon.
The business dimensions that actually matter for decision-making live somewhere else:
- Customer segment (Enterprise, Mid-Market, SMB) is in your CRM
- Industry (Technology, Media, Healthcare) is in your CRM
- Deal source (inbound, outbound, partner) is in your CRM
- Account owner and customer health score are in your CRM
Stripe knows what someone pays. Your CRM knows who they are. Until those two datasets are in the same place, you cannot answer the questions that drive retention strategy.
This is not a Stripe limitation per se. Stripe is a billing system, not a customer intelligence platform. The gap exists because most teams treat billing data and CRM data as separate concerns, and the tools they use reinforce that separation.
What We Built: A Cross-Source Revenue Dashboard
We connected Stripe (subscription and billing data) and Salesforce (account metadata: segment, industry, plan tier) to Definite and asked Fi to build a dashboard combining both.
Here is what came back:
Top-line KPIs
| Metric | Value |
|---|---|
| Total MRR | $53,169 |
| ARR | $638,028 |
| Churn Rate | 33.3% |
| Active Accounts | 50 |
All from Stripe billing data, organized by the Salesforce account structure.
Churn by Customer Segment
This is where the cross-source join pays off. Stripe alone reports a single churn rate: 33.3%. When you break it down by CRM segment, the story changes completely:
| Segment | MRR | Active | Churned | Churn Rate | Avg MRR/Account |
|---|---|---|---|---|---|
| SMB | $19,553 | 18 | 7 | 28% | $1,086 |
| Enterprise | $17,953 | 14 | 11 | 44% | $1,282 |
| Mid-Market | $15,663 | 18 | 7 | 28% | $870 |
Enterprise accounts carry the highest average MRR ($1,282) but also the highest churn rate at 44%. That is a very different finding than "our churn is 33%." If your customer success team is allocating effort evenly across segments, they are underweighting the segment that costs the most to lose.
MRR by Industry
| Industry | MRR |
|---|---|
| Media | $25,974 |
| Technology | $18,463 |
| Retail | $3,984 |
| Logistics | $3,762 |
| Finance | $986 |
Media and Technology account for $44K of the $53K total. These are Salesforce fields applied to Stripe revenue data. No subscription analytics tool gives you this view out of the box.
Churn Rate by Industry
We asked Fi to add one more chart: churn rate broken down by industry. The results were stark.
| Industry | Churn Rate |
|---|---|
| Education | 60% |
| Government | 60% |
| Healthcare | 60% |
| Manufacturing | 60% |
| Energy | 60% |
| Finance | 30% |
| Logistics | 30% |
| Retail | 20% |
| Technology | 10% |
| Media | 10% |
Five industries are churning at 60%. Meanwhile, Media and Technology (the two biggest revenue drivers) are at 10%. That is a 6x difference hidden inside a single 33% average.
This is the kind of insight that changes resource allocation. If your sales team is prospecting equally across industries, they should know that Education and Government accounts churn at six times the rate of Technology accounts. If your customer success team is running the same playbook for every segment, they should know Enterprise is churning at 44% while SMB sits at 28%.
Why This Is Hard Without a Shared Database
There are three common approaches to getting segment-level Stripe metrics. None of them work particularly well.
Approach 1: Spreadsheet matching
Export Stripe subscriptions. Export your CRM accounts. Open a spreadsheet. Try to match them by email address or company name.
This fails for predictable reasons:
- Emails in Stripe often differ from CRM emails (billing@ vs. the contact's personal address)
- Company names have casing and spacing inconsistencies ("Acme Corp" vs. "acme corp" vs. "ACME")
- The match rate is rarely 100%, so your analysis always has holes
- It takes an afternoon, and you need to redo it every time someone asks for updated numbers
Approach 2: Subscription analytics tools
Tools like Baremetrics, ChartMogul, and ProfitWell connect directly to Stripe and give you MRR, churn, LTV, and cohort analysis. They are good at what they do.
But they only connect to Stripe (and sometimes a handful of payment processors). The moment you want to segment by a CRM dimension like industry or customer tier, you are back in the spreadsheet. ChartMogul recently added a CRM feature, but it is their own CRM, not a bridge to Salesforce or HubSpot data you already have.
For teams that only need Stripe-native breakdowns (by plan, by currency, by cohort month), these tools are fine. For teams that need CRM-enriched analysis, they leave a gap.
Approach 3: Build a data stack
Set up a data warehouse (Snowflake, BigQuery), an ETL tool (Fivetran, Airbyte) to sync Stripe and Salesforce into it, a transformation layer (dbt) to model the join, and a BI tool (Looker, Tableau) to visualize the result.
This approach works. It is also months of setup, multiple vendor contracts, and a data engineer to maintain it. For a Series A company that needs segment-level churn analysis before the next board meeting, it is overkill. (For a deeper look at what this stack actually costs, see our data stack cost guide or try the TCO calculator.)
What Definite does differently
Definite puts Stripe and Salesforce (or HubSpot, Attio, or whichever CRM you use) in the same database. Connecting each source takes a few minutes. Once both are synced, the cross-source join is just a question to Fi.
There is no spreadsheet matching, no separate ETL pipeline, and no multi-tool stack to assemble. The segment-level analysis we showed above was built by asking Fi a single question.
Why Stripe's MRR Number Might Not Match Yours
A related issue worth noting: Stripe's built-in MRR number may not match what you would calculate yourself. We covered this in depth in Calculating MRR From Raw Stripe Data, but the short version is that Stripe calculates MRR from subscription objects, which can diverge from actual invoiced revenue due to:
- Non-subscription line items that add revenue Stripe's MRR does not count
- Discount and coupon handling that may be applied at the invoice level, not the subscription level
- Annual plan normalization where Stripe may or may not divide annual subscriptions by 12 depending on your configuration
- Mid-cycle changes where upgrades, downgrades, and prorations create timing differences
If you are reporting MRR to investors, it is worth verifying whether Stripe's number matches your own definition. If you want to go deeper on the raw calculation, see the full post on Stripe MRR pitfalls.
Iterating on the Dashboard with AI
One advantage of building dashboards with an AI agent is iteration speed. In the video, after the initial dashboard was built, we asked Fi to add a new chart (ARR by plan tier over time). Fi queried the data, tested the results, and added the chart to the dashboard in under 30 seconds.
This matters because dashboards are never done on the first pass. The head of sales wants churn by industry. The CFO wants ARR by plan tier. The CEO wants a cohort view. With traditional BI tools, each request is a ticket. With Fi, it is a sentence.
Getting Started
If you have Stripe and a CRM and want segment-level metrics, the setup is straightforward:
- Connect Stripe in Definite (API key, takes about 2 minutes)
- Connect your CRM (Salesforce, HubSpot, Attio, or any of the 500+ connectors)
- Ask Fi to build the dashboard you need
Definite has a free tier that includes AI, dashboards, and two connectors. If you want to try what we showed in the video with your own data, that is enough to get started.
For teams already using Stripe Sigma and hitting its limitations (SQL-only, no CRM data, no AI), Definite is a natural next step.