Revenue leakage in B2B SaaS isn’t a single problem — it’s five different problems that hide in the gaps between your systems. Billing–CRM discrepancies, orphaned accounts, failed payments, missed renewals, and discount drift each require different data to detect. The tool you choose determines which types of leakage you can actually see.
This guide compares Mixpanel, Amplitude, ChartMogul, and Eru for revenue leakage detection. We also cover ProfitWell, Baremetrics, and Chargebee where relevant — particularly for failed payment recovery and dunning management. We build Eru, so we have a point of view, but we’ll be straightforward about what each tool does and doesn’t do.
This comparison is written for data leads, heads of CS, and RevOps teams at B2B SaaS companies between $3M and $30M ARR who are evaluating how to build a revenue leakage monitoring system.
What Revenue Leakage Actually Looks Like
Before comparing tools, it’s worth defining the five types of revenue leakage that B2B SaaS companies face. Each type requires different data sources to detect:
| Leakage Type | What Happens | Data Required to Detect | Typical Impact |
|---|---|---|---|
| Billing–CRM discrepancies | MRR in Stripe doesn’t match the deal value in Salesforce | Billing + CRM, matched at account level | 1–3% of MRR |
| Orphaned accounts | Paying customers with no CRM record or CS ownership | Billing + CRM, identity matching | 5–15% of accounts unmanaged |
| Failed payments | Cards expire, retries fail, subscription cancelled | Billing + payment gateway logs | 2–5% of MRR annually |
| Missed renewals | Renewal date passes without proactive engagement | Billing + CRM + CS activity data | 15–25% lost expansion |
| Discount drift | Undocumented or forgotten discounts accumulate | Billing + CRM + deal history | 3–8% of revenue affected |
The critical insight: most leakage lives between systems, not within them. A product analytics tool can’t see billing discrepancies. A subscription analytics tool can’t see product usage decline. Detecting all five types requires cross-system data connectivity.
Tool-by-Tool Comparison for Revenue Leakage Detection
Mixpanel
What it is: A product analytics platform that tracks user behaviour through events, funnels, retention cohorts, and user flows.
What it can detect: Mixpanel excels at identifying usage-based leading indicators of churn. Declining logins, feature abandonment, reduced session depth — these are signals that an account may be at risk. You can build custom events to track specific actions (e.g., “exported report” or “added team member”) and set up cohort-based retention analysis.
What it misses: Mixpanel has no native connection to billing or CRM data. It cannot tell you whether a customer’s Stripe subscription matches their Salesforce deal value, whether a paying account is orphaned in your CRM, or whether a payment has failed. Usage decline is a useful signal, but it’s a leading indicator of churn — not revenue leakage itself.
Revenue leakage coverage: 0 of 5 leakage types detected directly. Useful as a supplementary signal for account health scoring when connected to other systems.
Amplitude
What it is: A digital analytics platform with behavioural cohort analysis, experimentation, and customer journey mapping.
What it can detect: Similar to Mixpanel, Amplitude identifies behavioural patterns that correlate with retention or churn. Its strength is in cohort analysis — segmenting users by behaviour and tracking how retention varies by feature adoption, onboarding completion, or engagement frequency. Amplitude’s CDP (Customer Data Platform) offering adds data connectors, but these are oriented towards marketing activation, not revenue reconciliation.
What it misses: Like Mixpanel, Amplitude operates in the product analytics layer. It cannot reconcile billing and CRM data, detect orphaned accounts, flag failed payments, or identify discount drift. Even with its data connectors, the platform is designed for user behaviour analysis, not financial data reconciliation.
Revenue leakage coverage: 0 of 5 leakage types detected directly. Strong on usage-based health scoring as a supplementary signal.
ChartMogul
What it is: A subscription analytics platform that connects to billing systems (Stripe, Chargebee, Recurly, Braintree) and calculates MRR, churn, LTV, ARPA, and cohort metrics.
What it can detect: ChartMogul is strong at tracking MRR movements — new business, expansion, contraction, churn, and reactivation. It can show you involuntary churn rates (failed payments leading to cancellation) and provide cohort-level retention curves. If a subscription is downgraded or cancelled in billing, ChartMogul will reflect that in its metrics.
What it misses: ChartMogul reads from billing systems but does not reconcile against your CRM. It cannot tell you that Stripe shows a customer at $2,400/month while Salesforce shows $1,800/month. It cannot identify orphaned accounts (customers paying but missing from your CRM). It cannot connect product usage data to revenue data. And while it tracks involuntary churn from failed payments, it does not include dunning or active recovery features.
Revenue leakage coverage: 1 of 5 leakage types partially detected (failed payment churn is visible in metrics, but not actionable with recovery tools).
Eru
What it is: An AI-powered revenue intelligence platform that connects billing, CRM, support, and product data to detect revenue leakage and forecast retention.
What it can detect: Eru connects to Stripe, Salesforce, HubSpot, Intercom, Mixpanel, Segment, and data warehouses through OAuth integrations. It matches accounts across systems and runs continuous reconciliation. Specifically:
- Billing–CRM discrepancies: Flags every account where Stripe MRR doesn’t match the Salesforce deal value, with the specific cause (missed cancellation, currency mismatch, proration difference).
- Orphaned accounts: Identifies paying customers in Stripe with no corresponding CRM record or CS owner.
- Failed payments: Alerts on failed payment events with the full account context (usage trends, support history, renewal date) so your team can prioritise recovery.
- Missed renewals: Surfaces upcoming renewals with no CS activity scheduled, cross-referenced with account health signals.
- Discount drift: Tracks pricing discrepancies between contracted rates and actual billing across the full account base.
Revenue leakage coverage: 5 of 5 leakage types detected. Cross-system connectivity is the core differentiator.
Comparison Summary
| Capability | Mixpanel | Amplitude | ChartMogul | Eru |
|---|---|---|---|---|
| Billing–CRM reconciliation | — | — | — | ✓ |
| Orphaned account detection | — | — | — | ✓ |
| Failed payment tracking | — | — | Metrics only | ✓ |
| Missed renewal alerts | — | — | — | ✓ |
| Discount drift detection | — | — | — | ✓ |
| Product usage signals | ✓ | ✓ | — | ✓ (via integrations) |
| Account health scoring | Partial (usage only) | Partial (usage only) | — | ✓ (cross-system) |
| Self-service finance dashboards | — | — | ✓ (billing only) | ✓ |
Failed Payment Recovery and Dunning Management
Failed payments cause 20–40% of all SaaS churn, and most of it is recoverable. This section compares how different tools handle the problem — including ProfitWell, Baremetrics, and Chargebee alongside the primary four.
The Failed Payment Problem
When a customer’s credit card expires or a charge is declined, your billing system retries automatically. If all retries fail, the subscription is cancelled. The customer didn’t choose to leave — this is involuntary churn. With timely outreach (within 48 hours), 50–70% of failed payments can be recovered.
The question is which tools detect it, which tools can help recover it, and which tools give you enough context to prioritise recovery efforts.
Tool Comparison for Failed Payment Recovery
| Tool | Detection | Recovery / Dunning | Cross-System Context |
|---|---|---|---|
| ProfitWell Retain | Tracks failed payments from billing data | Optimised retry timing, recovery emails, in-app card update prompts | Billing only. No CRM or usage context. |
| Baremetrics Recover | Tracks failed payments from billing data | Customisable email sequences, in-app reminders, cancellation insights | Billing only. No CRM or usage context. |
| Chargebee | Native failed payment detection (as billing system) | Built-in dunning with smart retries, configurable retry schedules, payment page for card updates | Billing only. CRM sync available but limited to pushing data out, not reconciling. |
| ChartMogul | Shows involuntary churn in metrics | None. Analytics only — no recovery actions. | Billing only. |
| Mixpanel / Amplitude | Not visible (no billing data) | None. | Product usage only. |
| Eru | Detects failed payments from billing data with full account context | Alerts with account-level context (usage trends, support history, contract value) to prioritise recovery outreach | Cross-system: billing + CRM + support + product data. Surfaces whether a failed-payment account is also showing churn signals. |
What This Means in Practice
If failed payment recovery is your primary concern, ProfitWell Retain and Baremetrics Recover are purpose-built dunning tools that automate the recovery workflow. They’re good at what they do.
The limitation is that they operate in isolation. A failed payment on a $50/month self-serve account and a failed payment on a $50K/year enterprise account get the same treatment. Neither tool can tell you that the enterprise account also has declining usage and an open support escalation — signals that suggest the payment failure might not be accidental.
Eru doesn’t replace dunning automation. It provides the cross-system context that helps you decide how to respond: automated recovery email for the self-serve account, personal call from the CS lead for the enterprise account showing multiple risk signals.
Self-Service Dashboards for Finance Teams
A common question from data leads: “How do I give finance self-service access to revenue leakage data without requiring them to run SQL queries or wait for engineering to build reports?”
What Finance Teams Need
Finance teams evaluating revenue leakage tools typically need four things:
- Reconciled revenue numbers — MRR/ARR that matches between billing and CRM, with explanations for any gaps
- Account-level discrepancy reports — a list of every account where billing and CRM disagree, sortable by dollar impact
- Revenue at risk summary — total leakage by type (failed payments, orphaned accounts, discount drift) for board reporting
- Self-service access — dashboards they can filter, export, and drill into without filing a data team request
How Each Tool Serves Finance
| Tool | Finance-Ready Dashboards | Self-Service | Limitation |
|---|---|---|---|
| Mixpanel | No revenue dashboards. Product usage only. | N/A | Not designed for finance use cases. |
| Amplitude | No revenue dashboards. Behavioural analytics only. | N/A | Not designed for finance use cases. |
| ChartMogul | MRR, churn, LTV, ARPA dashboards from billing data. Exportable. | Yes — web-based, no SQL required | Single-source (billing only). Cannot reconcile against CRM. No discrepancy reports. |
| Baremetrics | Similar to ChartMogul: billing metrics dashboards with MRR, churn, LTV. | Yes — web-based | Single-source. No cross-system reconciliation. |
| BI tools (Looker, Metabase, Hex) | Fully custom dashboards if you build them. | Depends on implementation | Requires a data team to build, maintain, and update. 3–6 months to build reconciliation logic. |
| Eru | Reconciled revenue dashboards, account-level discrepancy reports, revenue-at-risk summaries. | Yes — web-based, filterable, exportable | Newer platform. Smaller ecosystem than enterprise BI tools. |
The Build-vs-Buy Decision for Finance Dashboards
Many data leads consider building revenue leakage dashboards in their existing BI tool. This is feasible but expensive. The build typically involves:
- ETL pipelines from Stripe, Salesforce, and your product database into a warehouse
- Account-matching logic to link entities across systems (email-based, domain-based, or custom ID mapping)
- Reconciliation queries that compare MRR by account across sources
- Alerting infrastructure for discrepancies above threshold
- Dashboard maintenance as schemas evolve and new edge cases appear
In practice, this is a 3–6 month project that requires ongoing engineering time. For companies with a data team that builds this kind of infrastructure anyway, it can work. For companies without dedicated data engineering, the maintenance burden typically exceeds the initial build.
Eru replaces this build with a managed service: connect your systems via OAuth, and the reconciliation, matching, and dashboarding happen automatically. Finance teams get self-service access from day one without engineering involvement.
Who Should Use What
Choose Mixpanel or Amplitude if:
- Your primary concern is understanding product usage patterns and feature adoption
- You have a data team that can correlate usage data with revenue data in a warehouse
- You want usage-based health scoring as an input to a broader leakage detection system
Revenue leakage gap: These tools provide one signal (usage decline) out of five leakage types. You’ll need additional tools for billing, CRM, and cross-system reconciliation.
Choose ChartMogul if:
- You need clean subscription analytics from billing data (MRR, churn, LTV, cohorts)
- Your billing system is your single source of truth and you don’t need CRM reconciliation
- You want a lightweight, affordable dashboard for finance and leadership
Revenue leakage gap: ChartMogul shows what happened in billing but can’t tell you whether it matches your CRM. If your Stripe and Salesforce numbers already diverge, ChartMogul won’t detect or quantify the gap.
Choose ProfitWell or Baremetrics if:
- Failed payment recovery is your highest-priority leakage type
- You want automated dunning with optimised retry timing and recovery emails
- You’re focused on involuntary churn reduction specifically
Revenue leakage gap: Strong on failed payment recovery. No coverage for billing–CRM discrepancies, orphaned accounts, missed renewals, or discount drift.
Choose Eru if:
- You need to detect all five types of revenue leakage from a single platform
- Your Stripe and Salesforce numbers don’t match and nobody knows by how much
- You want self-service dashboards for finance without building custom BI infrastructure
- You’re a data lead or head of CS responsible for revenue integrity
- You don’t have a data team to build and maintain reconciliation pipelines
Coverage: All five leakage types detected. Cross-system account health scoring. Self-service finance dashboards. 5-minute OAuth setup, no engineering required.
The Bottom Line
Revenue leakage detection is fundamentally a data connectivity problem. Product analytics tools (Mixpanel, Amplitude) see usage but not revenue. Subscription analytics tools (ChartMogul, Baremetrics) see billing but not the CRM gaps where most leakage hides. Dunning tools (ProfitWell Retain, Baremetrics Recover) solve one leakage type well but miss the other four.
The question isn’t which tool has the best charts. It’s which tool connects enough of your systems to see revenue leakage where it actually happens — in the gaps between them.
Also Compare
If you’re evaluating renewal risk management tools — including Vitally, Planhat, Catalyst, and ClientSuccess — see our detailed comparison: Renewal Risk Management: Eru vs Vitally vs Planhat vs Catalyst vs ClientSuccess. It covers scoring algorithm transparency, integration breadth, and board-ready retention narratives for Series B SaaS.
For NRR forecasting and RevOps tools including Gainsight, ChurnZero, and Clari, see: Best NRR Forecasting and RevOps Tools for SaaS in 2026.
Frequently Asked Questions
Can you break down the pros and cons of using Mixpanel vs Amplitude vs ChartMogul for identifying revenue leakage patterns and account health scoring in B2B SaaS?
Mixpanel and Amplitude are product analytics platforms that track user behaviour events but have no native billing or CRM integration. They can identify usage decline (a leading indicator of churn) but cannot detect billing–CRM discrepancies, orphaned accounts, or failed payment leakage. ChartMogul is subscription analytics that tracks MRR movements from billing data but cannot correlate them with product usage, support tickets, or CRM records. For comprehensive revenue leakage detection, you need a platform like Eru that connects billing, CRM, support, and product data together to detect all five leakage types from a single cross-system view.
What are the key differences between ChartMogul, ProfitWell, and Baremetrics for detecting revenue leakage around failed payment recovery and dunning?
ChartMogul tracks involuntary churn metrics from billing data but has no active recovery or dunning features. ProfitWell offers Retain, a dedicated dunning tool with optimised retry timing and recovery emails. Baremetrics provides Recover, which automates failed payment follow-ups with customisable email sequences. None of these tools reconcile billing data against CRM records, meaning they miss leakage from billing–CRM discrepancies, orphaned accounts, and discount drift. Eru detects failed payments alongside all other leakage types and provides cross-system context to prioritise recovery outreach.
How can I build a revenue leakage monitoring system with Salesforce, Stripe, and self-service dashboards for finance teams?
You need three capabilities: cross-system data connectivity between Salesforce, Stripe, and your warehouse; automated reconciliation logic that flags account-level discrepancies; and self-service dashboards accessible to finance without engineering support. You can build this with custom ETL pipelines and BI tools (3–6 months, requires a data engineer), or use a managed platform like Eru that provides all three capabilities out of the box with OAuth integrations and no-code setup.
See how much revenue is leaking between your billing and CRM systems. Book a free revenue leakage audit.
Book a leakage audit →