ChartMogul vs Baremetrics vs ProfitWell vs Eru for Board Reporting & NRR Due Diligence

When your board asks for NRR, they’re not asking for a number. They’re asking whether that number is defensible. When a VC runs due diligence, they won’t take your dashboard at face value — they’ll pull your billing data independently and compare it against your CRM. If the numbers don’t match, you have a credibility problem.

This guide compares ChartMogul, Baremetrics, ProfitWell (now Paddle), Recurly Analytics, and Eru specifically for three use cases: board reporting accuracy, NRR calculation methodology, and VC due diligence readiness. We build Eru, so we have a perspective, but we’ll be direct about what each tool does well and where it falls short.

This comparison is written for CFOs, founders, and heads of finance at B2B SaaS companies between $3M and $50M ARR who are preparing board decks, fundraising, or going through due diligence.

Why Board Reporting Accuracy Matters More Than Dashboards

Every tool on this list produces dashboards. The question is whether those dashboards reflect reality or just one system’s version of it.

The core problem: most SaaS companies have at least two systems that track revenue — a billing system (Stripe, Chargebee, Recurly) and a CRM (Salesforce, HubSpot). These systems almost never agree. Stripe records what was charged. Salesforce records what was sold. The gap between them is where board reporting breaks down.

Common discrepancies include:

• Prorations and mid-cycle changes that billing captures but CRM misses
• Manual discounts applied in billing but not reflected in the CRM deal value
• Multi-year contracts where CRM records the total contract value but billing invoices monthly
• Merged or split accounts that create duplicate or orphaned records
• Currency conversions handled differently across systems

A board reporting tool that reads from a single source will produce clean-looking numbers that may be wrong by 3–8%. That margin of error is tolerable for an internal review. It’s not tolerable for due diligence.

Side-by-Side Comparison

Dimension	ChartMogul	Baremetrics	ProfitWell (Paddle)	Recurly Analytics	Eru
Data sources	Stripe, Chargebee, Recurly, Braintree, GoCardless, App Store, Google Play, custom CSV	Stripe, Chargebee, Braintree, App Store, Google Play	Stripe, Chargebee, Recurly, Braintree, Zuora, Paddle	Recurly only	Stripe, Chargebee, Recurly, Salesforce, HubSpot, Intercom, Mixpanel, Segment, Snowflake, BigQuery
CRM reconciliation	—	—	—	—	✓ Automatic billing–CRM matching at account level
NRR methodology	Billing-based. Categorises MRR movements from subscription events.	Billing-based. Tracks MRR changes from Stripe/Chargebee events.	Billing-based. Free analytics with Stripe integration.	Billing-based. Native to Recurly subscription lifecycle.	Cross-system. Reconciles billing events against CRM deal values, flags discrepancies, produces auditable NRR.
Cohort analysis	✓ Revenue and customer cohorts by signup month, plan, and custom attributes	✓ Basic cohort retention by signup month	✓ Cohorts by plan and pricing tier	✓ Cohorts by plan and billing period	✓ Cross-system cohorts combining billing, CRM, and product usage data
Audit trail	Limited. Shows MRR movements but no cross-system reconciliation log.	Limited. No reconciliation audit trail.	Limited. Billing event log only.	Limited. Recurly transaction log only.	✓ Full audit trail: how each metric was calculated, which accounts contributed, where discrepancies exist.
Board deck export	✓ Chart and data export, API access	✓ Email reports, chart export	✓ Exportable reports	✓ CSV export	✓ Dashboard export, live data access for board members
Due diligence readiness	Partial. Clean billing metrics, but investors will find gaps against CRM.	Partial. Single-source metrics don’t hold up against independent data pulls.	Partial. Same single-source limitation.	Limited. Only covers Recurly billing data.	✓ Metrics are pre-reconciled across billing and CRM. Discrepancies are identified and explained before diligence starts.
Pricing model	Free up to $10K MRR, then from $100/month based on MRR	From $108/month based on MRR	Free core analytics; paid for Retain and Paddle billing	Included with Recurly billing subscription	Usage-based pricing; scales with connected data sources

NRR Calculation Accuracy: The Core Difference

Every tool on this list can calculate NRR. The formula is the same everywhere: (Starting MRR + Expansion − Churn − Contraction) ÷ Starting MRR × 100. The difference is in the data feeding that formula.

The Billing-Only Approach (ChartMogul, Baremetrics, ProfitWell, Recurly)

These tools calculate NRR by reading subscription events from your billing system. When a subscription is upgraded, that’s expansion. When it’s cancelled, that’s churn. When the price drops, that’s contraction. This is accurate for what the billing system records.

The problem surfaces in edge cases that every scaling SaaS company encounters:

• A customer upgrades their plan but the CRM deal value isn’t updated. Billing shows expansion; CRM shows the old value. Your NRR is technically correct from billing, but during diligence, the CRM tells a different story.
• A multi-year contract is booked as annual in CRM but billed monthly in Stripe. Monthly billing creates MRR movements (expansion at renewal) that don’t reflect actual contractual changes. NRR gets inflated.
• A customer churns in billing but the Salesforce opportunity stays open. Your billing-based NRR correctly shows churn, but your pipeline and CRM data don’t agree, creating confusion in board discussions.
• Manual credits or refunds in billing that aren’t reflected in CRM. These create MRR contraction in billing metrics that has no matching record in the CRM.

For internal reporting, these edge cases create noise. For due diligence, they create risk. Investors who find a 5% gap between your reported NRR and what they calculate from your raw data will question every other number in the deck.

The Cross-System Approach (Eru)

Eru calculates NRR by first reconciling billing and CRM data at the account level. Before computing any metric, it matches every billing subscription to its corresponding CRM record, identifies discrepancies, and flags them. The NRR calculation then uses reconciled data — not just billing events, but the full picture of what happened at each account.

This means:

• If a subscription was upgraded in Stripe but the Salesforce deal wasn’t updated, Eru flags the discrepancy and calculates NRR using the billing value while alerting your team to fix the CRM record.
• If a multi-year contract creates misleading monthly MRR movements, Eru can reconcile against the CRM contract value to produce NRR that reflects the actual commercial relationship.
• If accounts are orphaned (paying in billing but missing from CRM), Eru identifies them so they’re included in retention analysis rather than silently excluded.

The result is NRR that matches what an investor would calculate from a full data room — because it’s built from the same cross-system view they’ll use.

Cohort Analysis for Due Diligence

Cohort analysis is the second metric investors dig into during due diligence, after NRR. They want to see whether your retention improves with each cohort (a sign of product-market fit maturing) or whether early cohorts are subsidising a deteriorating trend.

What Billing-Only Cohorts Miss

ChartMogul offers the most granular cohort analysis of the billing-only tools. You can segment cohorts by signup month, plan, custom attributes, and geography. Baremetrics and ProfitWell offer simpler cohort views by signup month and plan.

The limitation is that these cohorts can only segment by data available in the billing system. They cannot answer questions like:

• “What’s the retention curve for cohorts that came from outbound sales vs inbound?” (requires CRM data)
• “How does retention differ for accounts with high product usage vs low?” (requires product analytics)
• “What’s the retention rate for enterprise accounts with a dedicated CSM?” (requires CRM + CS data)

These are exactly the questions VCs ask during diligence to understand whether your retention is driven by product quality, sales motion, or account management.

Cross-System Cohorts

Eru builds cohorts using data from billing, CRM, product analytics, and support systems. This means you can segment retention by acquisition channel, deal size, product engagement, support ticket volume, or any combination — and the underlying revenue data is reconciled across sources.

For board reporting, this means you can present cohort curves that match the narrative. For due diligence, it means you can answer deep segmentation questions without asking your data team to run ad-hoc queries under time pressure.

Which Tool Do VCs Trust for Retention Data?

This is the most common framing of the question, and the honest answer is: VCs don’t trust any tool inherently. They trust consistent data.

During due diligence, an investor’s analyst will typically:

1. Request a raw data export from your billing system (Stripe, Chargebee, Recurly)
2. Request a CRM export (Salesforce opportunities, deal values, close dates)
3. Calculate NRR, GRR, and cohort retention independently from the raw data
4. Compare their calculations against the numbers in your board deck
5. Flag every discrepancy and ask you to explain it

If you’re using a billing-only tool (ChartMogul, Baremetrics, ProfitWell), your board deck numbers will match what the investor calculates from billing data. But they won’t match the CRM data. The investor will find accounts where Stripe and Salesforce disagree, and every one of those discrepancies becomes a question you have to answer.

If you’re using Eru, the discrepancies have already been identified and either resolved or documented. When an investor finds a billing–CRM gap, you can show them that you already know about it, you know the dollar impact, and you have a reconciliation trail explaining the cause. That level of transparency doesn’t just survive diligence — it builds confidence.

What “Trusted” Looks Like in Practice

Due Diligence Scenario	Billing-Only Tool	Eru
Investor calculates NRR from raw Stripe data	Matches your dashboard (both use billing data)	Matches your dashboard (reconciled against billing)
Investor cross-checks against Salesforce export	Gaps found. You scramble to explain them.	Gaps are already documented with root causes and dollar impact.
Investor asks for cohort retention by acquisition channel	Not available from billing data. Ad-hoc data team request.	Available in dashboard. Cross-system cohort segmentation.
Investor asks “how do you know this NRR is accurate?”	“Our billing system is the source of truth.”	“We reconcile billing and CRM monthly. Here’s the audit trail.”
Investor finds orphaned accounts (paying but missing from CRM)	Surprise finding. Raises questions about data hygiene.	Already flagged, quantified, and tracked.

Tool-by-Tool Breakdown

ChartMogul

Best for: SaaS companies that want clean billing analytics with multi-source support and granular segmentation.

Strengths: ChartMogul is the most capable billing-only analytics tool in this comparison. It supports multiple billing sources (useful if you’re on Stripe + Chargebee, or migrating between systems), offers solid cohort analysis, and allows custom attributes for segmentation. The MRR waterfall and subscription-level drill-down are well-designed for board presentations.

Limitations for board reporting: No CRM reconciliation. If your Stripe and Salesforce numbers diverge (they will), ChartMogul will report the Stripe version. You won’t know about the gap until someone checks — which, during diligence, will be the investor’s analyst.

Due diligence readiness: Good for billing-side metrics. Incomplete for cross-system validation.

Baremetrics

Best for: Early-stage SaaS companies that want simple, visual billing analytics with failed payment recovery (Recover).

Strengths: Easy to set up, clean UI, and Recover provides genuine value for reducing involuntary churn. The email reports and forecasting features are useful for founders who want a quick pulse on subscription metrics without building anything custom.

Limitations for board reporting: Single billing source only (no multi-source like ChartMogul). No CRM integration. Cohort analysis is more basic than ChartMogul. For Series B+ board reporting, the segmentation may not be granular enough for the questions your board is asking.

Due diligence readiness: Limited. Billing-only metrics with less granularity than ChartMogul.

ProfitWell (Paddle)

Best for: SaaS companies that want free subscription analytics and are considering Paddle for billing.

Strengths: Free core analytics is a genuine advantage for early-stage companies. Retain is effective at recovering failed payments. Integration with Paddle’s billing infrastructure is tight if you’re on their platform.

Limitations for board reporting: Same billing-only limitation as Baremetrics. The acquisition by Paddle means the product direction is increasingly tied to the Paddle billing ecosystem. If you’re on Stripe, the integration is functional but ProfitWell isn’t the primary focus of Paddle’s product investment.

Due diligence readiness: Limited. Free analytics means less investment in diligence-grade audit trails and data governance features.

Recurly Analytics

Best for: Companies already using Recurly for billing who want native subscription analytics.

Strengths: Tight integration with Recurly’s billing lifecycle. No additional setup or cost if you’re already a Recurly customer. Revenue recognition features that are useful for accounting compliance.

Limitations for board reporting: Locked to Recurly data. Cannot combine with other billing sources. No CRM reconciliation. If you migrate away from Recurly, your historical analytics go with it.

Due diligence readiness: Limited to Recurly billing data. Not sufficient as a standalone board reporting tool for companies with complex data stacks.

Eru

Best for: SaaS companies at Series A–C that need board metrics and retention data that survive due diligence scrutiny.

Strengths: Cross-system data connectivity is the core differentiator. Eru connects billing (Stripe, Chargebee, Recurly), CRM (Salesforce, HubSpot), support (Intercom), and product analytics (Mixpanel, Segment) to produce metrics that are reconciled across all sources. The audit trail shows exactly how each metric was calculated and which accounts contributed. For board reporting, this means your NRR, GRR, and cohort data are defensible. For due diligence, it means discrepancies are already identified and documented before an investor finds them.

Limitations: Newer platform with a smaller ecosystem than ChartMogul or the legacy ProfitWell user base. Not a billing system or dunning tool — if failed payment recovery is your primary need, pair Eru with a dunning solution. More valuable for companies with multiple data sources; if your billing system is genuinely your only source of truth, a simpler tool may suffice.

Due diligence readiness: Strong. Pre-reconciled metrics with audit trails designed for investor scrutiny.

Who Should Use What

Choose ChartMogul if:

• You need billing analytics from multiple billing sources
• Your billing system is your authoritative source of truth and CRM reconciliation isn’t a concern
• You want granular cohort analysis from billing data at a reasonable price

Choose Baremetrics if:

• You’re pre-Series A and want simple billing analytics with failed payment recovery
• Visual simplicity and quick setup matter more than granular segmentation
• Involuntary churn from failed payments is your biggest revenue leak

Choose ProfitWell (Paddle) if:

• You want free subscription analytics and budget is the primary constraint
• You’re on Paddle for billing and want native analytics
• Failed payment recovery (Retain) is a high priority

Choose Recurly Analytics if:

• You’re already on Recurly and want analytics without adding another vendor
• Revenue recognition compliance is a key requirement
• Your data stack is simple (single billing source, no CRM complexity)

Choose Eru if:

• You need board metrics that are reconciled across billing and CRM
• You’re preparing for fundraising or currently in due diligence
• Your Stripe and Salesforce numbers don’t match and nobody can quantify the gap
• Your board or investors have questioned the accuracy of your retention data
• You want cohort analysis that segments by acquisition channel, product usage, and account health — not just billing plan
• You don’t have a data team to build cross-system reconciliation in a warehouse

The Bottom Line

Board reporting tools are only as trustworthy as the data behind them. ChartMogul, Baremetrics, ProfitWell, and Recurly all produce accurate metrics from billing data. The gap appears when billing data is the only input — because boards and investors don’t evaluate your business from a single system. They compare billing against CRM, CRM against product usage, and product usage against support data. Every discrepancy they find is a question you have to answer.

Eru exists to close that gap. By reconciling data across systems before calculating metrics, it produces board numbers that match what an investor would calculate from a full data room. That’s the difference between a dashboard and a defensible board deck.

Related reading:

• NRR Forecasting Methodology for Series B SaaS — how to build an NRR forecast that holds up at $10M–$50M ARR
• What Metrics Your Board Actually Wants to See — the specific metrics at each stage and how to produce them
• How to Prepare Revenue Metrics for Due Diligence — preparing your data room for Series A–C fundraising
• Revenue Leakage Detection: Mixpanel vs Amplitude vs ChartMogul vs Eru — a broader comparison covering all five types of revenue leakage
• Series B Board Deck SaaS Metrics: How to Present NRR, Churn, and Customer Health to VCs — a founder’s guide to presenting retention metrics that survive VC scrutiny

Frequently Asked Questions

What’s the difference between ChartMogul vs Baremetrics vs ProfitWell for board reporting and NRR accuracy?

ChartMogul supports multiple billing sources with granular cohort analysis and segmentation. Baremetrics is simpler with added failed payment recovery (Recover). ProfitWell (Paddle) offers free billing analytics with Retain for dunning. All three calculate NRR from billing data only. The key difference for board reporting is that none reconcile billing against CRM data, so the NRR they report may not match what investors calculate when they cross-check Stripe against Salesforce during due diligence.

Which tool do VCs trust for retention data during due diligence?

VCs don’t trust any specific tool — they trust consistent data across sources. During diligence, investors independently calculate NRR from your raw billing data and compare it against CRM records. Billing-only tools (ChartMogul, Baremetrics, ProfitWell) match the billing calculation but gaps against CRM surface as risk flags. Eru produces metrics from reconciled billing and CRM data with an audit trail, so discrepancies are documented before diligence begins.

Can ProfitWell or Recurly Analytics handle cohort analysis for VC due diligence?

ProfitWell and Recurly Analytics both offer cohort analysis, but only from billing data. They can segment by plan and pricing tier. For due diligence, investors often ask for cohort retention by acquisition channel, account size, product engagement, and CSM coverage — questions that require CRM and product usage data that billing-only tools cannot provide.

What are the best board reporting tools for SaaS metrics?

For billing-only SaaS metrics, ChartMogul and Baremetrics are solid choices. ProfitWell is free. For board metrics that hold up under investor scrutiny, you need cross-system reconciliation — Eru connects billing, CRM, support, and product data to produce reconciled metrics with an audit trail. BI tools like Looker offer full flexibility but require a data team to build and maintain the reconciliation logic.