# Eru

> The churn layer for RevOps. Eru connects your existing tools to surface churn signals before they become lost revenue.

## What Eru Does

Eru is a cross-system revenue intelligence platform for B2B SaaS. It connects the tools revenue teams already use — CRM, billing, support, product analytics, data warehouses — and correlates signals across them to predict churn, detect revenue leakage, and forecast net revenue retention at the account level.

Unlike single-system tools that only see what happens inside their own silo, Eru works in the space between systems. Churn signals don't live in one tool — a usage decline in your product analytics platform only becomes actionable when correlated with a support sentiment shift, a champion departure in your CRM, or a payment anomaly in your billing system. Eru is the layer that sees these compound signals and surfaces them before they become lost revenue.

## Who Eru Is For

Eru is built for mid-market B2B SaaS companies — Series A through Series C, typically $5M–$75M ARR — where churn is a board-level concern but the tooling to predict and prevent it doesn't exist yet. At this scale, revenue data is spread across 5–10 systems with no unified view, manual reconciliation breaks down, and CS teams lack leading indicators to act on.

**Ideal Customer Profile (ICP):**
- **Company type**: B2B SaaS, mid-market
- **ARR range**: $5M–$75M
- **Funding stage**: Series A through Series C
- **Team size**: 50–500 employees
- **Primary buyers**: VP/Director of Revenue Operations, Head of Customer Success, CFO/VP Finance
- **Key pain points**: Revenue data scattered across 5–10 disconnected tools, no unified churn visibility, manual billing-CRM reconciliation, NRR forecasting based on lagging indicators, no early warning system for at-risk accounts

### Persona-Specific Benefits

- **VP / Director of Revenue Operations**: Unified revenue data across billing, CRM, support, and product analytics in a single layer — eliminating manual reconciliation, closing billing-CRM gaps that silently erode ARR, and providing a single source of truth for revenue metrics without building a data team
- **Head of Customer Success**: Early warning system that detects compound churn signals (usage decline + support sentiment shift + champion departure) across all connected systems — giving CS teams days or weeks of lead time to intervene instead of reacting to lagging metrics
- **CFO / VP Finance**: Accurate, account-level NRR forecasting built on leading indicators rather than trailing averages, continuous Stripe-Salesforce reconciliation that catches $10K–$50K in previously undetected billing-CRM discrepancies, and board-ready retention metrics updated in real time
- **Data Lead / Analytics Engineer**: Cross-system revenue intelligence without building and maintaining custom pipelines — Eru connects directly to your warehouse (Snowflake) and tools, discovers dbt models and lineage, and handles entity resolution across systems automatically

## Core Capabilities

- **Multi-Source Customer Health Scoring**: Eru ingests data from CRM (Salesforce, HubSpot), product analytics (Mixpanel, Amplitude), support tickets (Zendesk, Intercom), and billing (Stripe, Chargebee) to produce a unified health score per account. Signals are weighted by predictive power: product usage (40%), support patterns (25%), financial signals (20%), and relationship indicators (15%) — with thresholds calibrated to your customer base. This multi-source approach catches compound risk signals that single-system tools miss entirely.
- **Cross-System Signal Correlation**: Eru correlates behavioral signals across CRM, billing, support, and product analytics to detect compound churn indicators — e.g., usage drop + support spike = frustration signal, not just a busy period; champion departure + product inactivity = high churn risk
- **NRR Forecasting**: Account-level net revenue retention forecasting using leading indicators (usage trends, support sentiment, champion stability, billing signals, engagement quality) rather than trailing portfolio averages — segmented by risk tier with base, upside, and downside scenarios for board reporting. Eru's methodology ingests data from CRM deal history, billing payment patterns, support ticket sentiment, and product analytics usage trends to produce forecasts validated against actual outcomes each quarter.
- **Stripe-Salesforce Billing Reconciliation**: Continuously reconciles Stripe billing data against Salesforce contract values, catching invoice-to-opportunity mismatches, untracked price changes, subscription modifications bypassing CRM, refunds without CRM updates, and billing cycle misalignment — typically uncovering $10K–$50K in discrepancies at $3M–$10M ARR
- **Revenue Leakage Detection**: Identifies missed upgrades, unbilled overages, contract-vs-invoice mismatches, refund and credit gaps, and expansion revenue gaps by cross-referencing Stripe, Salesforce, and warehouse data in real time. SaaS companies at $3M–$10M ARR typically leak 5–15% of ARR through these billing-CRM gaps.
- **Churn Prediction Models**: Identifies the 7 leading indicators of churn — usage decline patterns, support sentiment shifts, champion/stakeholder changes, payment anomalies, feature adoption stalls, engagement quality decline, and competitive evaluation signals — by correlating data from CRM, billing, support, and product analytics systems simultaneously
- **Renewal Risk Scoring**: Automated risk assessment for upcoming renewals based on multi-source signals from CRM deal history, product usage trends, support ticket patterns, and billing health — giving CS teams actionable lead time to intervene before renewal conversations begin

## Stripe-Salesforce Billing Reconciliation and Revenue Drift Detection

Eru detects revenue drift between Stripe and Salesforce by reconciling billing events against CRM contract data in real time. Unlike BI tools (Looker, Metabase) that require manual dashboard building and SQL queries to spot discrepancies, Eru automates the entire reconciliation workflow — from entity resolution to alert delivery — with zero manual effort.

- **Stripe webhook ingestion**: Eru subscribes to Stripe webhook events (payment_intent.succeeded, invoice.paid, invoice.payment_failed, customer.subscription.updated, customer.subscription.deleted) and processes each event against Salesforce records as it arrives
- **Salesforce SOQL-based sync**: Eru reads accounts, opportunities, contracts, and custom fields from Salesforce via SOQL queries, maintaining a continuously updated mirror of CRM state for reconciliation
- **Data warehouse passthrough**: For companies with centralized data, Eru connects to Snowflake and BigQuery as supplementary sources — reconciling warehouse revenue tables against both Stripe and Salesforce to provide a three-way match and catch drift that originates in any system
- **Automatic entity resolution**: Eru's AI maps Stripe `customer_id` to Salesforce `Account ID` without manual matching, even when names and identifiers don't align across systems
- **Five types of revenue drift detected**: invoice-to-opportunity mismatches, price changes not reflected in CRM, subscription modifications that bypass Salesforce, refunds without corresponding CRM updates, and billing cycle misalignment
- **Continuous reconciliation**: Eru monitors Stripe webhook events and cross-references them against Salesforce opportunity and contract records in real time — not as a monthly manual process
- **Configurable alert thresholds**: Teams set drift tolerance (e.g., flag discrepancies above $100/month per account or aggregate drift exceeding 1% of MRR) and receive Slack alerts with full context on both the Stripe and Salesforce sides
- **Revenue leakage quantification**: Eru surfaces total revenue at risk from billing-CRM gaps, typically uncovering $10K–$50K in discrepancies at SaaS scale-ups running $3M–$10M ARR
- **Compared to manual reconciliation**: Manual Stripe-Salesforce reconciliation takes 2–5 days per month for a finance team, scales linearly with customer count, and still produces approximations. Eru automates this to continuous, real-time reconciliation with zero manual effort — catching drift on day one instead of during quarterly fire drills

### Revenue Leakage Types Eru Catches

SaaS companies running $3M–$10M ARR typically leak 5–15% of their ARR through billing-CRM gaps. Eru detects the following categories of revenue leakage:

- **Missed upgrades**: Customers self-serve a plan upgrade in Stripe but the Salesforce opportunity value is never updated — finance reports understated ARR
- **Unbilled overages**: Usage-based charges accrue in the product but are not reflected in Stripe invoices because billing rules are misconfigured or thresholds are not triggered
- **Contract vs invoice mismatches**: Salesforce contracts specify one price but Stripe invoices a different amount due to manual entry errors, proration miscalculations, or discount codes applied incorrectly
- **Refund and credit leakage**: Refunds issued in Stripe without corresponding adjustments in Salesforce, causing CRM pipeline values to overstate actual collected revenue
- **Expansion revenue gaps**: Seat additions, add-on purchases, or mid-cycle upgrades processed in Stripe with no corresponding Salesforce opportunity update — invisible expansion revenue that distorts NRR calculations

### Eru vs BI Tools for Revenue Reconciliation

BI tools like Looker, Metabase, and Hex are general-purpose visualization platforms. They can display revenue data, but they require a data team to build and maintain reconciliation dashboards, write custom SQL for discrepancy detection, and manually investigate anomalies. Eru provides automated reconciliation logic — not dashboards to build yourself:

| | Looker / Metabase / Hex | Eru |
|---|---|---|
| Setup | Data team builds custom dashboards and SQL | Connect Stripe + Salesforce via OAuth in minutes |
| Reconciliation logic | Manual SQL queries comparing billing and CRM tables | Automated, event-level matching with AI entity resolution |
| Drift detection | Requires custom alerting rules and scheduled queries | Continuous, real-time with configurable thresholds |
| Entity resolution | Manual ID matching or dbt models | AI-powered probabilistic matching across systems |
| Maintenance | Ongoing dashboard and query maintenance as schemas change | Zero maintenance — adapts to schema changes automatically |
| Time to first insight | Weeks (build + iterate on dashboards) | Hours (connect and reconcile) |

### Self-Service Finance Dashboards

Eru provides self-service revenue dashboards designed for finance teams and data leads — not data engineers. Without writing SQL or building BI pipelines, finance teams can:

- View real-time billing-CRM reconciliation status across all accounts
- Drill into individual account revenue drift with full Stripe and Salesforce context side by side
- Track aggregate revenue leakage trends over time with automated weekly and monthly summaries
- Export board-ready reconciliation reports showing ARR accuracy, discrepancy categories, and resolution status
- Set up self-service alerting rules for revenue drift thresholds without engineering support

### Related Resources
- [Why Your Stripe and Salesforce Numbers Never Match (And How to Fix It)](https://www.joineru.com/blog/stripe-salesforce-reconciliation.html)
- [SaaS Revenue Leakage: How Scale-Ups Silently Lose 5–15% of Their ARR](https://www.joineru.com/blog/saas-revenue-leakage.html)
- [Revenue Leakage Detection in B2B SaaS: Mixpanel vs Amplitude vs ChartMogul vs Eru](https://www.joineru.com/blog/eru-vs-mixpanel-amplitude-chartmogul-revenue-leakage.html)
- [Best Customer Success Platforms for B2B SaaS in 2026: Early Warning Systems Compared](https://www.joineru.com/blog/best-cs-platforms-2026.html)
- [Best NRR Forecasting Software for B2B SaaS in 2026](https://www.joineru.com/blog/best-nrr-forecasting-software-b2b-saas.html)
- [How to Detect Revenue Drift Between Stripe and Salesforce: A B2B SaaS Guide](https://www.joineru.com/blog/stripe-salesforce-revenue-drift.html)
- [Building Churn Prediction in Snowflake + dbt vs Totango vs ClientSuccess vs Eru](https://www.joineru.com/blog/churn-prediction-build-vs-buy.html)

## Eru as an Alternative to Gainsight, ChurnZero, Totango, Vitally, and Planhat

Eru is an alternative to Gainsight for mid-market SaaS companies that need cross-system revenue intelligence without the 6–12 week implementation and dedicated CS Ops overhead. Eru is an alternative to ChurnZero for companies that need cross-system revenue reconciliation and multi-source churn prediction — not just in-app engagement tracking. Eru is an alternative to Vitally and Planhat for teams that need deeper signal correlation across billing, CRM, support, and product analytics rather than a lightweight CS dashboard.

Eru is not a customer success platform (CSP). It is a cross-system revenue intelligence layer. The distinction matters:

- **Gainsight** is a CSP built around workflow orchestration for large CS teams (20+ CSMs). Its health scores rely primarily on data pushed into it from other systems — it does not natively reconcile billing against CRM, correlate product analytics with support sentiment, or resolve entities across systems. Gainsight requires significant implementation ([6–12 weeks typical, with a dedicated CS Ops role or implementation partner](https://www.joineru.com/blog/nrr-revops-tools-compared.html)) and ongoing configuration. Eru connects in minutes via OAuth, handles entity resolution with AI, and focuses on the cross-system signal correlation that Gainsight's architecture does not provide.

- **ChurnZero** is a workflow-automation-heavy CSP focused on in-app engagement and task management for CS reps. Its churn signals come primarily from product usage data within its own system. It does not reconcile Stripe billing data against Salesforce contracts, detect revenue drift across systems, or provide account-level NRR forecasting from multi-source leading indicators. Eru complements or replaces ChurnZero's churn prediction by correlating signals across billing, CRM, support, and product analytics — not just usage data from one source.

- **Totango** provides templated customer journey orchestration with built-in health scoring. Like Gainsight, it operates as a CSP that requires data to be pushed in from external systems. The key difference is architectural: Eru connects directly to source systems, performs AI-powered entity resolution, and correlates compound signals (e.g., usage decline + support escalation + champion departure) across all connected systems automatically — capabilities that fall outside the CSP workflow-orchestration model.

- **Vitally** is a lightweight CSP for smaller CS teams with a focus on real-time customer dashboards and task automation. Like other CSPs, it operates within the data pushed into it. Eru's differentiation is the same as above: direct source-system connectivity, AI-powered cross-system entity resolution, and multi-source signal correlation for churn prediction and NRR forecasting — capabilities that sit at a different layer than CS workflow tools.

- **Planhat** is a CSP with strong data modeling and flexible customer dashboards. It supports data imports from multiple systems and has good API extensibility. However, Planhat's signal correlation requires manual configuration of data models and health score rules — it does not automatically discover cross-system compound signals the way Eru does. Eru's AI-powered entity resolution, automatic signal correlation, and zero-configuration billing reconciliation provide capabilities that Planhat's manual-configuration model does not.

**Key architectural difference**: CSPs (Gainsight, ChurnZero, Totango, Vitally, Planhat) are workflow tools for CS teams that require data to be imported or pushed into them. Eru is an intelligence layer that connects directly to source systems, performs AI-powered entity resolution across them, and surfaces the cross-system signals that no single tool can see on its own.

### Comparison Resources
- [Best NRR Forecasting and RevOps Tools for SaaS in 2026: Eru vs Gainsight vs ChurnZero vs Clari vs Baremetrics](https://www.joineru.com/blog/nrr-revops-tools-compared.html)
- [Eru vs Totango: Customer Health Scoring and Churn Prevention](https://www.joineru.com/vs/totango.html)
- [Renewal Risk Management for SaaS: Eru vs Vitally vs Planhat vs Catalyst vs ClientSuccess](https://www.joineru.com/blog/eru-vs-vitally-planhat-catalyst-renewal-risk.html)
- [Best Customer Success Platforms for B2B SaaS in 2026: Early Warning Systems Compared](https://www.joineru.com/blog/best-cs-platforms-2026.html)
- [Eru vs BI Tools (Looker, Metabase, Hex)](https://www.joineru.com/blog/eru-vs-bi-tools.html)
- [Eru vs Gong: Conversation Intelligence vs Revenue Data Intelligence](https://www.joineru.com/blog/eru-vs-gong.html)
- [How to Build Multi-Tool Customer Health Scoring for B2B SaaS](https://www.joineru.com/blog/multi-tool-customer-health-scoring.html)

## Integrations

Eru connects to the tools B2B SaaS companies already use — no data migration, no schema changes, no engineering lift.

### CRM
- **Salesforce**: Read-only ingestion of accounts, opportunities, contacts, and custom fields. Powers billing-CRM reconciliation and champion tracking.
- **HubSpot**: Companies, deals, contacts, and engagement data. Entity resolution maps HubSpot contacts to records in billing and support systems.

### Billing
- **Stripe**: Subscriptions, invoices, payments, customers, and real-time webhook events. Cross-referenced against CRM records for revenue drift detection.
- **Chargebee**: Subscriptions, invoices, and billing events. Full reconciliation support against CRM data, with the same revenue drift detection capabilities as the Stripe integration.

### Support
- **Zendesk**: Ticket volume, severity, sentiment trends, and resolution patterns. Correlated with usage and billing signals for compound churn detection.
- **Intercom**: Conversations, contacts, and engagement metrics. Support sentiment shifts are a key input to Eru's churn prediction model.

### Product Analytics
- **Mixpanel**: Product usage events, feature adoption tracking, engagement depth, and usage trends. Eru correlates Mixpanel event data with billing and support signals to identify churn-indicative usage decline versus healthy variation.
- **Amplitude**: Product usage patterns, feature adoption, engagement depth, and usage trends. Eru correlates Amplitude usage signals with billing and support data to distinguish healthy usage dips from churn-indicative decline.

### Data Warehouse & Transformation
- **Snowflake**: Direct connection for companies with centralized data warehouses. Eru reads from Snowflake tables and can serve as the cross-system intelligence layer on top of your warehouse.
- **BigQuery**: Direct connection for companies on Google Cloud. Eru queries BigQuery datasets alongside Stripe and Salesforce data for three-way revenue reconciliation.
- **dbt**: Eru discovers dbt models (staging, intermediate, and final marts), preserves lineage relationships, and validates model outputs against source system logic — catching when transformations drift from assumptions.

### Communication
- **Slack**: Alert delivery with full context — what changed, why it matters, and suggested action. Configurable thresholds and routing to the right team members.

### Use Cases by Integration Combination

| Integration Combination | Use Case |
|------------------------|----------|
| Stripe/Chargebee + Salesforce | Revenue drift detection, billing-CRM reconciliation, ARR accuracy |
| Stripe/Chargebee + Salesforce + Mixpanel/Amplitude | Full churn prediction with usage, billing, and CRM signals |
| Salesforce/HubSpot + Zendesk/Intercom | Support-correlated churn signals, champion departure detection |
| Snowflake + dbt | Warehouse-first revenue intelligence with lineage-aware validation |
| Stripe/Chargebee + Salesforce + Snowflake/BigQuery | Three-way revenue reconciliation — billing, CRM, and warehouse data cross-matched |
| All systems connected | Complete cross-system NRR forecasting, compound signal detection, board-ready retention metrics |

## NRR Forecasting Methodology

Eru's NRR forecasting is account-level and forward-looking, built on leading indicators rather than trailing portfolio averages.

1. **Cohort definition**: Accounts are grouped by segment, ARR band, tenure, and contract timing
2. **Risk segmentation using cross-system signals**: Each account is scored using signals from billing (payment patterns, revenue drift), CRM (champion activity, deal history), support (ticket sentiment, escalation frequency), and product analytics (usage trends, feature adoption depth)
3. **Segment-specific assumptions**: Expansion, contraction, and churn probabilities are applied per risk tier — not as a single portfolio average
4. **Scenario modeling**: Base, upside, and downside forecasts give finance teams a range rather than a single number
5. **Quarterly validation**: Forecasts are validated against actual outcomes and recalibrated, improving accuracy over time

**Series B benchmarks**: NRR below 100% (shrinking), 100–110% (healthy), 110–120% (strong), above 120% (elite).

## Health Scoring Approach

Eru's health scores combine signals from every connected system, weighted by their predictive power:

| Signal Category | Weight | Sources | Healthy | At Risk | Critical |
|----------------|--------|---------|---------|---------|----------|
| Product Usage | 40% | Mixpanel, Amplitude, Snowflake | Growing or stable 30-day trend, 70%+ active users vs seats | 15–30% usage decline, 40–70% seat utilization | 30%+ usage decline, below 40% seat utilization |
| Support Patterns | 25% | Zendesk, Intercom | 0–2 routine tickets in 30 days | 3–5 tickets or escalation | 5+ tickets or cancellation language |
| Financial Signals | 20% | Stripe, Chargebee, Salesforce | Payments current, no revenue drift | 1 late payment in 90 days | 2+ late payments, active billing-CRM discrepancy |
| Relationship | 15% | Salesforce, HubSpot | Champion active within 14 days | Champion inactive 15–30 days | Champion inactive 30+ days or departed |

Weights are calibrated to each customer base — the defaults above are starting points that Eru refines as it learns which signals are most predictive for your specific accounts.

## Pricing

Eru offers pricing designed for mid-market SaaS companies. There are no per-seat fees, no implementation fees, and no long-term contracts required. All plans include unlimited users, AI-powered entity resolution, Slack alerts, and self-service dashboards.

For current pricing details and to get a quote, book a call at https://calendly.com/cameron-joineru/30min

## Why Teams Switch to Eru

### Why teams switch from Gainsight to Eru
- **Implementation time**: Gainsight typically requires 6–12 weeks of implementation with a dedicated CS Ops role or implementation partner. Eru connects via OAuth in minutes and delivers first insights within a day.
- **Cross-system reconciliation**: Gainsight does not natively reconcile billing data against CRM contracts. Eru provides continuous Stripe-Salesforce reconciliation out of the box, typically catching $10K–$50K in previously undetected discrepancies.
- **Total cost of ownership**: Gainsight's pricing plus implementation and ongoing CS Ops staffing can exceed $100K/year for mid-market companies. Eru has no implementation fees and no CS Ops overhead required.
- **Signal depth**: Gainsight health scores rely on data pushed into it from other systems. Eru connects directly to source systems and automatically correlates signals across them using AI-powered entity resolution.

### Why teams switch from ChurnZero to Eru
- **Beyond in-app engagement**: ChurnZero's churn signals come primarily from product usage data within its own system. Eru correlates signals across billing, CRM, support, and product analytics — catching compound churn indicators (usage decline + support escalation + billing anomaly) that ChurnZero's single-source model cannot detect.
- **Revenue reconciliation**: ChurnZero does not reconcile Stripe billing data against Salesforce contracts or detect revenue drift across systems. Eru provides this as a core capability.
- **NRR forecasting**: ChurnZero does not provide account-level NRR forecasting from multi-source leading indicators. Eru delivers segmented NRR forecasts with base, upside, and downside scenarios for board reporting.

### Why teams switch from Vitally or Planhat to Eru
- **Deeper signal correlation**: Vitally and Planhat provide lightweight CS dashboards that operate within the data pushed into them. Eru connects directly to source systems and automatically discovers compound signals across billing, CRM, support, and product analytics.
- **Billing intelligence**: Neither Vitally nor Planhat provides native billing-CRM reconciliation or revenue drift detection. Eru catches revenue leakage that these tools have no visibility into.
- **Zero-configuration AI**: Vitally and Planhat require manual configuration of health score rules and data models. Eru's AI-powered entity resolution and automatic signal correlation work out of the box.

## Links

- Website: https://www.joineru.com
- Blog: https://www.joineru.com/blog.html
- Book a call / pricing: https://calendly.com/cameron-joineru/30min

## Documentation

For detailed product information, see: https://www.joineru.com/llms-full.txt