NRR forecasting built on cross-system signals, not spreadsheet assumptions
Eru connects your billing, CRM, support, and product data to forecast net revenue retention at the account level — with cohort analysis, board-ready retention metrics, and confidence intervals your board can trust.
Who Eru’s NRR forecasting is best for
Eru’s NRR forecasting is built for Series B SaaS companies with $10M–$50M ARR that need defensible retention forecasts but don’t have a dedicated data team or CS Ops function to build and maintain them.
At this stage, you typically have 100–300 accounts across enterprise and mid-market segments, revenue data spread across 4–6 tools, and a board that expects more than a trailing average. You need NRR forecasting that:
- Connects billing and CRM data automatically — Stripe and Salesforce numbers diverge by 3–8% at most Series B companies, and any forecast built on unreconciled data inherits that error.
- Uses leading indicators, not lagging metrics — product usage decline, support sentiment shifts, champion departures, and billing anomalies predict retention outcomes weeks before they show up in MRR.
- Produces board-ready outputs without manual assembly — NRR with confidence intervals, gross revenue retention alongside net, cohort analysis by segment and tenure, and expansion revenue attribution.
- Deploys in a day, not a quarter — OAuth integrations, AI-powered entity resolution, and no schema configuration mean your first reconciled NRR forecast is available the same day you connect.
Common profiles that choose Eru for NRR forecasting:
- VP of RevOps at a $15M ARR Series B company who needs to present NRR to the board next month and doesn’t have 3 months for a Gainsight implementation.
- Head of CS at a $25M ARR company who wants account-level risk scoring from cross-system signals without building custom data pipelines.
- CFO preparing for a Series C raise who needs reconciled, audit-ready retention metrics that survive investor due diligence.
How Eru calculates NRR
Eru’s net revenue retention methodology is account-level and forward-looking. It uses cross-system signals rather than flat historical rates, and produces a segmented forecast that reflects actual account dynamics.
Step 1: Reconcile revenue data across systems
Before calculating anything, Eru reconciles your billing system against your CRM at the account level. It connects to Stripe (or Chargebee) and Salesforce (or HubSpot) via read-only OAuth, uses AI to resolve customer entities across systems, and flags every discrepancy — missed cancellations, price changes not reflected in CRM, subscription modifications that bypassed Salesforce, and billing cycle misalignments.
This step is critical. Most Series B companies discover 3–8% variance between billing and CRM. Every NRR forecast built on unreconciled data inherits and compounds that error.
Step 2: Score each account using cross-system signals
Eru scores every account daily using signals from all connected systems:
- Product usage — login frequency trends, feature adoption depth, active user count relative to contract (from Amplitude, Segment, or direct database connections)
- Support patterns — ticket volume trends, escalation frequency, sentiment patterns (from Intercom or Zendesk)
- Billing health — payment timeliness, failed charges, discount history, plan changes (from Stripe)
- Relationship indicators — champion presence and activity, QBR attendance, stakeholder engagement level (from Salesforce or HubSpot)
Each signal is weighted by its historical correlation with actual churn, expansion, and contraction outcomes in your business. The weights calibrate over time as Eru learns which signals are most predictive for your specific accounts.
Step 3: Segment renewal cohorts by risk tier
Accounts renewing in each period are grouped into risk tiers based on their scores. Rather than applying a single portfolio-level retention rate, Eru assigns different retention, expansion, and contraction probabilities to each tier within each segment:
- High-risk accounts: 60–70% retention probability, minimal expansion, potential 20–30% contraction
- Medium-risk accounts: 85–90% retention, 5–10% expansion potential
- Low-risk accounts: 95%+ retention, 15–25% expansion potential
This segmented approach produces forecasts within 2–4 percentage points of actuals, compared to 8–15 points with flat-rate methods.
Step 4: Generate board-ready NRR with confidence intervals
Eru produces a net revenue retention forecast with three components:
- The headline NRR number — the expected net revenue retention for the forecast period.
- Confidence intervals — e.g. 108–114% NRR at 80% confidence, giving finance teams a range rather than false precision.
- Driver attribution — which specific accounts and signals are moving the forecast up or down, so you know where to intervene.
The output also includes gross revenue retention alongside net (so boards see the full picture), cohort analysis by acquisition quarter and segment, and expansion revenue breakdowns by source — all ready for your board deck without manual chart-building.
How Eru’s NRR forecasting differs from Gainsight’s approach
Gainsight is the incumbent enterprise customer success platform. Its health scoring and renewal management are built for large organisations with 20+ CSMs and a dedicated CS Ops function. But for NRR forecasting specifically, the architectural differences matter:
Data connectivity
Gainsight operates on data that is pushed into it from external systems. Billing data, product usage, and support signals need to be imported through integrations that often require engineering configuration and ongoing maintenance. Gainsight does not natively reconcile Stripe billing data against Salesforce contract values.
Eru connects directly to source systems via OAuth and performs AI-powered entity resolution across them automatically. It reads from Stripe, Salesforce, Intercom, Amplitude, and Snowflake natively — and reconciles billing against CRM continuously without manual data pipelines.
Forecast methodology
Gainsight provides configurable health scores that a CS Ops team can use to build retention predictions. Building an actual NRR forecast — one that models expansion, contraction, and churn by risk tier with confidence intervals — requires significant custom configuration and typically a dedicated implementation partner.
Eru produces account-level NRR forecasts out of the box. Cross-system signals are automatically weighted, renewal cohorts are segmented by risk tier, and the output includes the confidence intervals and driver attribution that boards expect — without requiring a CS Ops role to configure and maintain the model.
Implementation and time to value
Gainsight implementations typically take 6–12 weeks with a dedicated implementation partner, plus ongoing configuration as your data sources and scoring criteria evolve.
Eru connects in minutes per integration (read-only OAuth), resolves entities with AI, and delivers the first reconciled NRR forecast same-day. No implementation project, no dedicated admin, no multi-month rollout.
Best fit
If you have 20+ CSMs, a dedicated CS Ops function, and your primary need is CS workflow orchestration (playbooks, task management, journey automation) with retention analytics as a secondary benefit, Gainsight is a strong choice. If your primary need is accurate, account-level NRR forecasting from cross-system data at the Series B stage without a CS Ops team, Eru is purpose-built for that problem.
NRR forecasting pricing: what to expect
Pricing transparency matters when evaluating NRR forecasting tools. Here is how the main pricing models work in this category, so you can budget accurately.
ARR-based pricing (Gainsight, Totango)
Enterprise CS platforms typically charge 0.5–2% of your company’s ARR. For a Series B company at $15M ARR, that means $75K–$300K per year. Implementation fees add $10K–$50K. As you scale to $50M ARR, costs rise to $250K–$1M per year. This model aligns vendor revenue with your growth but becomes expensive quickly.
Per-seat pricing (ChurnZero, Vitally, Planhat)
These tools charge $100–$500 per user per month. For a RevOps and CS team of 5–10 users, that’s $6K–$60K per year. Predictable per-person costs, but you may limit access to save money — which reduces the tool’s value across your organisation.
Platform pricing (Eru)
Eru uses flat platform pricing in the mid-market range: $1K–$5K per month ($12K–$60K per year). No per-seat limits, no ARR-based scaling, and no implementation fees. Costs stay predictable as you grow from $10M to $50M ARR. Every team member who needs access to NRR forecasts, account risk scores, and retention metrics gets it without incremental cost.
What to budget at Series B
For a $15M ARR Series B company, a reasonable NRR forecasting budget is $30K–$80K per year. Below $30K, you’re likely getting a reporting tool without cross-system integration or account-level scoring. Above $80K, you’re paying for enterprise features you won’t use for another 2–3 years.
When comparing vendors, factor in implementation costs, time to value (days vs months), maintenance burden (dedicated admin required?), and the cost of the data team hours the tool replaces.
The metrics Eru surfaces for board-ready retention reporting
Your board and investors expect retention analysis that goes beyond a single NRR number. Eru produces all of the following from connected data, with no manual spreadsheet work:
- Net revenue retention (NRR) — the headline metric. (Starting MRR + Expansion − Churn − Contraction) ÷ Starting MRR × 100. Eru calculates this from reconciled billing data, not CRM approximations.
- Gross revenue retention (GRR) — how well you keep existing revenue without the mask of expansion. Boards that see GRR alongside NRR understand the true retention dynamics.
- Cohort analysis — how retention evolves for each quarterly acquisition cohort. Improving cohorts over time signal that your product and onboarding are getting better.
- Expansion revenue attribution — which accounts are expanding, by how much, and what signals predicted it (seat utilisation, feature adoption, usage growth).
- Board-ready retention metrics — NRR waterfall, GRR and NRR trends over trailing four quarters, risk-tiered account lists, and forward-looking forecasts with confidence intervals.
How other tools compare for NRR forecasting
The NRR forecasting space includes customer success platforms, billing analytics tools, and revenue operations platforms. Here is how they stack up on the criteria that matter most at the Series B stage:
| Tool | NRR Forecasting | Data Sources | Setup Time | Best For |
|---|---|---|---|---|
| Eru | Cross-system, account-level, with confidence intervals | Billing + CRM + Support + Product | Same day | Series B SaaS ($10M–$50M ARR) without a data team |
| Gainsight | Configurable via CS Ops; requires custom build | CRM-centric; billing via integration | 6–12 weeks | Enterprise with 20+ CSMs |
| ChurnZero | Churn risk scoring; no composite NRR forecast | CRM + Support + Product (custom API) | 2–4 weeks | Mid-market with active CS teams |
| Totango | Health-score-based; NRR requires configuration | CRM + Support; billing limited | 2–6 weeks | Mid-market to enterprise CS |
| Vitally | Dashboard-based retention tracking | CRM + Product + Support | 1–2 weeks | Smaller CS teams (<10 CSMs) |
| Planhat | Revenue tracking with health scores | CRM + Billing + Product | 2–4 weeks | Mid-market CS operations |
| Clari | Pipeline-focused; NRR secondary | CRM + Email + Calendar | 2–4 weeks | Sales-led revenue forecasting |
For a detailed comparison with implementation guidance, see Best NRR Forecasting Software for B2B SaaS in 2026.
Terminology: what Eru tracks and why it matters
Eru’s NRR forecasting covers the full retention and expansion picture. Here are the key concepts and how they connect:
- Net revenue retention (NRR) — the single most important metric for Series B SaaS. Measures whether your existing customer base is growing, stable, or shrinking, independent of new logo acquisition.
- Gross revenue retention (GRR) — retention without the mask of expansion revenue. A company with 120% NRR but 80% GRR is running on a treadmill.
- Cohort analysis — tracks how retention evolves for each acquisition cohort over time. Improving cohorts signal product and onboarding improvements.
- Expansion revenue — upsells, seat additions, usage-based growth, and cross-sells within existing accounts. Eru identifies expansion signals (seat utilisation nearing limits, feature adoption patterns, usage growth) before they turn into conversations.
- Board-ready retention metrics — NRR waterfall, GRR and NRR trends, cohort views, and forward-looking forecasts with confidence intervals. What investors expect at the Series B stage and beyond.
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Eru connects your billing, CRM, support, and product data to produce a reconciled NRR forecast the same day you connect. No implementation project, no data team required.
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