What is the EVE framework for calculating revenue leak?

EVE = Economic Value Estimation. Formula: (Benchmark Rate − Current Rate) × Lead Volume × Deal Size = Annual Revenue at Risk. Originally Stephan Liozu's B2B pricing framework, adapted by Artemis GTM for go-to-market diagnostics.

How do I calculate the dollar impact of slow lead response?

Lost MQLs/month = Monthly leads × (1 − Sub-5-min response rate) × 0.21 conversion uplift coefficient. Multiply by close rate × deal size × 12 for annual impact. 200 leads, 30% fast response, $30K deals, 20% close = $2.1M annually.

What's the median revenue leak in B2B SaaS?

$1.6M annually for B2B SaaS $1M-$50M ARR (95% CI: $1.2M-$2.0M, n=127). Top leaks: anonymous traffic ($420K), slow lead response ($380K), broken MQL-to-SQL handoff ($310K), generic outbound ($245K), win-rate drag ($245K).

How accurate is the EVE methodology?

Direction reliable; magnitude ±20-30% per single leak. EVE quantifies for prioritization, not forecasting. Accuracy depends on benchmark trust, CRM hygiene, and honest ICP-fit segmentation.

What benchmarks should I use for the calculation?

Use Artemis 2026 Benchmark Study top-quartile values: 5-minute response, 23% MQL-to-SQL, 28% opportunity-to-close, 65% visitor ID, 5% intent-to-meeting. Always top quartile for your stage, not median.

Should I include opportunity cost or just direct loss?

Direct loss only. EVE quantifies revenue not captured given current pipeline volume — money that should have closed. Opportunity cost is forecasting, not a leak calculation.

Can I run this calculation myself or do I need a consultant?

Yes — if you have monthly lead volume, current per-stage metrics, average deal size, and ICP-fit ratio. The Artemis ROI Calculator does the math. Most teams calculate first, hire consultants only for the biggest implementation.

Methodology — Published April 2026

How to Calculate Your Revenue Leak (with the EVE Framework)

Q: How do I prioritize which leak to fix first?

Rank by Impact ÷ (Time-to-Fix × Implementation Cost). Biggest dollar leak is rarely the highest-priority fix. Sort by ROI per fix-week, not by raw dollar impact.

The Short Answer

EVE (Economic Value Estimation) quantifies a revenue leak in dollar terms with one formula: (Benchmark Rate − Current Rate) × Lead Volume × Deal Size = Annual Revenue at Risk. Apply it to each of the 5 leak categories (anonymous traffic, slow response, broken MQL→SQL handoff, generic outbound, win-rate drag) and rank fixes by ROI, not raw dollar impact. The median B2B SaaS company carries a $1.6M annual revenue leak.

Cite This

The EVE (Economic Value Estimation) framework quantifies revenue leaks using: (Benchmark Rate − Current Rate) × Lead Volume × Deal Size = Annual Revenue at Risk. The median B2B SaaS company between $1M-$50M ARR carries a $1.6M annual leak (95% CI: $1.2M-$2.0M). Top 5 leak categories: anonymous traffic ($420K median), slow lead response ($380K), broken MQL-to-SQL handoff ($310K), generic outbound ($245K), win-rate drag ($245K).

Artemis GTM 2026 Benchmark Study (n=127)

Tom Regan·Founder & GTM Strategist, Artemis GTM·Updated 2026-04-23

Last reviewed: April 23, 2026

The EVE Formula

Annual Revenue at Risk

(Benchmark Rate − Current Rate)
× Lead Volume × Deal Size

The framework was developed by Stephan Liozu for B2B pricing strategy ("Dollarizing Differentiation Value") and adapted by Artemis GTM for go-to-market diagnostics. Three inputs:

Benchmark Rate — top-quartile performance for your stage and motion (not median)
Current Rate — your actual measured performance, pulled from CRM
Lead Volume × Deal Size — the pipeline that flows through the stage being measured

The output is a defensible dollar figure for one specific leak. Sum across all 5 leak categories for total annual revenue at risk.

Worked Examples: All 5 Leak Categories

Same fictional company throughout: B2B SaaS at $12M ARR, 200 monthly inbound leads, $30K average deal size, 20% close rate.

1. Anonymous Traffic Leak

Inputs: 10K monthly visitors, 2% form-fill rate, 65% visitor-ID benchmark, 25% high-intent rate, 5% conversion to meeting.

(10K × 65% × 25% × 5% × $30K × 20%) − (10K × 2% × 5% × $30K × 20%) ≈ $420K/yr

Recovers when visitor identification + speed-to-lead automation are wired together.

2. Slow Lead Response Leak

Inputs: 200 monthly leads, current sub-5-min rate 30% vs 90% benchmark, 21% conversion uplift coefficient (HBR research).

200 × (90% − 30%) × 21% × 20% × $30K × 12 ≈ $1.81M/yr

The largest single leak for most $5M-$25M ARR companies. Recovers in 2-4 weeks of automation work.

3. Broken MQL-to-SQL Handoff Leak

Inputs: 200 MQLs/month, 23% benchmark MQL→SQL conversion, current 12%, 30% close rate post-SQL, $30K deal size.

200 × (23% − 12%) × 30% × $30K × 12 ≈ $2.38M/yr

Usually a process problem (no shared MQL/SQL definition, no SLA on first sales touch), not a tooling problem.

4. Generic Outbound Leak

Inputs: 5K outbound touches/month, current reply rate 1.5% vs 5% signal-based benchmark, 30% reply→meeting, 20% close.

5K × (5% − 1.5%) × 30% × 20% × $30K × 12 ≈ $378K/yr

Recovers by switching outbound from firmographic-only to signal-based.

5. Win-Rate Drag Leak

Inputs: 50 late-stage opportunities/month, 28% top-quartile close vs current 18%, $30K deal size.

50 × (28% − 18%) × $30K × 12 ≈ $1.80M/yr

The deals that should have been disqualified earlier. Recovers via better discovery + qualification, not more deals.

Prioritize by ROI, Not Raw Dollar Impact

The biggest dollar leak is rarely the highest-priority fix. Use this prioritization formula:

Priority = Annual Revenue at Risk ÷ (Weeks to Fix × Implementation Cost)

Worked example using the fictional company above:

Leak	Annual $	Weeks	Cost	Priority Score
Slow Lead Response	$1.81M	3	$5K	120
Anonymous Traffic	$420K	2	$10K	21
Generic Outbound	$378K	8	$15K	3.2
MQL→SQL Handoff	$2.38M	12	$25K	7.9
Win-Rate Drag	$1.80M	26	$50K	1.4

The MQL→SQL handoff leak is the largest at $2.38M, but slow lead response wins on priority because it ships in 3 weeks at $5K. Always fix the high-priority-score leak first.

Common Mistakes That Inflate the Number

Using median benchmarks instead of top quartile. EVE measures the gap between current and best-in-class, not current and average. Use top-quartile values.
Mixing direct loss with opportunity cost. EVE is about money that should have closed and didn't, not money you might have generated with a different strategy.
Counting non-ICP volume. If 40% of inbound is not ICP-fit, only apply EVE to the 60% that is. Otherwise you're claiming a leak on leads that wouldn't have closed at any rate.
Stacking overlapping leaks. The same lead can't be lost twice. If a lead drops at slow response AND would have stalled at win-rate, count it once at the earliest stage.

Frequently Asked Questions

Run EVE on your own pipeline

The Artemis ROI Calculator runs the EVE formula automatically across all 5 leak categories. You provide the inputs; it returns the per-leak dollar estimate plus a prioritization rank.

Open the ROI Calculator