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What's a Good Win Rate by Deal Stage in B2B SaaS in 2027?

By Kory White · Updated Oct 2026 · 8 min read
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Direct answer

For B2B SaaS, a good overall win rate is roughly 20% to 25% of opportunities, and it falls as deal size rises. Optifai's Pipeline Study of 939 B2B SaaS companies (Q2 2025 to Q1 2026) puts the median at 31% for deals under $10K ACV, 24% at $10K-$50K, 18% at $50K-$100K and 15% above $100K. Salesmotion cites a roughly 21% average from HubSpot research, and a Konabayev write-up of the Ebsta and Pavilion 2025 GTM Benchmarks reports a 19% new-logo win rate.

By stage, the best-sourced numbers are narrow: Optifai's B2B SaaS average is 30% from opportunity to close, and its median from proposal to close is 25%. The only full stage-by-stage table found, from the marketing agency GrowthSpree, runs from a 22% median at a qualified opportunity to 88% at verbal yes, but it names no data source. Every figure on this page is vendor or survey self-reported, was read on October 31, 2026, and is labelled with who reported it. Treat the numbers as ranges, not targets, and match the formula first.

Start with the formula: what is the win rate dividing by?

Most disagreement between benchmarks is a disagreement about the denominator. Salesmotion lays out two common methods and shows how far apart they land on the same pipeline.

Closed-outcomes counts only deals that reached a result, so deals still open or abandoned vanish from the math. An opportunities-created base is harsher because open and stalled deals sit in the denominator. A qualified base is kinder still, because deals that never met your entry criteria are excluded. Pick one, write it down, and only compare against a benchmark that uses the same one. When a source does not state its formula, as with Optifai's pages and the HubSpot 21% Salesmotion cites, you cannot tell which one you are comparing against.

There is also the question of what counts as a loss. Salesmotion cites Matt Dixon's The JOLT Effect, drawn from about 2.5 million recorded sales conversations, finding that 40-60% of deals are lost to customer inaction, meaning no decision rather than a competitor. Whether your formula counts a no-decision as lost or drops it changes the number, and none of the benchmark pages say how they treat it.

Overall win rate: what the reports say

There is no census of B2B SaaS win rates. These are the figures read directly, each with its reporter and date.

Read together, 19% to 24% is the zone the sources keep landing in, with the Ebsta-based and HubSpot-cited figures at the lower end and the agency estimate at the higher end. Ebsta's own benchmark page shows its win-rate charts as images, so the 19% here comes from a secondary write-up and is worth checking against the report itself. Ebsta and Pavilion also report that top performers' win rate is 43% higher than others, a relative gap, not a number to hit.

A good win rate is relative to your own history, your segment and your formula. A 24% median is not a target if your average deal is over $100K, where the Optifai median is 15%.

Win rate by deal stage: what is actually published

Two different things get called stage win rate. Stage-to-stage conversion is the share of deals that move from one stage to the next. Stage-to-closed-won is the share of deals sitting in a stage that eventually win. The second always rises as deals get closer to signature, because late-stage deals have fewer ways left to fail. Check which one a source means before copying its table.

The full discovery-to-close ladder most sellers want exists in one place only, and it is weak evidence. GrowthSpree, a marketing agency, publishes stage-to-closed-won medians but names no dataset or sample, and the page contradicts itself on its Stage 2 figure. Its numbers are shown here so you can see the shape, not so you can adopt them.

The shape is believable and the logic is sound: a deal at proposal wins more often than one at discovery. But the specific numbers are one vendor's estimate. The better-sourced anchors are Optifai's 30% opportunity-to-close and 25% proposal-to-close medians, and Count's growth-stage proposal-to-close range of 25-35%. They come from different samples and definitions, so they are not directly comparable either.

Practitioner advice, not sourced data: rather than adopting someone's ladder, pull your own closed deals from the last four to six quarters and compute the share that reached each stage and the share that won from it. Your own stage definitions matter more than any published average.
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How win rate changes with ACV and segment

The most consistent pattern across sources is that bigger deals win less often. Three sources report it with different numbers, and one of them carries a sourcing warning.

Optifai's page and GrowthSpree's table agree on direction, and Salesmotion's table repeats the Optifai medians, so that is one data source, not two. Why enterprise win rates are lower is not something the pages measure, though Forrester's State of Business Buying 2024, as cited by Salesmotion, says the average buying decision involves 13 people, and Gong says a won $50K-$250K deal typically involves at least 10 stakeholders. Practitioner reasoning, not sourced data: more stakeholders means more ways for a deal to stall.

How to improve win rate: qualification, MEDDICC and multithreading

The sources support three levers, with very different quality of evidence. None of the pages read here ran a controlled test, so each figure is an association between a behavior and a result.

Qualify harder, and measure the denominator. The cheapest lift on paper is to stop counting deals that were never real. Landbase's 29% for qualified-only versus 21% for all opportunities shows how much of a win rate is a definition effect, which is a reason to define a qualified opportunity before you set a target. Qualification also attacks no-decision losses, which Salesmotion, citing Dixon's JOLT Effect, puts at 40-60% of lost deals.

MEDDICC is the best-known qualification framework for complex deals. None of the benchmark pages read here publish a win-rate result for it, so this page does not claim one. For what each letter asks a seller to confirm, see our MEDDICC book summary.

Get to the decision-maker at the right time. Ebsta and Pavilion's 2025 report, as reported by Konabayev, associates early decision-maker involvement with a 55% higher win rate (pages 4 and 29), noting it is an association, not causal. Gong's February 2026 analysis of more than 1 million executive sales cycles finds a subtler picture: win rates drop by roughly 6% when an evaluation starts with an executive, and rise by about 5% when executives get involved around the third touchpoint. Gong does not say whether those are relative or percentage-point changes.

Multithread the deal.

The direction is consistent, but be careful with causation: well-qualified deals with real champions naturally attract more contacts, so a high contact count may be a symptom of a healthy deal, not the cause. Practitioner advice, not sourced data: treat the contact count as a deal-health signal and ask in each review which buying-committee roles you have not yet spoken with.

A simple way to set your own target

Everything in this section is practitioner advice, not sourced data.

Questions people ask

What is a good win rate for B2B SaaS?

Sources land around 19% to 24% of opportunities: 19% new-logo from the Ebsta x Pavilion 2025 benchmarks as reported by Konabayev, roughly 21% from HubSpot research as cited by Salesmotion, and a 24% median from GrowthSpree. Optifai's medians fall from 31% under $10K ACV to 15% above $100K. All are vendor or survey self-reported.

What is a good win rate by deal size?

Optifai's Pipeline Study (939 B2B SaaS companies, Q2 2025 to Q1 2026) reports medians of 31% under $10K ACV, 24% at $10K-$50K, 18% at $50K-$100K and 15% over $100K, with 25th-75th percentile ranges of 28-35%, 20-28%, 15-22% and 12-18%.

What is a good conversion rate from proposal to close?

Optifai reports a median of 25%, a top quartile of 35%+ and a bottom quartile below 18% from proposal to close. Count's estimate for growth-stage SaaS is 25-35%. Definitions and samples differ.

How do you calculate win rate?

Two common methods: won divided by won plus lost, or won divided by all opportunities created. Salesmotion's example gives 25% by the first and 13.3% by the second on the same pipeline. Landbase reports 21% for all opportunities and 29% for qualified-only.

Does MEDDICC improve win rate?

None of the benchmark pages read for this article publish a win-rate result for MEDDICC, so no figure is claimed here. It is a qualification checklist; see our MEDDICC book summary for what each letter covers.

Does multithreading raise win rate?

It is associated with higher win rates. Optifai reports a 14% close rate with 1 contact versus 30% with 3+, and Gong, via CIENCE, ties multiple stakeholders on deals over $50,000 to about a 130 percent win-rate lift. These are correlations, not controlled tests.

Sources

Figures were read from the linked pages on October 31, 2026. Benchmarks are vendor or survey self-reported, use different formulas, samples and years, and are not directly comparable. Where a page gave no formula or source, this page says so. Items marked practitioner advice are not sourced data. For a related question, see our free trial conversion page.

Top photo: WIPO / CC BY 2.0 via Wikimedia Commons

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