Proposal Win Rate Benchmarks: What a Good Number Looks Like
A healthy proposal win rate for a B2B tech company usually lands between 25% and 50%, but the number only means something if you divide by the same thing the benchmark did. Published figures run from 18% to 70% because each study counts a different set of deals. Before you compare yourself to anyone, fix your definition, split new business from expansion, and segment by deal size.
Real talk: most Heads of Sales who ask “are we below average?” are comparing their full-funnel number to someone else’s proposal-stage number. That’s like comparing a marathon time to a 5K.
Before any benchmark, get the denominator straight. The same quarter of sales activity produces three different percentages:
| Metric | Formula | What it tells you |
|---|---|---|
| Opportunity win rate | Deals won ÷ all qualified opportunities that reached a decision | Full-funnel quality, from first qualification |
| Proposal win rate | Deals won ÷ proposals sent | How well you close once you’ve priced and pitched |
| RFP win rate | Bids won ÷ formal bids submitted | Performance in formal tenders only |
The proposal-stage version runs higher than the opportunity version because weak opportunities drop out before a proposal goes out. The same source recommends counting only deals that have closed, won or lost, over the same period, and leaving open deals out until they resolve.
The APMP, the professional association for proposal management, describes two ways to calculate it: proposals won divided by proposals submitted (3 wins out of 10 is 30%), or revenue won divided by revenue bid ($300K won of $1M bid is also 30%). A team that wins many small deals and loses the big ones will look very different on the two measures.
If you’re a US-style buyer-seller shop selling into the EU, the logic is identical. The unit is a decision, and a decision is a yes or a no.
Here are the figures most often quoted, with what each one actually counts.
| Source | Figure | What it counts |
|---|---|---|
| APMP (2010) | 33% industry average, most firms 10% to 75% | Proposal wins ÷ proposals submitted |
| APQC benchmarking measure | 70% median (91 companies) | New proposals resulting in a new contract |
| QorusDocs 9th Annual Survey (2025) | 37% median new-business win rate, most firms 25% to 49% | US service firms incl. IT/SaaS, RFP-driven |
| Loopio 2024 report | 43% average RFP win rate in 2023 | 1,650+ companies, RFP responses |
| Proposify State of Proposals 2025 | 36% close rate on its platform vs. 20% industry average | 902,305 proposals across 27 industries |
The spread is wide, and that’s the point. APQC’s 70% median reflects firms that already filter heavily before bidding. The 20% industry average in the Proposify data reflects a broader pool. Neither is wrong. They’re measuring different funnels.
A useful cross-check comes from full-funnel data. Ebsta’s 2025 benchmarks, built on $48 billion of B2B opportunities from UK and US tech companies, found an 18% average win rate on new business versus 45% on customer expansion. Expansion deals also closed in 52 days versus 91 for new business.
That gap between 18% and 45% inside one dataset tells you more than any single headline average.
The APMP has been blunt about this: win rates used for marketing are rarely audited and often gamed. It also notes that roughly 80% of awards go to the lowest-price bidder in the kind of bids it studied, so a firm’s win rate reflects its non-price competitiveness only on the remaining share.
Practical takeaway: use benchmarks to find the right range, then rely on your own CRM data to judge direction.
If you only segment one way, segment by deal size. Proposify’s 2024 analysis of more than 1.28 million proposals found deal size was the biggest external factor on close rate: smaller deals close at higher rates consistently across industries, while company size had little effect. Their explanations will sound familiar to anyone who has sold to an IT buyer:
ProposalCraft’s 2026 conversion benchmarks put numbers on it: 40% to 50% for proposals under $10,000, 25% to 35% above $100,000, and around 20% as excellent for million-dollar deals. Competitive categories such as IT services sit lower than specialized niches.
The same pattern shows in qualified-pipeline data. A 2026 analysis of 939 B2B SaaS companies is often cited with a 31% median under $10K ACV falling to 15% above $100K. Treat those as directional, since the sources behind them are vendor datasets.
For a Head of Sales running a mid-market or enterprise motion, that means a 22% win rate on six-figure ACV deals may be perfectly healthy, and a 40% rate on small deals may be leaving money on the table. ProposalCraft’s rule of thumb is that under 20% signals lost revenue and consistently above 40% suggests you could raise prices.
Win rate is calculated on proposals you submit, not on opportunities you receive. Teams with strict go/no-go discipline report higher win rates, because selectivity and win rate move together.
That cuts both ways. If your rate jumped from 22% to 34% in two quarters, ask first whether you got better at selling or just stopped bidding on anything uncertain. One is a win. The other might be a shrinking pipeline in disguise.
Government contracting writers make the same point with a third metric: pursuit win rate, which counts contracts won against every opportunity actively evaluated, including the ones declined. Tracking proposal win rate alone can quietly reward reckless bidding or, in the opposite direction, timid bidding.
Here’s the routine we’d run before any benchmark comparison.
Where it goes wrong: stage definitions that drift. If reps can move a deal to “proposal” whenever they email a price, your denominator is inflated and your rate is meaningless. Our opportunity hygiene rules cover how to lock stage entry criteria so the number holds up in a forecast review.
Benchmarks are a range-check. Here’s how to use them without fooling yourself.
Start from your own baseline. Take your segmented rate for the last two to four quarters. A realistic improvement target is a few points within a segment, not a jump to the industry average.
Match the denominator. A team measuring opportunity win rate should compare against full-funnel numbers like the 18% to 31% ranges, and a team measuring proposals sent should compare against the 25% to 50% ranges. Mixing them is the most common benchmarking error we see in board decks.
Read the shape, not the point. If your proposal win rate is healthy but your opportunity win rate is low, the leak is upstream: qualification or discovery. If it’s the other way round, look at pricing, packaging and how you present to the buying committee. Our pieces on demo conversion rate and MQL to SQL benchmarks cover the upstream side.
Review losses before blaming price. Check whether the deal was properly qualified, whether the proposal was viewed by more than one stakeholder, and whether a champion existed. Price is the reason buyers give, not always the reason they decide.
Put an owner and a cadence on it. A win rate nobody owns drifts. Define the formula, the data source, who reviews it and how often. The RevOps metrics guide shows how to set that up for a metric like this.
Most of the benchmark data above comes from the US, UK or North America. If you’re selling from the EU into US accounts, those ranges are a fair guide for US deals. If you’re selling into EU public tenders, expect formal procurement to behave like the RFP data: more stakeholders, more scoring criteria, more price weight. Keep those deals in their own segment rather than blending them into your commercial pipeline.
We get asked for “the” proposal win rate benchmark nearly every time a leadership team feels their number is off. Our honest answer: the benchmark is rarely the problem.
What we see in the field of B2B tech sales is a definition problem first, and a system problem second. Stage criteria are loose, new business and expansion are blended, and nobody owns the formula. Then a quarter looks bad, the VP hires another rep, and the leak stays exactly where it was.
That’s why we build revenue systems end to end instead of patching one stage. Your win rate is the output of your ICP, your qualification, your sales roles, your pipeline governance and how your team presents. Fix one in isolation and the number barely moves. Connect them and it becomes something you can forecast.
Real talk: a 28% win rate you understand beats a 40% win rate you can’t explain. If you can say why you win, where you lose and which segment carries the number, you can plan hiring, pipeline coverage and quota around it. That’s structure, and structure beats heroics.
Antony
If your win rate is stuck and you can’t tell which stage is leaking, a diagnostic is the fastest way to find out. Our Revenue System Diagnostics and Sales Workflow Audit look at how your pipeline is defined, how deals move through stages and where proposals stall, so you leave with a clear view of what to fix first. They sit alongside our sales enablement and team setup work, all described on our services page.
Not sure whether you need outside help yet? Our guide on when to hire a sales consultant lists seven clear signals.
For new-business proposals at B2B tech and service firms, 25% to 50% is a common range, and one US survey of service firms reported a 37% median. Your own number should be judged by deal size and by whether the deal is new business or expansion.
Win rate is usually deals won divided by deals that reached a yes or no decision. Close rate is often defined more broadly, including in-progress pipeline. Pick one, write it down, and use it consistently.
Both. Count-based and value-based rates can diverge sharply if you win many small deals and lose large ones. Reviewing the two side by side shows whether the problem sits in enterprise pursuits or across the board.
Usually the denominator. A full-funnel opportunity win rate will always look lower than a proposal-stage rate, and new-business figures such as the 18% Ebsta average sit well below blended figures. Match the definition before concluding you’re behind.
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CRO & Co-Founder with Sales Label Consulting
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