Most proposal benchmarks circulating online in 2026 are second-hand. Dig two layers in and you land on the PandaDoc State of Proposals 2023, a Forrester note from 2021, or an Aberdeen study from 2019. Useful once, stale for the committee you are selling to today.
This piece does two things. First, it publishes four observations we see consistently across 2,800 sales teams on Afterquoted. Second, it anchors those observations against the credible third-party research that still holds up for 2026, with full attribution, so you can cite whichever number fits your context.
Nothing below is a fabricated controlled study. Every stat has a named source. When the source is Afterquoted, we say "Afterquoted internal". When it is a public study, we link or name it.
How we compiled the six benchmarks
Afterquoted observations come from anonymized engagement data on the platform, covering the 2,800 sales teams active during 2025 and early 2026. We do not share customer-level data with anyone. The four Afterquoted numbers are platform averages, not a controlled experiment; they reflect what teams genuinely see when they use tracked links at scale.
Third-party research is attributed by name in each benchmark. When two sources disagree (and they often do), we show both numbers and explain why the methodologies differ. Treat this as a reading list more than a single verdict.
64% of proposals are never opened
Source: Afterquoted internal · 2,800 teams.
Across our platform, 64% of B2B proposals sent by email attachment are never opened by the intended recipient. Even with tracked links the open-rate problem does not fully disappear, since many proposals are forwarded instead of opened directly, but the visibility changes completely: a forward becomes a signal rather than a silent event.
External context that aligns with this observation: B2B buyers now juggle an increasing volume of internal and external communications, and buying committees frequently involve six to ten stakeholders according to Gartner's ongoing research on buying groups. An attachment sent to a single inbox gets distributed through a committee whose behavior you cannot see.
Takeaway: send tracked links, not attachments. See our complete guide to proposal tracking for the how.
The 23% conversion baseline, in context
Source: Afterquoted internal · 23%. Compare with: PandaDoc State of Proposals 2023 (~35% SaaS industry average), Landbase 2026 (21% all B2B opportunities, 29% qualified), Bidara 2026 (45% RFP win rate).
Across Afterquoted, the average B2B proposal conversion rate sits around 23%. The number is lower than PandaDoc's widely quoted 35% SaaS average (2023) and higher than Landbase's 21% all-opportunities benchmark (2026). Why do these numbers diverge?
- PandaDoc 2023 (35%) measures proposals built inside a proposal builder, which pre-qualifies the pipeline. The prospect who agrees to receive a PandaDoc proposal is already further along than the average cold proposal.
- Landbase 2026 (21% all / 29% qualified) measures from the opportunity stage, not from the proposal stage. Their "all" number includes opportunities that never reach a proposal.
- Bidara 2026 (45%) measures formal RFP responses, which are a narrow, heavily pre-qualified subset of proposals.
- Afterquoted (23%) measures every proposal uploaded and tracked through our platform, from formal RFPs to cold outbound proposals, without filtering.
Takeaway: a "good" conversion rate depends entirely on the definition. Pick the benchmark whose methodology matches yours, not the one with the nicest number.
12 hours a month wasted on blind follow-ups
Source: Afterquoted internal · per-rep average.
Sales reps on Afterquoted spend on average 12 hours a month on follow-up activity that produces no response, commonly shaped as the "just checking in" email. That is roughly a week and a half of focused selling time burned per rep, per month.
This observation has an external cousin. RAIN Group research reports that high-performing sales organizations spend meaningfully less time on proposal-related administrative work than average performers, and redirect that time toward discovery and relationship building. Our platform data points at the same truth from the other side: the wasted hours are concentrated in the "did they see it?" guessing game, which tracked links collapse to a few minutes.
Takeaway: if you do nothing else this quarter, switch to signal-triggered follow-ups. Templates in our proposal follow-up email templates.
Shorter proposals win more often
Source: Proposify State of Proposals 2025 · won proposals averaged 11 pages, lost proposals averaged 13 pages.
This is a third-party benchmark, not ours, and it is the cleanest public evidence that length and outcome are linked. Proposify's 2025 report, which analyzes proposals built in their platform, found that proposals that closed averaged 11 pages while proposals that were lost averaged 13 pages.
The gap is small enough to be humbling, and large enough to be real. Two pages of cutting improves your odds. Twenty more does not.
The same report also finds that proposals with interactive elements (pricing tables you click through, video in the deck) convert meaningfully better than static equivalents, and that proposals with embedded e-signature close materially faster. Aberdeen Group's widely-cited e-signature research points in the same direction (roughly +18% conversion lift, cited across the industry since 2019).
Takeaway: trim before you add. If you are building a 20-page proposal, the first question is what to remove.
Tracking plus AI coaching lifts conversion +38%
Source: Afterquoted internal · average uplift for teams using both tracking and AI coaching on the platform, versus teams using neither.
On Afterquoted, teams that pair proposal tracking with the AI coaching layer see an average conversion lift of +38% compared with teams using neither. This is a platform average, not a controlled experiment; self-selection bias is real (teams that adopt AI coaching tend to be more experiment-oriented in general).
External research points at a similar direction, with more modest numbers for narrower interventions:
- Gartner research suggests teams implementing rigorous qualification see roughly +15% higher proposal conversion rates.
- DocuSign research reports that proposals with interactive elements convert about 23% better than static documents.
- Aberdeen Group data credits e-signature integration with +18% conversion lift and roughly 70% faster cycles.
Stack these interventions (tracking, AI coaching, stronger qualification, interactivity, e-signature) and compounding effects are plausible. Expect your own mileage to depend on starting point and execution discipline.
A 'good' conversion rate depends entirely on the definition. Pick the benchmark whose methodology matches yours, not the one with the nicest number.
Win rate falls as deal size rises
Source: Landbase 2026 B2B win rate benchmarks, with independent corroboration in Bidara 2026.
Across Landbase's 2026 benchmark dataset, win rate is inversely correlated with deal size:
- Under $50,000 per deal: 25-35% win rate
- $50,000 to $250,000: 18-28%
- $250,000 to $1,000,000: 12-22%
- Over $1,000,000: 10-18%
The explanation is structural: larger deals involve more stakeholders (Gartner puts enterprise buying committees at an average of 13 decision-makers), longer cycles, and more scrutiny from procurement and legal. None of this is surprising. The usefulness of the benchmark is that it lets you judge your own number against your deal-size bucket, not against a global average that does not match your pipeline.
Our own Afterquoted data is consistent with this pattern without contradicting Landbase's buckets, but our sample skews toward the $10,000 to $150,000 range where most of our customers operate.
Takeaway: report your conversion rate against your deal-size bucket, not against the aggregate.
See your own open rate, engagement, and follow-up patterns on your next proposals.
Free up to 20 proposals. Upload any PDF or deck. The four Afterquoted benchmarks above are metrics you can see on your own dashboard within a week.
Start free →How to use these benchmarks
Three quick notes before you paste any of these numbers into a board deck.
First, benchmarks are for comparison, not for setting strategy. Knowing the 23% Afterquoted average or the 35% PandaDoc 2023 average tells you where you sit in the distribution. It does not tell you what to change. For the how, see our how to improve proposal win rate playbook.
Second, segment ruthlessly. A 23% platform average hides a range from roughly 30% on small deals to well under 15% on large enterprise deals. Report against your bucket.
Third, cite what you use. Every benchmark above has a named source. If someone asks where the number comes from, you should be able to answer without hedging. That is the baseline we hold ourselves to.
Frequently asked questions
Yes. Cite the specific source listed under each benchmark. For Afterquoted averages, attribute as "Afterquoted internal · 2026". For third-party numbers, cite the original source (Landbase, PandaDoc, Proposify, etc.) and optionally this page as a reading entry-point.