Quota attainment collapsed to 43%. Stop blaming your reps.

I've sat in enough QBRs to know what happens when the attainment number hits the screen. The room gets quiet. Someone asks what's going on with the team. Leadership starts talking about coaching, accountability, maybe a round of PIPs. By the end of the meeting, the conclusion is almost always the same: we need better people.

I've been watching this play out across B2B sales orgs for 15 years, and the pattern hasn't changed. What changed is the scale. RepVue’s Cloud Sales Index for Q2 2025, which draws on about 47,000 ratings from quota-carrying sales professionals at 246 cloud and software companies, found just 42.69% of reps hit quota. Ebsta’s 2025 GTM Benchmarks, published in April 2025, found 78% of sellers missed quota, up from 69% the year before. And the response from leadership is still "we need better reps."

That response is wrong. Not because the people don't matter, but because it treats a system-level problem as a talent problem. And until that framing changes, the attainment numbers won't either.

Quota attainment statistics at a glance (2026)

In the largest rep-level dataset, fewer than half of quota-carrying reps hit their number in 2025 and 2026. RepVue’s Cloud Sales Index for Q2 2026, built from about 58,500 ratings at 252 cloud and software companies, puts quota attainment at 43.60%. The Bridge Group’s 2026 AE research, published in June 2026 from 158 B2B companies, found 48% of account executives at quota, down from 51% in 2024. Every figure below links to its source.

These numbers come from different instruments, so they don’t match. RepVue collects answers from reps. The Bridge Group, ICONIQ and Salesloft survey sales and go-to-market leaders. Ebsta pairs pipeline data with a survey of CROs. Read together, the newest share-of-reps figures put between 43% (RepVue) and 48% (Bridge Group, AEs) at quota, with SDRs higher at 60%. On a typical AE team, more reps finish below the line than above it.

What is the average quota attainment?

There are two answers, and both have 2026 data. The share of reps who hit 100% of quota was 43.60% in RepVue’s Cloud Sales Index for Q2 2026, built from about 58,500 ratings at 252 cloud and software companies. Average quota attainment reported by sales leaders runs higher: Salesloft’s 2026 U.S. Revenue Benchmark Report, fielded by Censuswide among 500 U.S. sales and revenue decision-makers, put it at approximately 62%.

The rep-level number has barely moved in a year. RepVue’s share of reps hitting quota stayed inside a band of less than two points for five straight quarters:

RepVue called Q1 2026 a new high-water mark, then reported attainment retreating to 43.60% in Q2 2026 as its Inbound Leadflow Sentiment score fell to the lowest level in the index’s recent history. Forrester’s Seth Marrs put average quota attainment for B2B sales organizations at 47% in March 2023 and argued that roughly half of sellers at quota is what a plan built around the median seller should produce. That holds when quota is set at the median. It stops holding when the quota itself is padded.

Why most reps miss quota: over-assignment is built into most plans

Most companies hand out more quota than the revenue plan needs. ICONIQ Growth’s sales compensation guide, published in May 2023 from a March 2023 survey of 236 B2B SaaS go-to-market executives, found 58% of companies over-assign quotas, typically by 20 to 30%, padding each rep’s number beyond what the company target requires. Targets are still climbing: in Salesloft’s 2026 U.S. Revenue Benchmark Report, 68.4% of respondents said their pipeline quotas had increased.

The logic sounds reasonable on paper: set the bar high and people will stretch to reach it. If the target is $2M, the theory goes, the rep will land somewhere around $1.5M and you've accounted for the gap in your plan.

Except when every rep in the org is carrying an over-assigned number, the math collapses. You haven't built a stretch culture. You've built a system where the majority of your team is set up to miss before the quarter even starts.

Quota attainment by role and deal size

Attainment differs sharply by role. The Bridge Group’s 2026 AE research (158 B2B companies, June 2026) found 48% of account executives at quota, and its 2025 SDR research (351 B2B companies, February 2025) found 60% of SDRs at quota, the lowest in that study’s history. A finer role-by-role split comes from RepVue data published by The Quota in November 2023, with data as of November 14, 2023:

Deal size cuts the other way. In RepVue’s Q2 2026 index, sellers with average deals above $200K posted the highest attainment at 48.60%, and sellers of deals under $10K the lowest at 39.99%. Enterprise AEs trailed in the 2023 role data while large-deal sellers lead in 2026, which points at deal economics and quota design rather than deal complexity on its own.

In the Ebsta and Pavilion 2024 B2B Sales Benchmarks, 69% of reps fell short of quota. The same report shows what moves that number: average quota targets were 19% smaller than the year before, and Ebsta estimated that 79% of reps would have missed had quotas stayed flat. Ten points of the miss rate moved with the targets.

What does the quota distribution curve look like?

Lopsided. Most of the team sits below 100% of quota, and a small group above it carries most of the revenue. RepVue’s Cloud Sales Index for Q2 2026 found 43.60% of reps hit quota across about 58,500 ratings at 252 cloud and software companies, which puts the median rep under the line. Salesloft’s 2026 U.S. Revenue Benchmark Report, fielded by Censuswide among 500 U.S. sales and revenue decision-makers, found the top 10% of sellers generate 47.4% of closed-won revenue. The Ebsta and Pavilion 2024 B2B Sales Benchmarks, covering 4.2 million opportunities across 530 companies, found 17% of reps generate 81% of revenue, and only 15% of sales teams had more than half their reps reach 80% or more of quota.

That shape matters for planning. A quota model that assumes the middle of the team lands near 100% is planning against a curve that does not exist, and the role table above shows the curve sitting furthest left for mid-market and enterprise AEs.

Why does 17% of your team generate 81% of the revenue?

The stat comes from the Ebsta and Pavilion 2024 B2B Sales Benchmarks, an analysis of 4.2 million opportunities across 530 companies: 17% of reps generate 81% of revenue. I used to look at it and think it was a talent distribution problem. Top performers are just wired differently. After working inside enough orgs to see the mechanics up close, I think that read is incomplete.

The top 17% aren't outperforming because they sell harder. They're working fundamentally different pipelines. Better account distribution. More qualified opportunities. Sales cycles that are actually proportional to the targets set against them. Once you account for those variables, the gap between your best and your average gets a lot smaller than leadership thinks it is.

But here's what happens instead. Leadership sees the concentration and concludes the bottom 83% are the problem. So they invest in more coaching, more pressure, tighter performance management. They hire more aggressively. None of it moves the number, because the architecture underneath the team is producing the outcome it was designed to produce.

What happens when most of the team is built to miss?

Turnover climbs. In the Ebsta and Pavilion 2024 B2B Sales Benchmarks, turnover among reps not making the grade rose from 22% to 36%. The downstream effects are the part that keeps me up at night, because they compound.

Reps aren't leaving because they're weak. They're leaving because they spent a year working toward a number their own company knows they can't hit. Smart people feel that. They don't always articulate it clearly, but they feel the difference between genuine underperformance and being set up to fail. And they respond by leaving.

So turnover accelerates. Your best reps, the 17% who actually carry the load, start looking outside because now they're managing the morale of a team that's demoralized by design. Cost per hire compounds. Training investment dilutes into a revolving door. You lose institutional knowledge and operational efficiency every cycle.

I've watched this become a vicious loop inside companies. Over-assign quota. Watch attainment fall. Blame the team. Over-staff the org to make up for it. Burn through high performers faster. Lose them to companies that don't run their orgs this way. Hire cheaper to backfill. Attainment drops further. Repeat.

The cost of that loop isn't just the revenue you don't close. It's everything else you torch in the process.

Is the pipeline problem the one nobody wants to name?

This is where the conversation usually stops, and it's where it should start. RepVue’s Inbound Leadflow Sentiment score fell to 2.65 in its Q2 2026 Cloud Sales Index, the lowest level in the index’s recent history. Salesloft’s 2026 U.S. Revenue Benchmark Report, fielded by Censuswide among 500 U.S. sales and revenue decision-makers, found an estimated 19.7% of pipeline is affected by stalled deals, slipped close dates and other execution breakdowns.

When I dig into the deal-level data across a sales org, the pattern isn't that reps are losing more deals at the bottom of the funnel. The funnel is narrower at the top. Fewer qualified opportunities are entering the pipeline relative to the quota assigned against it. The gap between required activity and available opportunities shows up by Q2, and the rest of the year becomes a scramble.

Reps spend the back half of the year chasing deals they know won't close, extending timelines, shrinking deal size. All of that looks like a selling problem on a dashboard. It's a pipeline problem. And if you misdiagnose it, you end up coaching reps on discovery technique when what they actually need is more viable opportunities against a realistic number.

This is also why attainment is so predictable by role and segment. Enterprise deals have longer cycles and fewer at-bats per quarter. Assign the same quota logic across segments with fundamentally different deal economics, and you'll see attainment drop the moment the funnel reality meets the spreadsheet. This pipeline gap also shows up in how CRM data gets manipulated to mask it: close dates get pushed forward, deal amounts stay inflated, and the forecast obscures the structural shortfall underneath, which is why measuring sales forecast accuracy honestly matters as much as the quota. It is the same incentive that explains why good reps enter bad data.

What actually changes when you restructure the baseline?

Everything becomes measurable again. That's the real upside, and it's bigger than it sounds.

Right now, attainment data across most B2B orgs is partially a performance measure and partially theater. A rep sitting at 38% could be genuinely underperforming or could be a strong seller working against a number that was never achievable. You can't tell. The signal is contaminated by the quota structure underneath it.

When you separate the structural piece from the talent piece, you can actually see who your people are. You can identify whether low attainment is a pipeline generation issue, a territory design issue, a comp structure issue, or a genuine capability gap. You can build performance management that doesn't operate as a morale tax on two-thirds of your team.

You start treating quota as a measurement instrument instead of a motivational device. And a measurement instrument points you toward the real levers: pipeline generation, opportunity quality, sales cycle compression, account stratification. Those are where attainment actually moves.

The full data behind all of this, including the benchmarks by segment and role, is in The State of B2B Revenue 2026. If you want to understand how this connects to where your sellers actually spend their time, we dug into how much of the week sellers spend selling. And if you want to understand why the pipeline stays thin in the first place, buyer behavior has shifted further than most orgs have adjusted for.

The quota crisis is a system crisis. The reps are telling you that. The data is telling you that. The question is whether leadership is listening.