Sales Quota

Definition A sales quota is a specific, measurable goal assigned to a seller or sales unit that defines “success” for a given interval (for example, “close $600K in new ARR this quarter”). Quotas are typically tied directly to variable compensation, so they function as both a performance benchmark and a behavioral steering mechanism. They can be set at multiple levels: individual AE/SDR, pod, region, segment, or entire org. Effective quotas align top-down company targets (ARR plan, growth goals) with bottom-up reality (historical performance, territory potential, win rates, and capacity), so that if everyone hits quota, the company hits or beats its plan. How to Calculate Quotas are usually derived top-down from the company’s revenue plan, then allocated across teams and reps using capacity and historical data. Basic top-down approach: Start with the annual or quarterly revenue goal (for example, “$24M in new ARR this year”). Decide how much will come from each segment (SMB/MM/Enterprise), region, and motion (new vs. expansion). For each team, calculate realistic rep capacity using: Average quota attainment (e.g., 70–80% historical) Average deal size (ACV) Win rate Ramp time and number of ramping reps Set individual quotas so that: Sum of rep quotas ≥ plan (often 1.1–1.3× plan to account for under-attainment) Quotas are achievable (60–80% of fully ramped reps at or above 100% is a common design goal). Example: Company new-business ARR target: $12M 10 fully-ramped AEs Target over-assignment factor: 1.2× (to offset underperformance) Total AE quota pool = $12M × 1.2 = $14.4M → per-AE annual quota = $1.44M (or $360K per quarter). Other quota types: Revenue quota: $X in ARR or TCV. Volume quota: Y closed/won deals or new customers. Activity quota: Z meetings held, demos completed, outbound touches. Hybrid/MBO: Mix of revenue plus strategic objectives (for example, new logos in a segment, expansion deals, multi-year contracts). Why Quota Matters Benchmarks for quota design in B2B SaaS are typically expressed in ranges and patterns rather than hard numbers.​ Defines what “good” looks like for reps and managers. Drives compensation, effort, and prioritization (what pipeline to pursue, what deals to drop). Determines hiring plans, coverage models, and overall revenue capacity. If quotas are systematically too high, they demotivate reps, spike attrition, and push sandbagging or bad selling behavior. If they are too low, the organization risks overpaying for underperformance and missing its growth potential. Proper quota design is one of the highest-leverage responsibilities of CROs and RevOps. Industry Benchmarks Patterns vary by stage and segment, but common benchmarks for B2B SaaS: Benchmark Typical Range / Pattern Notes Over-assignment (sum of all rep quotas ÷ plan) 1.1× – 1.3× plan Ensures company hits plan even if some reps underperform. % of fully ramped reps at/above 100% quota 60% – 80% Healthy distribution; avoids “no one can win” or “everyone wins.” Quota : OTE (AEs, MM/ENT) 4× – 6× annual quota to annual OTE Higher ratios possible in very strong markets. Time to full quota (ramp) 6 – 9 months Early quarters often at 25–75% of full quota. New business vs. expansion mix in quota 70–90% new business / 10–30% expansion Varies by motion and maturity; more expansion at later stages. Planning cadence Annual quota setting with quarterly review Structural changes only, to preserve trust and stability. Real-World Examples A mid-market SaaS team with 8 AEs and a $6M annual new ARR goal sets each AE’s annual new-business quota at $1.1M, yielding $8.8M in total quotas (about 1.47× plan). With 70% attainment on average, they expect to hit the $6M plan. An enterprise team moves from pure revenue quota to a hybrid model (new logos + expansion ARR + multi-year deals) to incentivize strategic, sticky business instead of just “end-of-quarter discounting.” An SDR org uses activity-based quotas (qualified meetings held + opportunities created) mapped back to downstream closed-won expectations so that new-business AE quotas remain achievable. Common Mistakes Copy-paste quotas from last year without revisiting market conditions, product maturity, or territory potential. Setting quotas purely top-down (divide plan by reps) without checking bottom-up capacity, leading to “impossible” numbers. Ignoring ramp and assigning full quotas to new reps too early, poisoning culture and retention. Not adjusting for territory potential so some reps have “easy” patches and others face structural disadvantages. Misaligned comp plans, where accelerators or thresholds don’t match quota difficulty, leading to weird behavior (for example, sandbagging, pushing deals into the next period). The Fix: Use a hybrid top-down/bottom-up planning process, incorporate historical attainment, win rates, and territory potential, explicitly model ramp, and test quotas so that if the designed percentage of reps perform at historical norms, the company hits or exceeds plan. Frequently Asked Questions How is a sales quota different from a target or goal? “Sales quota” usually refers to a formal, comp-tied, time-bound number assigned to a rep or team. Goals can be broader (for example, “grow in enterprise”) and not necessarily tied to variable comp. How often should quotas be changed? Most SaaS orgs set quotas annually and lock them, with the ability to adjust mid-year for major structural changes (new territories, big product shifts, M&A). Constantly changing quotas destroys trust. What percentage of reps should hit quota? Healthy design often aims for roughly 60–80% of fully ramped reps at or above 100% of quota, with a meaningful upside for top performers via accelerators. Should SDRs and AEs have different quota structures? Yes. SDR quotas are usually activity- or opportunity-based, while AE quotas are mainly revenue/TCV/ARR‑based, sometimes with overlays for strategic objectives. How do you set quota for expansion reps or CSMs? Commonly as a mix of expansion ARR, renewals (GRR/NRR targets), and sometimes specific motions (upsell of certain products, multi-year renewals), calibrated to historical expansion patterns and book-of-business size.