← Hub
Pulse ← Library ⚡ Hire a Fractional CRO
Pulse Knowledge Library

What's the difference between hunters and farmers and when to hire each?

Kory White, Chief Revenue Officer
Curated byKory WhiteChief Revenue Officer  ·  CRO Syndicate
👍 Yup or 👎 Nope — vote this up its category:
📅 Published · Updated · 18 min read
What's the difference between hunters and farmers and when to hire each?

Hunters vs. Farmers, the short version: Hunters are high-activity new-logo closers (40-60 prospecting touches/week, 15-25% close rate on cold opps, 70-80% variable comp). Farmers are relationship-driven account growers (10-20 strategic touches/week, 40-50% close rate on warm/expansion opps, 30-50% variable comp).

Hire hunters for greenfield, new vertical entry, or low-touch transactional SaaS. Hire farmers when NRR is your primary growth lever (typically $50M+ ARR) or churn exceeds 8%. Hiring a hunter to farm an existing book is a known anti-pattern: they will ignore QBRs, miss expansion signals, and the book will leak 2-4 points of NRR within 12 months.

What's the difference between hunters and farmers and when to hire each?

Sourced benchmarks (anchor your hiring math here):

The mechanics, not just the vibes:

The hunter/farmer split is fundamentally a *commission topology* problem, not a personality problem. Two reps with identical Predictive Index profiles will behave like a hunter or a farmer depending entirely on what their plan pays. Build the plan first, then hire to fit.

Hunter comp formula (clean):

Farmer comp formula (clean):

CRO overlay comp (the part most companies forget):

The CRO/VP Sales gets a blended plan that prevents either-side gaming:

This structure makes the CRO genuinely indifferent between hiring hunters or farmers, which keeps them honest about org design. If their plan over-weights new ARR, they will starve the farmer team and you will pay for it in NRR 18 months later.

Worked example (mid-market SaaS, $30M ARR):

Hunter Hailey: $180k OTE (45/55), $900k new ARR quota. Closes $1.1M = 122% attainment.

Farmer Frank: $150k OTE (60/40), $1.2M expansion quota, manages 35 accounts ($14M total ARR book).

Clawback edge cases (write these into the plan or you will pay them):

Why the clawback matters: Without a clawback, farmers learn to over-sell expansion seats that the customer never uses, which inflates Q1 expansion ARR and explodes as Q4 churn. The clawback aligns the farmer's bank account with the customer's actual product adoption. The clawback is the mirror image of the over-quota accelerator design covered in (q05): accelerators reward landing more, clawbacks ensure what was landed actually sticks.

Attribution model for split deals (the part most companies botch):

When a hunter closes a logo and a farmer expands it 18 months later, who gets credit?

Territory design math (the boring but load-bearing part):

For hunters: territory = TAM (total addressable accounts) / number of hunters, with each hunter holding 200-800 named target accounts depending on ACV. Rule of thumb: 200 named accounts at $100k ACV; 500 at $25k ACV; 800+ at <$10k ACV. Below 150 accounts, hunters run out of pipeline by Q3; above 1,000, they can't penetrate any account meaningfully.

For farmers: book = installed customers, capped by managed-relationship limit. Rule of thumb: 20-35 accounts per farmer, with total managed ARR per farmer of $3M-$8M depending on segment. Below $2M managed ARR, the role doesn't pencil out (OTE/managed ARR ratio > 5%).

Above $10M managed ARR, the farmer can't QBR every account quarterly without dropping balls.

90-day onboarding milestones (split by profile):

Hunter onboarding (greenfield territory):

Farmer onboarding (inherited book):

Org-design recipes by stage:

Industry case studies (named, not anonymous):

A note on pay bands: the OTE figures above are deliberately mid-market. For the enterprise end of the hunter band — $100k+ ACV field reps — calibrate against the dedicated breakdown in (q01); for the leadership layer that owns this whole hunter/farmer org, base-salary geography is covered in (q12).

Red flags - when NOT to hire either profile:

Don't hire a hunter if:

Don't hire a farmer if:

The Bear Case (genuinely adversarial, not strawman):

The hunter/farmer framework is, frankly, a mid-2000s artifact and increasingly wrong on three fronts. Take this seriously before you build an org around it:

  1. PLG and product-led expansion have collapsed the farmer role. If your product expands itself (seat-based PLG, usage-based pricing with auto-scaling), you don't need farmers; you need a Growth/PLG ops team plus a small CSM bench. Companies like Figma, Notion, and PostHog scaled past $200M ARR with almost no traditional farmers. If you're hiring farmers in a PLG motion, you're paying $140k OTEs to do work the product is already doing for free. Audit your expansion ARR: how much of it is closed by a human vs. Self-serve? If self-serve is >70%, kill the farmer role.
  1. Modern SaaS is consolidating both roles into 'Full-Cycle AE' or 'Pod' structures. HubSpot, Gong, and many AI-native sales orgs now run pods (1 AE + 1 SDR + 1 CSM + 1 SE) where the AE owns logo-to-logo lifecycle. The hunter/farmer split adds handoff friction (commission disputes, account ownership ambiguity, customer confusion about who their rep is). In the worked example below, the 25%-tail commission share on a $14M book at a 7% expansion rate represents roughly $25k-$30k per farmer per year of dead-weight payout purely to lubricate handoffs — about 8-10% of expansion-commission spend. If you're under 200 reps, full-cycle pods typically eliminate that overhead and outperform the split.
  1. The personality test is largely pseudoscience. Schmidt and Hunter's 1998 meta-analysis (and its 2016 update by Sackett et al.) showed personality assessments have predictive validity of r=0.10-0.31 for job performance overall, with sales-specific extensions rarely exceeding r=0.35. The Caliper, OMG, and DiSC profiles commonly used in sales hiring sit in this band. By contrast, structured behavioral interviews score r=0.51, and prior job performance in similar role scores r=0.58. Hire on track record and comp design, not on a personality test labeling someone a hunter.

Counter to the bear case (with field data): Even in PLG and pod models, *someone* is doing hunter work (cold outbound to enterprise) and *someone* is doing farmer work (renewal protection, exec sponsorship). The labels may be wrong but the work is real. Bessemer's 2026 cohort analysis shows that companies running explicit new/expansion comp splits achieve median NRR of 116% vs. 104% for those running flat full-cycle plans at the same revenue band ($30-100M ARR).

The right move in 2026 is to keep the *work segmentation* (new vs. Expansion) and drop the *personality segmentation*. Build comp plans around behaviors, not archetypes.

When the framework breaks (be honest about this):

Interview scorecard (use this, not a personality test):

For a hunter role, score the candidate 1-5 on each:

For a farmer role, score the candidate 1-5 on each:

Decision tree for your next hire:

  1. What's the gap in our pipeline math? (New ARR shortfall vs. NRR shortfall.)
  2. What's our motion? (PLG, sales-led, hybrid.) If PLG-heavy, default to CSM hires over farmer hires.
  3. What's our ACV and sales cycle? <$15k ACV / <30 day cycle = SDR-to-Inside-Sales hunter pipeline; $50k+ ACV / 90+ day cycle = field hunter or farmer depending on greenfield vs. Installed base.
  4. What's the candidate's last 4-quarter attainment in a similar ACV/cycle? If they don't have it, you're paying tuition.
  5. Build the comp plan first. Show the candidate the plan. If their eyes light up at the new-logo accelerators, they're a hunter. If they ask about the expansion pool and clawback math, they're a farmer. Self-selection is more reliable than any personality test.

The single most expensive mistake: hiring a hunter into a farmer role to 'shake up the book.' The hunter will burn 6-12 months chasing white space, ignore QBRs, miss renewal signals, and you'll lose 2-4 points of NRR. By the time you fire them, you've spent $200k+ in salary and lost $500k-$1M in retention.

If the book needs energy, hire a farmer with a turnaround track record, not a hunter.

Counter-Case (where this entry's own advice can hurt you):

Everything above is the consensus playbook. Here is the adversarial read — the specific ways following this entry literally can cost you money. Read it before you implement.

  1. The clawback can manufacture the churn it is supposed to prevent. This entry recommends a 25-50% expansion clawback for 12 months. The unmodeled second-order effect: a farmer staring at a clawback exposure will *defer* a renewal price increase, *avoid* a hard expansion conversation, and *steer away* from accounts they privately judge shaky — exactly the accounts that most need active management. The clawback does not just punish bad sales; it taxes honest effort on hard accounts. If your churn is concentrated in a few wobbly logos, a heavy clawback can push farmers to quietly abandon them, and you lose the account anyway — now with zero salvage attempt. Cap clawback at 25%, time-decay it aggressively, and exempt CS-attributable churn, or you are paying for risk aversion.
  1. The 12-month ownership-transfer rule destroys institutional memory at exactly the wrong time. Forcing accounts from hunter to farmer at month 12 sounds clean. In practice, complex enterprise deals (90+ day cycles, multi-stakeholder) are still being *implemented* at month 12; the hunter holds context the farmer cannot reconstruct from CRM notes. A rigid transfer mid-implementation correlates with first-year churn spikes. The honest rule is event-based, not calendar-based: transfer at "go-live + 90 days of stable usage," not at a fixed date.
  1. Comp-design-first assumes you can predict the plan you need — you usually can't. This entry says "build the comp plan first, then hire to fit." But at <$10M ARR your motion is still moving; the plan you design in January is wrong by June. Over-engineering a hunter/farmer split before product-market fit stabilizes locks you into a topology you will pay severance to unwind. Below ~$10M ARR the correct move is often *no split at all* — full-cycle AEs on a simple plan — and revisit only when expansion ARR independently crosses ~30% of net-new.
  1. Hiring on "track record" has a survivorship problem the validity stats hide. Yes, prior performance predicts better than personality (r≈0.58). But quota attainment is not portable: a rep who hit 130% on warm inbound at a category leader may be a 60% rep cold-sourcing for an unknown brand. Normalize attainment by inbound-vs-self-sourced mix and brand strength, or "hire on track record" quietly becomes "hire whoever had the easiest territory."
  1. The named case studies are confounded. HubSpot, Gong, and Snowflake have elite NRR — but they also have elite products, brands, and capital. Attributing their retention to the hunter/farmer comp split is reverse causation: great products *enable* expansion comp to work, not the other way around. A mediocre product with a textbook comp split still churns. Fix product and onboarding first; comp topology is a multiplier on a number that must already be positive.

The steelman of the entry survives all five: work segmentation (new vs. Expansion) beats personality segmentation, and explicit comp does lift NRR in the data. But implement the *mechanisms* with the counter-case caveats wired in — decayed clawbacks, event-based transfers, plan-after-PMF — or the playbook backfires.

Related Pulse entries (build the full hiring picture):

TAGS: hiring,hunters-farmers,sales-strategy,rep-types,quota,comp-design,nrr,plg,onboarding,interview

FAQ

What are the activity and close-rate profiles that distinguish hunters from farmers? Hunters run 40-60 prospecting touches per week with a 15-25% close rate on cold opps and 70-80% variable comp. Farmers run 10-20 strategic touches per week with a 40-50% close rate on warm/expansion opps and 30-50% variable comp.

The article frames the split as a commission-topology problem, not a personality problem.

How should hunter and farmer comp formulas differ on commission rates? A clean hunter plan pays 40-50% base, 8-12% on new ARR (uncapped with 1.5x-2x accelerators), and only 0-2% on expansion ARR so they don't farm, with quota at 4.5-5.5x OTE in new ARR. A clean farmer plan pays 55-70% base, 6-9% on expansion ARR, 1-3% on gross renewal, with a NRR gate requiring book NRR of 105%+ and a 25-50% churn clawback if a logo churns within 12 months.

The near-zero expansion rate for hunters and the NRR gate for farmers are the load-bearing design choices.

When should I hire farmers instead of hunters? Hire farmers when NRR is your primary growth lever (typically $50M+ ARR) or churn exceeds 8%, and hire hunters for greenfield, new vertical entry, or low-touch transactional SaaS. Hiring a hunter to farm an existing book is a known anti-pattern: they ignore QBRs, miss expansion signals, and the book leaks 2-4 points of NRR within 12 months.

Per Bessemer, top-quartile public SaaS show NRR of 118-125% driven by farmer-led expansion.

How does the CRO overlay comp prevent either-side gaming? The CRO gets 50-60% base, 40% of variable on total ARR, 30% on NRR target (gated at 105%), 20% on hunter team attainment, 10% on farmer team attainment, plus a clawback if attrition on either team exceeds 35% per year.

This makes the CRO genuinely indifferent between hiring hunters or farmers. Without it, a CRO whose plan over-weights new ARR will starve the farmer team and the company pays in NRR 18 months later.

What attrition and ramp differences should I budget for between the two roles? Per RepVue 2025, hunter voluntary attrition runs 28% per year against 14% for farmers, so a 10-hunter team needs roughly 3 backfills per year at $40-60k each in recruiting and ramp loss. Per Bridge Group, hunter ramp in greenfield runs 6-9 months while farmer ramp in an inherited book runs 2-4 months.

Hunter quota attainment medians (53-62%) also sit below farmer attainment (71-78%).

Keep reading
Was this helpful?  
⌬ Apply this in PULSE
Gross Profit CalculatorModel margin per deal, per rep, per territoryRecruiting CalculatorHow many reps you need before you hire
Related in the library
More from the library
pulse-q · revopsShould I open or buy a Keke's Breakfast Cafe franchise in 2027?pulse-q · revopsShould I open or buy an EcoShield Pest Solutions franchise in 2027?pulse-q · revopsShould I open or buy an El Pollo Loco franchise in 2027?pulse-q · revopsShould I open or buy a Code Wiz franchise in 2027?pulse-q · revopsShould I open or buy a Bloomin' Blinds franchise in 2027?pulse-q · revopsShould I open or buy a Sunny Street Cafe franchise in 2027?pulse-q · revopsShould I open or buy a Farmer Boys franchise in 2027?pulse-q · revopsShould I open or buy a Surface Specialists franchise in 2027?pulse-q · revopsShould I open or buy a Bishops Cuts/Color franchise in 2027?pulse-q · revopsShould I open or buy a Hunt Brothers Pizza franchise in 2027?pulse-q · revopsShould I open or buy a Steak Escape franchise in 2027?pulse-q · revopsShould I open or buy a Luna Grill franchise in 2027?pulse-q · revopsShould I open or buy a HealthSource Chiropractic franchise in 2027?pulse-q · revopsShould I open or buy a Paris Baguette franchise in 2027?pulse-q · revopsShould I open or buy a FYZICAL Therapy & Balance Centers franchise in 2027?
Was this helpful?