Design sales territories that reps believe are fair
Produces a complete territory model — carving logic, precise ownership definitions, a fairness analysis, rules of engagement, and rebalancing triggers. The fairness check and dispute rules are what most homegrown territory splits skip, and they're exactly what causes rep churn and CRM chaos six months later.
You are a sales operations consultant who has designed territory models for B2B teams from 3 reps to 300. You know territory design fails in two ways: mathematically unfair splits that burn trust and drive attrition, and models so complex nobody can explain who owns what. Your bias is the simplest model that is defensibly fair. Design a territory model for my team: 1. Recommend a primary carving dimension — geography, industry vertical, company size segment, named accounts, or round-robin — with two sentences on why it beats the alternatives for my situation. 2. Define the territories: what each rep owns, described precisely enough to resolve any account in ten seconds. 3. Fairness check: estimate the opportunity balance across territories and flag any split where one rep's patch is worth 1.5x another's. 4. Rules of engagement: who gets inbound leads, what happens on account disputes, how existing relationships and open opportunities transfer. 5. Rebalancing triggers: the specific conditions (rep count change, territory outperforming by X) that should reopen the design, so you're not redrawing maps every month. Avoid: hybrid models with three carving dimensions, splits that ignore where current pipeline sits, and pretending equal account counts means equal opportunity. Before you write anything, interview me. Ask me these questions ONE AT A TIME, waiting for my answer each time: 1. How many reps carry a quota, and are any of them new or ramping? 2. Describe your addressable market — roughly how many target accounts, in which industries, sizes, and regions? 3. Is there meaningful variation in deal size or win rate across regions, verticals, or segments? Share what you know. 4. How do accounts get worked today, and what feels unfair or messy about it? 5. Any special cases — house accounts, strategic accounts, channel-owned accounts, existing rep relationships? Once you have my answers, produce the model. If my account data is too thin to judge fairness, tell me the minimum data pull that would fix that.
How to use it
- 1
Copy the prompt into Claude, ChatGPT, or any LLM.
- 2
Pull a rough count of target accounts by segment or region before starting — even an Apollo search count helps.
- 3
Answer question 4 candidly; the current mess is the design constraint that matters most.
- 4
Stress-test the output with edge cases: 'Acme is HQ'd in Texas but the buyer sits in New York — who owns it?'
- 5
Socialize the fairness analysis with reps before announcing the map — evidence kills grievance.
Best practices
Under 6 reps, resist geographic splits — segment or round-robin models usually beat geography until density justifies it.
Weight territories by pipeline potential, not account count; 200 SMBs can be worth less than 30 mid-market accounts.
Write the rules of engagement into your CRM as assignment rules the same week, or the model stays theoretical.
Ask the model to draft the rep-facing announcement too — how a territory change is communicated decides whether it sticks.
Example: what this looks like in practice
A sales leader at a 25-person logistics software company has 5 AEs working a free-for-all list, and her two senior reps keep colliding on the same warehousing accounts. She answers the interview: 4,000 target accounts across three verticals, deals in 3PL run 40% larger than in retail logistics, one rep is in month two of ramp. The model recommends vertical carving over geography, gives the ramping rep the retail patch with round-robin overflow, weights the 3PL vertical across the two senior reps with a named-account split, and writes dispute rules: CRM timestamp wins, existing opportunities transfer with a 50% commission split for one quarter. The fairness table shows all five patches within 20% of each other on estimated pipeline value.
Best fit
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Pick the single dimension that best predicts opportunity variation in your market — geography if travel or regional relationships matter, vertical if industries buy differently, size segment if deal motion changes with company scale, round-robin if your market is homogeneous. This prompt recommends one primary dimension and warns against the three-dimension hybrids that nobody can administer.
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