Sales Rep Capacity Calculator and Prospecting Unit Economics
Prospecting Metrics 13 min
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Business problem
Sales leaders mandate unrealistic activity targets ("every SDR must send 150 bespoke emails daily") or teams drown in manual friction, contacting merely 15 accounts weekly. Lacking mathematical capacity models results in wasted software budgets with zero quantifiable impact on qualified pipeline.
Proven method
Capacity Engineering bridges rep time budgets with revenue unit economics:
| SDR Operating Model | Time per Tier 1 Account | Monthly Account Bandwidth | Average Cost per SQL | Revenue Generated / Rep |
|---|---|---|---|---|
| Manual (Legacy) | 45 minutes | ~ 80 - 100 accounts | ~ $600 | $10,000 |
| Hybrid (AI-Augmented SDR) | 12 minutes | ~ 300 - 400 accounts | ~ $180 | $35,000 |
| High-Automation Machine | 2 minutes (validation) | ~ 1,200+ accounts | ~ $65 | $60,000+ |
- Map monthly rep capacity: 160 working hours = 70h active prospecting, 40h discovery/demos, 30h CRM administration, 20h internal meetings and training.
- Measure actual unit duration per task: company research, contact lookup, copy drafting, and sequence administration.
- Deploy AI to alleviate operational bottlenecks: cutting account research from 25 mins to 5 mins via long-context LLM dossier generation.
- Calculate Unit Economics: fully loaded SDR cost (salary + tool licenses) divided by generated Sales Qualified Leads (SQL) must achieve an LTV:CAC ratio of at least 3:1.
Market example
- BAD
- Demanding 100 hyper-personalized outbound emails daily without AI support. A rep physically needs 30 hours per day, inevitably reverting to generic copy-paste templates that yield 0.2% reply rates and fast burnout.
- GOOD
- Deploying the capacity model: the SDR allocates 60 hours monthly to targeted outbound. Equipping them with Clay and Claude compresses account research from 40 to 10 minutes. The rep addresses 360 strategic accounts, producing 24 qualified discovery calls at $500 monthly software expense with a 14x ROI.
Ready-to-use prompt
You are a Revenue Operations (RevOps) Director and sales efficiency consultant. Context: I am structuring a Rep Capacity Model and Unit Economics calculator for our outbound prospecting team. Parameters: - Number of SDRs: [NUMBER — e.g., 2] - Fully loaded monthly cost per rep: [AMOUNT — e.g., $6,000 / month] - Monthly Outbound Stack Expense: [AMOUNT — e.g., $800 / month] - Average Contract Value (ACV): [AMOUNT — e.g., $25,000 / year] - Sales Cycle Duration: [DAYS — e.g., 60 days] Task: 1. Construct an outbound capacity matrix allocating 160 monthly working hours across sales tasks. 2. Model performance across 3 configurations: Fully Manual, AI-Augmented, and High-Automation. 3. Compute core Unit Economics metrics: - Cost per Sales Qualified Lead (Cost per SQL) - Required Pipeline Conversion Rate to hit payback breakeven - Projected ROI on AI sales software investments 4. Identify 3 Early Warning Metrics signaling rep overload or declining software leverage. Format: Structured financial model table followed by strategic executive recommendations.
Model rekomendowany: Claude 3.5 Sonnet / GPT-4o Copy and paste into ChatGPT, Claude or Perplexity
ALTERNATYWNE SCENARIUSZE
Variations & alternative scenarios
Full-cycle Account Executive model: modeling capacity under a 70% closing / 30% self-sourcing split.
Agency model: multi-client rep bandwidth calculation across independent domains and mailboxes.
Practical exercise
Calculate your actual monthly prospecting hours, divide by average time spent per vetted account, and compute your true monthly account capacity.
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