Bottoms-Up Build Recipe
A step-by-step guide to building the revenue plan from capacity and current-state pipeline, independent of top-down targets.
Step 1: Segment Your Business
Divide total addressable revenue into segments that have different unit economics, sales processes, or conversion rates.
Typical segmentation dimensions:
- Revenue type (New Business / Expansion / Renewal)
- Customer size (SMB / Mid-Market / Enterprise)
- Go-to-market motion (self-serve / sales-assisted / sales-led)
- Product line or vertical (if applicable)
Example segmentation:
New Business - SMB (self-serve + sales-assist): 20% of target revenue
New Business - Mid-Market (sales-led): 35% of target revenue
Expansion (usage-based upsell + success-driven): 25% of target revenue
Renewal (contractual + health-based retention): 15% of target revenue
Professional Services (delivery + implementation): 5% of target revenue
Why segment: Blended forecasts hide reality. SMB renewal rates (95% GRR) behave completely differently from Enterprise churn (88% GRR). Self-serve new business converts at 5x the velocity of sales-led enterprise. By segment, you see where the business is stable and where it is fragile.
Step 2: Document Current-State Baseline
For each segment, lock the prior-year actual or current-year run-rate.
Template:
Segment Current ARR/Bookings % of Total Data Source
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New Business - SMB $1.2M 20% CRM closed-won 2025
New Business - MM $2.1M 35% CRM closed-won 2025
Expansion $1.5M 25% CRM expansion bookings
Renewal $0.9M 15% Contract database
Professional Services $0.3M 5% Project tracking
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TOTAL $6.0M 100%
Lock this baseline. Do not adjust it during the planning process. This is your anchor.
Step 3: Build the Capacity Model
The capacity model answers: "If our sales team does exactly what they did last year, how much revenue should we produce?"
The Capacity Model Formula
Annual Bookings Capacity = (FTE Available) × (Ramp Factor) × (Annual Quota per AE)
Detailed formula with adjustments:
STARTING POINT:
Tenured AE headcount (100% productive): 5 FTE
New AE hires (expected to ramp): 2 FTE
Ramp timeframe for new hires: 6 months
RAMP ADJUSTMENT:
Tenured productivity: 5 FTE × 100% = 5.0 FTE
New hire ramp (assume 50% avg over 6-month): 2 FTE × 50% = 1.0 FTE
Total effective FTE for year: 6.0 FTE
QUOTA ASSIGNMENT:
Annual quota per tenured AE: $850K
Annual quota per new AE (after full ramp): $850K
BOTTLENECK ANALYSIS:
Is pipeline constrained by available opportunities? YES (pipeline generation is the constraint)
Haircut for pipeline availability: ×85% (historical fill rate)
CAPACITY CALCULATION:
Base capacity: 6.0 FTE × $850K/AE = $5.1M
Pipeline constraint haircut: $5.1M × 85% = $4.335M
Territory overlap / allocation efficiency: ×95% = $4.118M
FINAL CAPACITY ESTIMATE: $4.1M annual bookings
Capacity Model Components in Detail
Headcount Plan
Start with committed headcount (approved budget) by role:
Role Current Hiring (Year 1) Net Change End-of-Year
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Account Executives 7 2 +2 9
SDRs (pipeline gen) 4 1 +1 5
Sales Engineers 2 0 0 2
Sales Manager 1 0 0 1
Ramp Profile by Role
Each role has a ramp curve. Ramp period is the time until 100% productivity. Production during ramp is typically:
ACCOUNT EXECUTIVE (6-month ramp):
Month 1: 0% of full quota (onboarding, territory learning)
Month 2: 25% of full quota (first deals in pipeline)
Month 3: 50% of full quota
Month 4: 70% of full quota
Month 5: 85% of full quota
Month 6: 100% of full quota (fully ramped)
SDR (3-month ramp):
Month 1: 20% of pipeline target
Month 2: 60% of pipeline target
Month 3: 100% of pipeline target
Sales Engineer (2-month ramp):
Month 1: 50% of typical deal-support load
Month 2: 100% of typical deal-support load
Calculate effective FTE for the year:
If you hire 2 AEs in Month 1 (January) with 6-month ramp:
- Jan-Jun: producing 0% + 25% + 50% + 70% + 85% + 100% = 330% total over 6 months = 55% average
- Jul-Dec: producing 100% × 6 months = 600% total over 6 months = 100% average
- Annual contribution: (330% + 600%) / 12 months = 77.5% of a full FTE
Alternatively, use a simplified approach: average new-hire at 80% of a full-year tenured rep. This is conservative.
Annual Quota by Role
Set quotas based on historical achievement or benchmarks:
Role Quota per Rep Number of Reps Total Quota
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Account Executive $850K 9 (7 + 2 ramping) $7.65M
SDR (pipeline gen) $400K meetings 5 (4 + 1 ramping) $2M meetings created
Sales Engineer Support role 2 $0 direct
Quota setting guardrails:
- Set based on historical attainment (if last year AEs hit $800K at 78% attach rate, quota is $800K, not $1M)
- Adjust for known market changes (new product launch, new vertical entry, lost customer)
- Do NOT set quotas to match top-down targets until bottoms-up is done
Productivity Assumptions
Document the assumptions that connect headcount and quota to bookings:
Assumption Value Source/Confidence
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Deal close rate (overall) 60% CRM last 12 months
Average deal size (New Biz SMB) $25K CRM average 2025
Average deal size (New Biz MM) $85K CRM average 2025
Sales cycle length (SMB) 45 days Salesforce field audit
Sales cycle length (MM) 90 days Salesforce field audit
Pipeline velocity 35% per month CRM reporting
% of quota from self-sourcing 35% Activity tracking
% of quota from marketing-sourced 50% Lead source report
% of quota from channel/partnerships 15% Partner tracking
Win rate vs competition 35% Competitor intel
Pipeline available per AE (coverage) $3.2M CRM stage analysis
Check: Does the math connect?
SMB AE capacity test:
- Pipeline available: $3.2M (from CRM)
- Historical win rate: 38%
- Expected closure: $3.2M × 38% = $1.216M
- Assigned quota: $850K
- Implicit assumption: rep is only using 70% of available pipeline
Question: Is the other 30% low-quality, stale, or delayed-close?
Action: Audit pipeline health; improve pipeline generation if quality is good
Step 4: Calculate Segment-Specific Growth Assumptions
For each segment, determine what "nothing changes" looks like, then model growth independently.
New Business Segment
Prior-year closed new-business bookings: $3.3M
Current-year pipeline for new business: $4.8M (1.45x coverage)
Capacity-based forecast:
AE headcount available for new biz: 6.5 FTE (effective)
Quota per AE: $850K (blended SMB + MM)
Base capacity: $5.525M
Pipeline constraint (only $4.8M pipeline): $4.8M
Haircut for slippage (36% slip rate): $4.8M × 64% = $3.072M
Scenario analysis:
Base (no pipeline generation investment): $3.1M
+Scenario A (ABM spend +$100K invested): +$250K pipeline → $3.25M
+Scenario B (new AE hire): +$680K capacity → $3.65M if pipeline exists
Expansion Segment
Current expansion ARR: $1.5M
Historical gross retention rate (GRR): 92%
Historical net expansion rate: 12% (upsell + cross-sell net of downgrade)
Bottoms-up forecast:
Renewal base (92% of $1.5M): $1.38M
Expansion growth (12% of $1.5M): +$0.18M
New expansion from new-customer base: +$0.05M (only 3-4 new customers ready to expand)
Total expansion forecast: $1.61M
Variance analysis:
If retention drops to 88% (2-year churn acceleration): $1.32M (miss of $0.29M)
If new-customer base expands faster (10 vs 4 ready): $1.71M (beat of $0.1M)
Renewal Segment
Current renewal ARR: $0.9M
Historical gross retention (GRR): 97%
Known renewals at risk: $80K (customer feedback indicates low NRR)
Contraction from existing (downsells): -$20K (expected downgrades)
Bottoms-up forecast:
Base at-risk ($0.9M - $0.08M) × 97%: $0.795M
At-risk book ($0.08M with intervention): $0.06M (75% save rate expected)
Contraction risk (-$0.02M): -$0.02M
Total renewal forecast: $0.835M
Confidence level: HIGH (renewal base is most predictable)
Step 5: Consolidate Segment Forecasts into Bottoms-Up Plan
Create a summary table with segment forecasts, assumptions, and confidence levels:
Segment Forecast Assumptions Confidence Owner
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New Business - SMB $1.5M AE capacity, pipeline MEDIUM VP Sales
New Business - MM $1.65M AE capacity, pipeline MEDIUM VP Sales
Expansion $1.61M GRR 92%, expansion 12% HIGH VP CS
Renewal $0.835M GRR 97%, save rate 75% HIGH VP CS
Professional Services $0.35M Implementation capacity MEDIUM VP Services
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BOTTOMS-UP TOTAL $6.035M
Narrative commentary:
"Our bottoms-up plan of $6.035M assumes our sales team produces at historical productivity levels, existing customer base retains and expands as historically expected, and pipeline is generated at current rates. Key risks: New Business pipeline ($4.8M) is below 2-year average ($5.2M), suggesting pipeline-generation investment is not currently sufficient. Expansion assumes no change in customer health; if CS team delivers on success initiatives, upside exists."
Step 6: Compare Bottoms-Up Against Capacity Model
Reconcile the two approaches:
Capacity Model Estimate: $4.1M
Bottoms-Up Segment Sum: $6.035M
Variance: +$1.935M (bottoms-up is higher)
Analysis:
- Capacity model assumes only new-business forecasting
- Expansion + Renewal segments not captured in AE-quota model (separate CS metrics)
- Bottoms-up correctly separates revenue types
Interpretation:
- Capacity model baseline (AE productivity): $4.1M in new bookings
- Expansion from retention: +$1.61M
- Renewal from existing: +$0.835M
- Total: $6.545M (theoretical if all segments hit)
Current bottoms-up ($6.035M) is conservative relative to capacity model
because pipeline-generation is a bottleneck in new business.
Red flag: If bottoms-up is significantly lower than capacity suggests, investigate:
- Is pipeline generation weak? (pipeline available per rep is below historical)
- Is deal velocity slowing? (sales cycle lengthened, win rate dropped)
- Is the team actually underperforming? (quota attainment is below 70%)
Step 7: Document Assumptions in Shared Assumption Template
Transfer all key assumptions to a shared spreadsheet so Finance can validate and challenge. See planning-assumptions-template.md for the format.
Example:
Assumption: New Business Win Rate 38%
Owner: VP Sales
Data Source: CRO School case analysis (Pavilion, 2025; $65K ACV, 8 customers won, 21 opportunities in pipeline)
Historical data: Last 12 months: 42%, Last 24 months: 40%, 3-year avg: 39%
Adjustment for 2026: -1% (one major competitor entering market)
Confidence: MEDIUM (competitive risk introduced)
Linked to: New Business capacity and pipeline coverage models
Appendix: Pavilion Capacity Model (from CRO School Class 4)
For a worked example, the model structure is:
Inputs:
- AE headcount by tier (Mid-Market vs Enterprise)
- Monthly quota per tier
- Start dates for each rep (hire dates)
- Ramp period in months
- Quota achievement rate (e.g. 78% = expectation that reps will achieve 78% of quota)
Outputs:
- Monthly quota per rep (adjusted for ramp)
- Monthly quota by team (sum of reps)
- Period quota (3-month, 6-month, annual)
Formula (per Pavilion):
Monthly Quota for Rep =
IF(ramp_month_passed, full_monthly_quota,
full_monthly_quota * (days_into_ramp_month / total_days_in_month))
This allows fractional ramp when a hire date falls in the middle of a month.
Example (from Pavilion worksheet):
Hire date: 1 October Ramp period: 3 months Full ramp date: 1 January Monthly quota: $50K
- October 1-31: Ramp in progress. Days into month = 31/31 = 100%. But ramp month = 1. Prorated: $50K × (31/31) = $50K (or 0%, depending on ramp model)
- November: Full month in ramp. Ramp month = 2. Partial output: $50K × 33% = $16.67K
- December: Full month in ramp. Ramp month = 3. Partial output: $50K × 67% = $33.33K
- January onwards: Ramped. Full quota: $50K/month
Total in ramp year: Jan-Sep = 9 × $50K + Oct-Dec = $150K = $600K annual Annual contribution of this hire in first year = $600K (9 full months at quota + fractional ramp months)
When to use this model:
- Forecasting new-hire contribution to bookings
- Calculating team-wide capacity with turnover/hiring
- Adjusting annual targets for mid-year hiring decisions
- Modeling what-if scenarios (e.g. hire 3 AEs in Q2 vs Q1)