Unit Economics & KPI Model

Unit Economics — Per Customer

Revenue per Customer (Monthly)

Component	Starter Customer	Professional Customer	Enterprise Customer
Cluster management fees	€1,700/mo (1 prod + 1 dev)	€4,600/mo (2 prod + stg + dev)	€13,000/mo (3 prod + 2 stg + 2 dev + 1 on-prem)
Support tier	€0 (Essential)	€800 (Business)	€2,500 (Enterprise)
Infrastructure margin (10%)	€10/mo	€45/mo	€150/mo
Total MRR	€1,710/mo	€5,445/mo	€15,650/mo
Annual Revenue	€20,520/yr	€65,340/yr	€187,800/yr

Cost to Serve per Customer (Monthly)

Cost Component	Starter	Professional	Enterprise
Engineer time (operations)	4 hrs/mo × €50/hr	8 hrs/mo × €50/hr	16 hrs/mo × €50/hr
Infrastructure (management share)	€15/mo	€25/mo	€50/mo
Monitoring overhead	€5/mo	€15/mo	€40/mo
Backup storage	€4/mo	€12/mo	€30/mo
On-call allocation	€20/mo	€50/mo	€150/mo
Support time	1 hr/mo × €50/hr	3 hrs/mo × €50/hr	8 hrs/mo × €50/hr
Total Cost to Serve	€294/mo	€502/mo	€1,070/mo

Gross Margin per Customer

Metric	Starter	Professional	Enterprise
MRR	€1,710	€5,445	€15,650
Cost to Serve	€294	€502	€1,070
Gross Profit	€1,416	€4,943	€14,580
Gross Margin	82.8%	90.8%	93.2%

Blended gross margin target: 85-90%

Unit Economics — Per Cluster

Revenue per Cluster

Cluster Type	Management Fee	Infra Margin	Total Revenue
Development	€500/mo	€4/mo	€504/mo
Staging	€500/mo	€4/mo	€504/mo
Production (Small)	€1,200/mo	€9/mo	€1,209/mo
Production (Standard)	€1,800/mo	€14/mo	€1,814/mo
Production (Large)	€2,500/mo	€23/mo	€2,523/mo
On-Prem / Air-Gap	€3,500/mo	€0	€3,500/mo

Cost per Cluster

Cost Component	Per Cluster/Month	Notes
Engineer time (steady state)	€100-200	~2-4 hours/month for routine ops
Monitoring agent overhead	€5-10	Prometheus scraping, log ingestion
Backup storage	€4-15	Depends on data volume
Management platform share	€5-10	Amortized management cluster cost
Total Cost per Cluster	€114-235

Cluster Margin

Cluster Type	Revenue	Cost	Margin	Margin %
Development	€504	€114	€390	77%
Production (Small)	€1,209	€160	€1,049	87%
Production (Standard)	€1,814	€185	€1,629	90%
Production (Large)	€2,523	€235	€2,288	91%
On-Prem / Air-Gap	€3,500	€300	€3,200	91%

Customer Acquisition Economics

Customer Acquisition Cost (CAC)

Component	Year 1	Year 2	Year 3
Sales personnel cost (allocated)	€4,000/deal	€3,500/deal	€3,000/deal
Marketing cost per lead	€200	€150	€120
Leads per deal (funnel)	20	15	12
Marketing cost per deal	€4,000	€2,250	€1,440
Pre-sales engineering time	€1,000/deal	€800/deal	€600/deal
Total CAC	€9,000	€6,550	€5,040

CAC Payback Period

Customer Type	ACV	CAC	Payback (months)
Starter	€20,520	€9,000	5.3
Professional	€65,340	€9,000	1.7
Enterprise	€187,800	€9,000	0.6
Blended average	€53,000	€9,000	2.0

Target: CAC payback < 6 months — achieved across all segments.

Customer Lifetime Value (LTV)

Assumption	Value
Average monthly churn	1.5%
Average customer lifetime	67 months (1 / 0.015)
Average MRR per customer	€4,500 (blended)
Gross margin	87%

LTV = MRR × Gross Margin × Customer Lifetime

LTV = €4,500 × 0.87 × 67 = €262,395

LTV:CAC = €262,395 / €9,000 = 29:1

Target: LTV:CAC > 3:1 — we are well above threshold.

Operational Efficiency Metrics

Engineer-to-Cluster Ratio

Phase	Engineers	Clusters	Ratio
Year 1	3	33	1:11
Year 2	6	102	1:17
Year 3	10	203	1:20

Target: 1:20 clusters per engineer (steady state)

This improves over time due to:

Better automation
Standardized cluster blueprints
Proven runbooks reducing incident time
GitOps reducing manual operations

Support Load per Engineer

Phase	Support Engineers	Customers	Ratio
Year 1	1 (shared with ops)	13	1:13
Year 2	2 (incl. CSM)	34	1:17
Year 3	3 (incl. CSM)	58	1:19

Target: < 1:20 customers per support person

KPI Dashboard — Operating Model

Revenue KPIs

KPI	Target	Red Flag	Measurement
Monthly Recurring Revenue (MRR)	Growing 8-12% MoM (Year 1)	< 5% MoM growth	Billing system
Annual Recurring Revenue (ARR)	Per financial model targets	> 20% below target	Billing system
Average Revenue Per Customer (ARPC)	> €4,000/mo	< €2,500/mo	MRR / # customers
Average Revenue Per Cluster	> €1,400/mo	< €800/mo	MRR / # clusters
Net Revenue Retention (NRR)	> 110%	< 100%	Year-over-year cohort
Expansion Revenue %	> 15% of MRR	< 5% of MRR	Upsell tracking

Customer KPIs

KPI	Target	Red Flag	Measurement
New customers per month	Per phase targets	< 50% of target	CRM
Monthly logo churn	< 2%	> 3%	# lost / # total
Monthly revenue churn	< 1.5%	> 3%	Lost MRR / Total MRR
Net Promoter Score (NPS)	> 50	< 30	Quarterly survey
Customer satisfaction (CSAT)	> 4.5/5	< 4.0/5	Post-ticket survey
Time to first value (onboarding)	< 2 weeks	> 4 weeks	Onboarding tracker

Operational KPIs

KPI	Target	Red Flag	Measurement
Platform uptime	> 99.9%	< 99.5%	Monitoring
P1 incidents per month	< 2 across platform	> 5	Incident tracking
Mean Time to Detect (MTTD)	< 5 minutes	> 15 minutes	PagerDuty
Mean Time to Acknowledge (MTTA)	< 10 minutes	> 30 minutes	PagerDuty
Mean Time to Resolve (MTTR)	P1: < 4h, P2: < 8h	P1: > 8h	Incident tracking
SLA compliance	> 99.5%	< 98%	Monthly report
Backup success rate	> 99.5%	< 98%	Velero monitoring
Clusters per engineer	> 15	< 10	Headcount / clusters
Deployment frequency (platform)	Weekly	< Monthly	ArgoCD
Change failure rate	< 5%	> 15%	Incident tracking

Financial KPIs

KPI	Target	Red Flag	Measurement
Gross margin (unit-level, per cluster/customer)	> 85%	< 70%	(Revenue - direct infra & ops cost per cluster) / Revenue
Company gross margin (incl. shared platform costs)	> 72%	< 65%	(Total Revenue - COGS incl. shared infra, platform, on-call) / Revenue
EBITDA margin	> 30% (Year 2+)	< 10%	P&L
CAC payback period	< 6 months	> 12 months	CAC / monthly GP
LTV:CAC ratio	> 10:1	< 3:1	LTV / CAC
Revenue per employee	> €150K/yr	< €80K/yr	ARR / headcount
Cash runway	> 6 months	< 3 months	Cash / monthly burn
Professional services margin	> 40%	< 20%	PS revenue - PS cost

Growth KPIs

KPI	Target	Red Flag	Measurement
Pipeline coverage	> 3x quarterly target	< 2x	CRM pipeline
Sales cycle length	< 6 weeks	> 12 weeks	CRM
Lead-to-close rate	> 5%	< 2%	CRM
Demo-to-close rate	> 25%	< 15%	CRM
Marketing qualified leads (MQLs)	Per phase targets	< 50% of target	Marketing tools

Profitability Model — Sensitivity Analysis

Base Case

Metric	Year 1	Year 2	Year 3
Customers	13	34	58
Clusters	33	102	203
ARR	€560K	€2.0M	€3.8M
Team	5	10	17
EBITDA	€149K	€1.04M	€2.16M
EBITDA Margin	27%	52%	57%

Bear Case (50% fewer new customers)

Metric	Year 1	Year 2	Year 3
Customers	7	18	30
Clusters	18	54	105
ARR	€300K	€1.1M	€2.0M
Team	4	7	12
EBITDA	€35K	€350K	€750K
EBITDA Margin	12%	32%	38%

Bear case is still profitable from Year 1 — the model works even at half the target growth.

Bull Case (50% more customers, higher ACV)

Metric	Year 1	Year 2	Year 3
Customers	20	52	90
Clusters	50	156	315
ARR	€840K	€3.1M	€5.9M
Team	6	14	22
EBITDA	€300K	€1.6M	€3.2M
EBITDA Margin	36%	52%	54%

Break-Even Analysis

Fixed Costs (Monthly)

Phase	Monthly Fixed Costs	Break-Even MRR	Break-Even Clusters
Phase 1 (3 people)	€22,000	€25,300 (at 87% GM)	~18 clusters
Phase 2 (5 people)	€36,000	€41,400	~30 clusters
Phase 3 (10 people)	€75,000	€86,200	~62 clusters
Phase 4 (17 people)	€133,000	€152,900	~109 clusters

Marginal Contribution per New Cluster

Cluster Type	Revenue	Marginal Cost	Contribution
Development	€500/mo	€114/mo	€386/mo
Production (Standard)	€1,800/mo	€185/mo	€1,615/mo
Production (Large)	€2,500/mo	€235/mo	€2,265/mo

Each new production cluster contributes €1,600-2,300/month in gross profit.

At Phase 1 fixed costs (€22K/mo), we need just 14 production clusters to break even.

Investment Return Model

Bootstrap Scenario (No External Funding)

Metric	Value
Initial investment (founders)	€100,000-150,000
Break-even	Month 5-6
Cumulative profit Month 12	€149,000
Cumulative profit Month 24	€1,192,000
Cumulative profit Month 36	€3,350,000
ROI (3-year)	2,100-3,350%

Seed Investment Scenario

Metric	Value
Seed investment	€500,000
Pre-money valuation	€2,000,000
Investor equity	20%
Break-even	Month 8-10 (higher salaries + marketing)
Year 3 ARR	€3.8M
Year 3 valuation (8x ARR)	€30.4M
Investor return	€6.1M on €500K = 12.2x

Key Model Assumptions That Must Hold

Assumption	Threshold	If Violated
Blended ACV > €40K	Below €25K — model stressed	Shift to larger customers only
Monthly churn < 2%	Above 3% — growth stalls	Invest in customer success, annual contracts
CAC < €10K	Above €15K — LTV:CAC breaks	Focus on inbound/referral, reduce outbound
Gross margin > 80%	Below 70% — hiring limits	Improve automation, raise prices
Engineer:cluster ratio > 1:15	Below 1:10 — labor costs eat margin	Invest in automation, standardize blueprints
Platform uptime > 99.5%	Below 99% — SLA credits + churn	Invest in reliability, add redundancy
Time to onboard < 4 weeks	Above 8 weeks — sales cycle lengthens	Improve automation, hire onboarding specialist

Model Summary

This business model works because:

High gross margins (85-93%) — software-like margins on a managed service
Low marginal cost — each new cluster adds minimal operational overhead
High switching costs — once integrated, customers rarely leave (K8s migration is painful)
Compounding revenue — MRR grows as customers add clusters
Bootstrap-friendly — profitable with just 14 production clusters
Strong unit economics — LTV:CAC of 29:1 leaves massive room for error
German market advantage — data sovereignty and trust create a defensible position
Open-source stack — zero software licensing costs