5-tab financial model

Don't over-engineer. The model investors actually read has five tabs, change one driver and watch the cash line move, and three scenarios you can defend.

The skeleton

TAB 1 · DRIVERS  (every assumption editable here)
Pricing
  - ASP (avg selling price) per customer  / month: $___
  - Annual price increase %: ___
GTM
  - CAC blended: $___
  - Payback period: ___ months
  - Sales cycle (days): ___
  - Conversion: lead → trial → paid: ___% / ___%
Retention
  - Gross monthly churn: ___%
  - Net dollar retention: ___%
Headcount
  - Engineers: q1 ___ → q4 ___
  - GTM: q1 ___ → q4 ___
  - Ops: q1 ___ → q4 ___
  - Average loaded cost per FTE / region: $___
Cost
  - Hosting / infra (% of revenue): ___%
  - Tools / SaaS (per FTE / month): $___
  - Office / travel (per month): $___

TAB 2 · REVENUE  (built bottom-up from Drivers)
                       Jan  Feb  Mar  Apr  May  Jun  ...
New customers          ___  ___  ___  ___  ___  ___
Churned customers      ___  ___  ___  ___  ___  ___
Net new customers      ___  ___  ___  ___  ___  ___
Total customers (EOM)  ___  ___  ___  ___  ___  ___
Avg revenue / customer ___  ___  ___  ___  ___  ___
MRR                    ___  ___  ___  ___  ___  ___
ARR                    ___  ___  ___  ___  ___  ___
NDR                    ___  ___  ___  ___  ___  ___

TAB 3 · COSTS  (headcount-led)
Headcount build
  Eng / GTM / Ops by month, totalled

Salary cost (loaded — salary + benefits + tax)
  Per category, per month

Variable costs
  - Hosting (= Drivers.hosting% × Revenue)
  - Tools/SaaS (= Drivers.tools/FTE × FTE count)
  - Travel/office (= Drivers monthly)

GTM spend
  - Paid acquisition (CAC × new customers)
  - Sales tooling
  - Events / content

TAB 4 · P&L  +  CASH FLOW
                       Jan  Feb  Mar  Apr  May  Jun  ...
Revenue                ___  ___  ___  ___  ___  ___
COGS                   ___  ___  ___  ___  ___  ___
Gross margin           ___  ___  ___  ___  ___  ___
Gross margin %         ___% ___% ___% ___% ___% ___%
Salary cost            ___  ___  ___  ___  ___  ___
GTM spend              ___  ___  ___  ___  ___  ___
Other opex             ___  ___  ___  ___  ___  ___
Operating loss / gain  ___  ___  ___  ___  ___  ___
Net cash burn          ___  ___  ___  ___  ___  ___
Opening cash           ___  ___  ___  ___  ___  ___
Closing cash           ___  ___  ___  ___  ___  ___
Runway (months)        ___  ___  ___  ___  ___  ___

TAB 5 · SCENARIOS  (3 only)
Base case            — driver values from Tab 1
Downside (-30%)      — revenue lower, hiring delayed 3 months
Upside (+30%)        — faster sales cycle, lower CAC, faster hiring

For each: ARR EOY, runway, cash needed for Series A timing.

Common model mistakes

• Hard-coded assumptions buried in formulas. Refactor everything to point back to Tab 1.
• Top-down market sizing in the model. Tabs build bottom-up; market size is for the deck appendix only.
• 14 scenarios. Three scenarios you defend beat 14 scenarios that look impressive.
• Stale dates. Last-modified date matters. Investors see a model from 6 weeks ago and trust drops 30%.

Related skeletons