
When to Use Top-Down vs Bottom-Up Forecasting in a Startup Financial Model
Learn when to use market sizing, top-down scenarios, and bottom-up event-driven forecasting in a startup financial model.
Practical guides for early-stage founders building SaaS and subscription products.
Pillar guide
A practical guide to building a connected startup financial model — and using it to make better decisions across pricing, acquisition, costs, runway, and fundraising.

Learn when to use market sizing, top-down scenarios, and bottom-up event-driven forecasting in a startup financial model.

Use forecasted unit economics to stress-test CAC, churn, payback, plan mix, channels, and contribution before growth spend scales.

Read startup Cash Flow as a survival and timing view: collections, outflows, financing, ending cash, and month-by-month runway risk.

Read startup P&L in layers — revenue, COGS, gross profit, operating expenses, and EBITDA — and know what this operating view explains best.

Use a detailed step-by-step forecast layer to trace how assumptions create subscribers, revenue, costs, and burn behind high-level finance views.

Use P&L, Cash Flow, Unit Economics, and a detailed monthly forecast together to interpret one connected startup model and make clearer operating decisions.

Plan financing from cash timing and milestones: founder funding, staged rounds, minimum vs suggested raise, buffer, and the funding gap on top of a solid operating forecast.

Model hiring as role-by-role timing decisions so payroll, burn, runway, and fundraising need stay aligned to milestones.

Stage recurring overhead and one-time setup work separately so burn, runway, and fundraising needs reflect the company you have now.

Payment processing, per-user serving, trials and free usage, and usage-based APIs close to margin — payroll, overhead, and acquisition elsewhere.

COGS, SG&A, Team, and one-time costs — staged by milestone — so margin, burn, and unit economics stay readable before fundraising.

Model generative AI under COGS: cost per action, caps by plan, explicit trial and free usage, then read COGS, margin, cash, and unit economics.

Separate paid channels with budget, start and end months, CPC or CPM buying, and funnel conversion — then read subscribers, CAC, and burn before you commit spend.

Split partners into real signup-based sources with growth, caps, payouts, and end dates — so subscribers and CAC stay tied to how you actually sell.

Split non-paid traffic into real sources—compounding, steady, and finite—with visits, caps, conversions, and end dates you can still believe in later.

Split paid, organic, partners, and referral into channel inputs—then trace trials, subscribers, CAC, and revenue.

Model trial vs freemium paths side by side: funnel shape, subscriber timing, and when revenue becomes visible.

Plan mix, billing cadence, and churn assumptions—modeled before launch so revenue, cash, and LTV stay coherent.