How to Build a Bottom-Up Revenue Model

A bottom-up revenue model builds the revenue plan from the capacity and activity that produce it, such as the number of salespeople and what each can close, or the marketing spend and what it converts to, and adds them up. It answers the question investors and boards ask first: what has to be true for this number to happen? This guide shows how to build a bottom-up revenue model for a growing business, with a sales-capacity model with ramp times, a marketing-led funnel, an account-based view for larger customers, a combined worked example, reconciliation with a top-down check and a list of the assumptions reviewers challenge. It is part of budgeting and forecasting and a companion to top-down vs. bottom-up revenue forecasting.

What bottom-up means

A top-down forecast starts with a market size and a share. A bottom-up forecast starts with your own capacity and conversion:

Use bottom-up to plan, and top-down to test whether the result is plausible. See top-down vs. bottom-up revenue forecasting.

Choose the engines of growth

Most companies have one to three engines. Model each separately.

Engine 1: Sales capacity model

The logic is: revenue capacity equals productive reps times productivity per rep. New reps are not productive at once, so include a ramp.

Assumptions (hypothetical)

• A fully ramped rep closes new annual contract value (ACV) of $30,000 per month at 100 percent of target.
• Average attainment is 85 percent of target.
• Ramp: month 1 of tenure 0 percent, month 2 25 percent, month 3 50 percent, month 4 75 percent, month 5 onward 100 percent.
• The company starts with 2 fully ramped reps and hires a third at the start of month 3.
• A fully loaded rep costs $9,000 per month.

Calculation

Productivity of a ramped rep = $30,000 × 85% = $25,500 per month.

Check the new rep's contribution: 25% × $25,500 = $6,375; 50% × $25,500 = $12,750; 75% × $25,500 = $19,125; sum = $38,250. Total = $306,000 + $38,250 = $344,250.

The new rep costs $9,000 × 4 months (months 3 to 6) = $36,000 and produces $38,250 of ACV within the period, but the ACV is annual contract value, not revenue or margin, and it takes until month 5 for the rep to reach full productivity. This is why hiring plans must be tied to the revenue timeline, and why a hiring freeze in a downturn improves cash in the short run and hurts bookings six months later. Include recruiting time, too: if it takes two months to find a rep, the rep starts later than the requisition.

Engine 2: Marketing-led funnel

The logic: spend, divided by cost per customer, gives customers; customers times revenue each gives bookings.

Assumptions (hypothetical): marketing spend of $20,000 per month, customer acquisition cost (CAC) of $500, average contract value of $1,200 per year.

• New customers per month = $20,000 / $500 = 40
• New ACV per month = 40 × $1,200 = $48,000

If CAC rises to $650 as the cheapest channels saturate, customers fall to 20,000 / 650 = 30.8 and ACV to $36,923, a decline of 23 percent for the same budget. Always model CAC as rising with spend unless you have evidence otherwise.

Engine 3: Accounts and expansion

For the installed base: accounts × expansion rate × expansion size, less churn. For example, 400 accounts, 1.5 percent expand each month by an average of $800, and 1 percent churn at an average of $1,100: expansion = 400 × 0.015 × $800 = $4,800; churn = 400 × 0.01 × $1,100 = $4,400; net effect = +$400 per month. A small net figure that hides large gross movements, and a reminder to forecast both. See SaaS revenue forecasting for recurring revenue mechanics.

Combine the engines

Add the engines for new bookings, then convert bookings to revenue.

Convert to revenue by the date a contract starts and the recognition policy. For annual contracts billed monthly, the revenue per month is ACV / 12 starting at the contract date. Cash depends on billing terms. See cash flow management.

Build the model in a spreadsheet

1. Assumptions sheet, with every input labeled, sourced and dated.
2. One sheet per engine, with monthly columns.
3. Summary sheet, combining bookings, revenue, headcount cost and cash.
4. Checks sheet: total equals sum of parts, no negative headcount, revenue ties to bookings.
5. Scenarios: a switch cell that selects base, low or high assumptions. See scenario planning for finance teams.

Reconcile with a top-down check

If the model implies $4,000,000 of new ACV next year in a market where you estimate the addressable annual spend at $80,000,000, your implied share of new spend is 5 percent. Ask whether that is plausible given your current share, competitors and the number of qualified buyers you can reach. If the bottom-up result implies a share that your history cannot support, either the capacity assumptions are too generous or the market estimate is too small.

The assumptions reviewers challenge

Give each assumption a source (history, pilot, supplier quote or judgment) and an owner.

Engine 4: Channel partners

For a partner-led model, forecast the partners, not just the deals.

Check: 8 × 2.5 = 20; 20 × 0.40 = 8; 8 × $20,000 = $160,000. Partner programs often take two or three quarters to produce, so include a lag between recruitment and the first deals, and remember that partner margin or commission reduces net revenue. In this model the weakest assumption is the 50 percent activation rate; ask what it was for the last cohort of partners.

Add the cost side

A bottom-up revenue plan implies costs that should be in the budget at the same time. Using the sales capacity example: a commission of 10 percent on $344,250 of new ACV is $34,425; the new rep's cost over the period is $36,000; the marketing engine's spend is $20,000 a month, or $120,000 over six months. Together these are $190,425 of acquisition cost against $344,250 of sales-led ACV plus $288,000 of marketing-led ACV (6 × $48,000), a total of $632,250. Dividing the cost by the ACV gives about 30 cents of acquisition spend per dollar of new annual contract value. That ratio, tracked over time, tells you whether growth is getting cheaper or dearer. The simple figures omit management, tools and onboarding costs, which a full model would add.

Sensitivity to the big assumptions

Note on the hire timing: a rep starting at month 5 is at 0 percent in month 5 and 25 percent in month 6, contributing $6,375 in the period instead of $38,250, a loss of $31,875. Attainment check: at 75 percent, a ramped rep produces $22,500 a month; two reps over six months = $270,000, plus the new rep at 75/85 of $38,250 = $33,750, for $303,750. Run these tests in the model and see sensitivity analysis in financial models. When bookings have a strong seasonal pattern, apply it to the capacity engines too; see adjusting forecasts for seasonality.

Measuring the model

Compare bookings and revenue with the plan monthly, break variances into volume (capacity and conversion) and price (deal size), and update the assumptions that missed. Use accuracy measures from how to measure financial forecast accuracy. A model that is never compared with actuals will not improve.

Link to profitability

A bottom-up revenue model should flow into costs: commission, hiring, marketing, onboarding and support. Revenue growth that requires unprofitable acquisition is not an improvement. See unit economics for contribution and payback analysis.

Common mistakes

• Treating new hires as productive immediately.
• Assuming CAC stays constant as spend rises.
• Using quota as capacity without applying attainment.
• Mixing bookings, revenue and cash.
• No view of churn and expansion.
• Ignoring recruiting lead time.
• Building a model so detailed that nobody can maintain it.
• No top-down check.

FAQs

What is a bottom-up revenue model?

A revenue forecast built from operational drivers such as sales capacity, marketing conversion and customer accounts, then added up.

How do I model sales rep ramp?

Assign a productivity percentage to each month of a new rep's tenure, rising to 100 percent, and apply it to a ramped rep's output.

What is the difference between bookings and revenue?

Bookings are contracts signed; revenue is recognized as the service is delivered, according to accounting rules.

How do I check a bottom-up model?

Compare it with a top-down market view and test the key assumptions against history.

What do investors look at first?

Typically the capacity, conversion and retention assumptions and how well they match your history.