Sales forecast for a new business: assumptions to evidence

A sales forecast for new business starts with customers, conversion, price and capacity assumptions because there is no reliable sales history to extend. Build it month by month, show a range around uncertain inputs, and replace those inputs with evidence from completed sales.

1. Build an assumptions sheet from the evidence you have

Gather your lead list, quotes, pilot orders, price list and staffing schedule. Give each lead a unique ID, source, qualification date, expected decision date and eventual outcome. Keep a separate delivery record so an accepted order does not automatically become this month's sales.

The SBA's market research guidance identifies demand, location, competition and pricing as questions to investigate. Interviews and early quotes help test those questions, but interest is weaker evidence than a completed purchase.

Write an assumption owner, evidence date and reason beside every forecast input. A lead assumption could come from a planned campaign and a trial response rate. A delivery limit could come from scheduled staff hours. Label estimates honestly; a new business does not have an established conversion rate merely because a planning worksheet contains one.

Use the sales projection guide once recurring revenue and observed win rates become available. The method here deliberately begins before that history exists.

2. Turn the inputs into monthly sales

For a simple project business, use these relationships:

Expected orders = Qualified leads × Conversion assumption

Delivered projects = Smaller of expected orders and delivery slots

Forecast sales = Delivered projects × Net price per project

This simplified launch example assumes leads decide and projects are completed in the same month. All projects have the same price, and there are no repeat purchases, credits or opening orders. If those conditions do not hold, schedule lead cohorts and deliveries separately before calculating sales.

An illustrative US installation business forecasts the following quarter. These are planning assumptions, not industry benchmarks.

Put those columns in A:H, with January in row 2. In F2, calculate expected orders:

=B2*C2

In G2, limit deliveries to capacity:

=MIN(F2,D2)

In H2, calculate sales, then fill F2:H2 down through row 4:

=G2*E2

In H5, total the months using Excel's SUM function:

=SUM(H2:H4)

Expected orders can be fractional in a larger planning sheet; retain that precision for an expected-value forecast and round only the displayed result. For an operational appointment plan, schedule whole projects separately.

The check is 45 delivered projects × $500 = $22,500, matching the sum of monthly sales. Expected demand is 54 orders, so the forecast assumes the remaining demand is lost rather than carried forward. If customers will wait, add an opening and closing backlog schedule instead of discarding it.

3. Test a range without hiding the capacity limit

Change only February's conversion assumption. Keep its 100 leads, 15 delivery slots and $500 price unchanged.

The high case produces more demand but no extra sales because delivery is already full. This tells management what to test next: the value and cost of additional capacity, rather than assuming marketing growth automatically becomes revenue. A conservative sales forecast documents a wider downside case when several risks need review.

The SBA's business plan guide recommends clearly explained projections with quarterly or monthly detail for the first year. A short assumptions register makes that detail reviewable without pretending the estimate is certain.

4. Replace assumptions with observed results

Suppose February finishes with these actual results. All leads have reached an outcome by the review date, and all accepted projects were completed.

Observed conversion is 14 / 100 = 14%; sales are 14 × $500 = $7,000.

The sales variance is $7,000 − $7,500 = −$500. Record that difference against the frozen forecast. Investigate whether the lower conversion reflects the channel, offer or qualification standard before carrying 14% into every future month.

At the sales forecast meeting, distinguish new evidence from management changes. Preserve the previous assumptions, record the revised rate and date, and assign the next evidence check. Keep the new business cash flow forecast separate so credit terms do not disappear inside sales figures.

Where it goes wrong

• Visitors counted as qualified leads. Use one documented qualification standard and remove duplicate contacts.
• Unfinished cohorts. Recent leads still awaiting a decision make conversion look weaker than it is.
• Orders treated as delivered sales. Apply the actual service schedule and appropriate revenue timing.
• Capacity ignored. Expected demand above staffed delivery slots requires a backlog or lost-demand assumption.
• Forecasts overwritten. Replacing the original figures prevents a fair comparison with actual results.

Compare launch assumptions with your own results in Covirage

Bring your monthly assumptions sheet, lead outcomes and sales export to Covirage. Covirage maps the columns, and its tools compute and check the supplied scenarios and actual results; the external AI model explains the differences with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data.

See forecast analysis for the questions this comparison helps finance teams answer.

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