Merchandise Revenue & Calc
Build monthly retail sales from daily visits, days open, buyer conversion, lines per purchase, five category shares, and their realized selling prices.
The Quilt Shop Financial Model is an Excel planning template for a 1,500-square-foot leased retail quilt shop. It forecasts 2026–2030 merchandise sales from foot traffic, purchase conversion, shopping-basket lines, category mix, and net selling prices, then links expenses and staffing to EBITDA.
The illustrative business is a six-day-per-week neighborhood store in suburban Columbus, Ohio, selling quilting fabrics, precuts, kits, batting, notions, and printed patterns. It does not model classes, longarm quilting, sewing-machine sales, wholesale, subscriptions, or ecommerce delivery.
The workbook connects shop-level sales assumptions with operating expenses, staffing, startup investment, financial statements, and decision reports.
Build monthly retail sales from daily visits, days open, buyer conversion, lines per purchase, five category shares, and their realized selling prices.
Plan merchandise purchasing, freight, cutting losses, card fees, recurring occupancy expenses, and store manager and associate FTE in separate operating schedules.
Use CAPEX, CapTable, Dashboard working-capital controls, and Sources & Uses to review equipment, owner contributions, inventory timing, and funding allocation.
Review the Income Statement, Cash Flow, Balance Sheet, Dashboard, Summary, and financial charts for different views of projected store performance.
Compare Low, Base, and High assumptions; examine break-even and payback mechanics; and use input and reconciliation checks before relying on a scenario.
Store visits determine potential transactions; purchase conversion and basket lines determine category quantities, which are multiplied by net selling prices.
Each forecast month uses 26 open days and 60% purchase conversion. The model multiplies store visits by these inputs and 1.6 merchandise lines per purchase, then assigns every line to one retail category; a kit and its components are not counted twice.
The case assumes 30 daily visits in 2026, rising to 48 in 2030. The merchandise line mix is 40% fabric cuts, 20% precut bundles, 10% quilt kits, 10% batting packs, and 20% notions and patterns.
The Revenue Forecast presents store visits, conversion, lines per purchase, category allocation, and selling prices as the sales drivers. Its monthly and annual calculations help test the effect of different foot-traffic assumptions or merchandise mix on revenue.
30 visits/day × 26 days × 60% conversion × 1.6 lines × $46.30 weighted net line price ≈ $34,669 monthly revenue.
The $46.30 weighted selling price combines $52 fabric cuts, $45 precuts, $95 kits, $38 batting packs, and $16 notions or patterns using their stated shares. Twelve full operating months produce approximately $416,033 in 2026 revenue, excluding sales tax.
Merchandise purchasing, sales-related charges, recurring overhead, and base salaries are modeled separately and counted once in operating expenses.
Direct COGS is 53% of sales: 50% wholesale merchandise, 2% inbound freight, and 1% shrink and cutting loss. Variable expenses add 2.9% processing, 0.4% packaging consumables, and 1% incremental sales campaigns, totaling 4.3% of revenue.
The COGS and Operating Expenses report separates direct merchandise costs, variable selling costs, and fixed monthly overhead. Adjusting purchases, freight, shrinkage, or store occupancy assumptions shows how cost pressure changes margins and EBITDA.
Fixed operating expenses include rent and occupancy, utilities, insurance, POS connectivity, local marketing, professional services, maintenance, cleaning, and renewals. The illustrative lease is $2,800 monthly, while combined recurring fixed expenses are $55,920 annually throughout the forecast.
The Payroll Forecast plans a working manager at $50,000 annual base pay and retail/cutting associates at $36,000 per annual-average FTE. Associate coverage rises from 1.0 FTE in 2026 to 1.5 FTE in 2030, raising total annual base payroll from $86,000 to $104,000.
The setup plan distinguishes physical shop assets, separate December 2025 preopening payments, inventory funding, and owner equity from operating EBITDA.
Startup assets total $40,500: $15,000 for racks and displays, $18,000 for leasehold lighting and fitout, $5,000 for cutting counters and durable tools, and $2,500 for POS hardware and office equipment. These are opening assets, not recurring annual merchandise or payroll expenses.
The Capital Expenditure Plan records store fixture, fitout, cutting-equipment, and POS purchases by amount and date. Its depreciation and asset schedules distinguish these investments from the recurring costs used to calculate operating EBITDA.
Separate preopening cash covers a refundable lease deposit, permits and professional setup, launch advertising, December 2025 occupancy, and preopening training. The example sets receivables at 0 days, supplier payables at 15 days, and inventory at 120 days.
The Sources and Uses of Funds report organizes planned funding and cash allocation across operations, investment, and financing. The example provides $213,908 initial owner funding for qualifying assets, preopening cash, opening inventory net of supplier credit, and a three-month recurring operating reserve; no committed outside financing is assumed.
In the selected illustrative case, annual merchandise revenue rises with store traffic while planned staffing and merchandise costs determine EBITDA.
| Year | Revenue | Operating Expenses | EBITDA |
|---|---|---|---|
| 2026 | $416,033 | $380,307 | $35,726 |
| 2027 | $485,372 | $423,638 | $61,734 |
| 2028 | $554,711 | $468,769 | $85,942 |
| 2029 | $610,182 | $505,954 | $104,228 |
| 2030 | $665,653 | $541,339 | $124,314 |
Planning example, not observed store results; values are rounded to the nearest dollar.
The 2026 projection combines $416,033 revenue with $380,307 operating expenses for $35,726 EBITDA. In 2030, illustrative revenue reaches $665,653 and EBITDA reaches $124,314; this change follows the selected traffic, product pricing, cost rates, and staffing assumptions.
EBITDA is after direct merchandise costs, variable selling expenses, fixed overhead, and base payroll, but before depreciation, interest, and tax. The standard Income Statement, Cash Flow, and Balance Sheet support broader analysis; these case figures do not establish net profit or ending cash.
The Cash Flow Forecast shows monthly operating, investing, and financing cash movements and reconciles opening to closing cash. Inventory held for 120 days, opening fitout costs, and owner contributions can affect liquidity differently from the positive EBITDA in the table.
The workbook evaluates operating sales break-even, cash break-even, investment payback, and annual ROIC as separate questions rather than using EBITDA as a substitute.
Sales break-even tests the sales needed to cover the modeled cost structure; cash break-even reflects cash movement. Investment payback assesses recovery of invested funds, while annual return on invested capital considers operating returns relative to capital employed.
The Break-Even, Payback and ROIC analysis presents operating sales thresholds, project and cumulative free cash flow, invested capital, and annual ROIC. Use it to judge the economics of store expansion or launch assumptions without treating positive EBITDA as proof that the initial investment is recovered.
Dashboard Scenario Controls compare Low, Base, and High multipliers for sales, direct costs, variable expenses, fixed expenses, and payroll. Optional debt controls support financing schedules, but this example assumes no committed non-owner funding.
This financial model suits a merchandise-only neighborhood quilt shop evaluating sales volume, assortment economics, staffing, rent, and opening inventory needs.
Owners and planners can change daily visits, buying conversion, average basket lines, five category shares, net line prices, direct-cost rates, fixed monthly expenses, role-based staffing FTE, and opening capital requirements. The worksheet checks help identify inconsistent or missing assumptions.
If the shop offers classes, longarm services, machine dealership activity, wholesale, subscriptions, or ecommerce delivery, its revenue logic must be expanded beyond this retail-only case. Benchmarks and valuation reports can support further analysis using independently chosen comparison and discount assumptions.
These answers clarify what the workbook forecasts, which inputs are editable, and which results are not established by the illustration.
Yes. The example is a leased 1,500-square-foot retail quilt shop with five merchandise categories and a monthly 2026–2030 forecast.
The model uses daily visits, open days, purchase conversion, and purchased lines, then assigns every line to one category and applies its net selling price.
Yes. The forecast uses editable visits, conversion, product mix, net prices, cost rates, overhead assumptions, and annual-average staffing FTE.
Yes. The standard workbook includes Cash Flow and Balance Sheet reports, but the supplied illustrated operating results end at EBITDA.
No. Startup assets and separate preopening payments are distinguished from recurring COGS, variable expenses, fixed overhead, and payroll.
No committed non-owner financing is included. The Dashboard offers debt controls for modeling optional facilities and repayment schedules.
No. Inventory, capital spending, payment timing, and financing affect cash. The Returns report evaluates payback and annual ROIC separately.
KPIs, forecasts, and cash flow at a glance.
Key assumptions and calculations driving revenue forecasts.
Funding sources, spending, and closing cash.
Cash break-even, payback, and ROIC.
DCF valuation and sensitivity analysis.
Largest costs and spending trends.
Annual and monthly financial performance.
Compare margins and returns to benchmarks.
The low, base, and high cases were laid out cleanly, so I stopped bouncing between versions and built my forecast in one pass. It saved me about 4 hours on planning and made the assumptions easier to share.
I was worried one bad formula would throw off the whole model, but the structure kept everything tidy and easy to check. I caught issues faster and avoided a full rebuild before my lender call.
The model made margins and break-even easy to see without digging through rows for an hour. That clarity helped me tighten pricing and walk into my meeting with a clearer plan.