Strategy & Expansion
New Store Financial Projection Generator
Builds automated financial projections for potential new locations using historical performance patterns from your best analog stores — grounded in real data.
What it does
- Builds revenue projections using historical analog store performance
- Calculates Year 1 through Year 5 P&L by location
- Models sales ramp curve based on comparable new openings
- Calculates payback period and IRR for each candidate site
- Factors in cannibalization impact on nearby existing stores
- Runs sensitivity analysis on key revenue and cost assumptions
- Generates investment committee memo with full financial model
- Tracks forecast accuracy vs. actual post-opening performance
What it takes
- Analog Store Performance Data
- Market Demographic Data
- Site-Level Cost Estimates
- Lease Term Sheet / LOI
- Portfolio Financial Model
What it returns
- Excel Model
- PDF Report
- Investment Memo
- JSON Data
Written into the systems your team already runs, not into a second system of record.
How teams run it
Base Case Financial Model
Generate Year 1–5 P&L projections using top analog stores as benchmarks.
Payback Period & IRR
Calculate investment return metrics for site approval decisions.
Sensitivity & Scenario Analysis
Model bull, base, and bear case projections with key variable sensitivity.
Cannibalization-Adjusted Model
Adjust projections for sales transfer impact on nearby locations.
Cited, or flagged
Every value is anchored to the clause it came from. Where one is missing, Surfaice says so rather than inventing it.
Read where it lives
Documents are processed for the request and not retained afterwards. Nothing is copied into a second system of record.
Never trained on
Your documents do not train models — yours or anyone else's.
More in Strategy & Expansion
See it run on your own documents.
Fifteen minutes, your files, and the clause behind every answer.