How to read this
Cells are referenced by R<row>/<column><row> notation. R9/E9 means column E, row 9. R38–R45 is a block of inputs spanning those rows. Multi-column ranges like D39–J39 mean the same row across several columns. Types: INPUT = user-edited, FORMULA = calculated, DROPDOWN = select from list.
Ecommerce Forecasting Tool — Sheet Map
Sheets (9)
README, License, Disclaimer, Get Started, Key Reports, Forecast, Historicals, Model Comparison, Changelog
Get Started (B1:F49)
Setup (R5-R14)
| Row |
Label |
Type |
Default |
| R6/D6 |
Company Name |
INPUT |
"Company" |
| R7/D7 |
Currency |
INPUT |
"$" |
| R8/D8 |
First forecast date |
INPUT (date) |
Jan 2025 |
| R9/D9 |
Fiscal year end |
INPUT (date) |
Dec 2025 |
| R12/D12 |
First historical date |
INPUT (date) |
Jan 2021 |
| R13/D13 |
Historical FY end |
INPUT (date) |
Dec 2021 |
| R14/D14 |
Last historical date |
INPUT (date) |
Dec 2024 |
Revenue & Marketing (R16-R34)
| Row |
Label |
Type |
Default |
| R17/D17 |
Avg Revenue per Order, new |
INPUT ($) |
$50 |
| R18/D18 |
Avg Revenue per Order, repeat |
INPUT ($) |
$40 |
| R19/D19 |
Baseline rate of change AOV |
INPUT (%) |
10% |
| R20/D20 |
Rate decline per month |
INPUT (%) |
-5% |
| R22/D22 |
Cost of Sales % |
INPUT (%) |
25% |
| R23/D23 |
Additional COGS % |
INPUT (%) |
10% |
| R24/D24 |
Additional COGS % (2nd) |
INPUT (%) |
0% |
| R28/D28 |
Shipping Revenue per order |
INPUT ($) |
$0 |
| R29/D29 |
Shipping Cost per order |
INPUT ($) |
$0 |
| R31/D31 |
CAC new customer |
INPUT ($) |
$30 |
| R32/D32 |
CAC repeat customer |
INPUT ($) |
$10 |
Growth & Churn (R36-R48)
| Row |
Label |
Type |
Default |
| R37/D37 |
Date to start growth |
INPUT (date) |
Jan 2025 |
| R38/D38 |
New Customers first month |
INPUT (#) |
550 |
| R39/D39 |
Baseline growth rate |
INPUT (%) |
90% |
| R40/D40 |
Growth rate decline per month |
INPUT (%) |
-15% |
| R41/D41 |
Conversion rate (sessions→orders) |
INPUT (%) |
2% |
| R42/D42 |
Customers beginning |
INPUT (#) |
0 |
| R43/D43 |
Churn rate per period |
INPUT (%) |
50% |
| R44/D44 |
Repeat cycle months |
INPUT (#) |
3 |
| R47/D47 |
After N total customers adjust |
INPUT (#) |
0 |
| R48/D48 |
Change cohort performance by |
INPUT (#) |
1 |
Forecast (B1:BO199) — Cohort-based
Retention Curve (R44):
- Calculated from churn rate and repeat cycle
- Can be overwritten with manual retention curve
- R46: Adjustment factor applied to all cohorts
Orders (R50-R100+):
- R51: Website Traffic (FORMULA from orders ÷ conversion)
- R52: New Customers per period (FORMULA)
- R54: Total Orders (FORMULA: sum of all cohorts)
- R55-R100+: Individual monthly cohorts — each row is a cohort, columns track orders per period (FORMULA based on retention curve)
Revenue (R103+):
- Orders × AOV per cohort
- Separated into new vs repeat revenue
- COGS, shipping, marketing spend calculated
Unit Economics (R150+):
- CAC, LTV, payback period
- Contribution margin
- Monthly cohort data for historical performance
- Users enter actual order counts per cohort
- Model blends historical retention with forecast assumptions
Key difference
Cohort-based, not subscription. Each monthly cohort tracked separately. Retention = repeat purchase probability, not subscription churn.