# How to Model Ecommerce using the Standard Financial Model How to configure the Standard Financial Model for ecommerce and DTC: specific cells, seasonality, inventory, and AI prompts that point where the edits go. ## How to model Ecommerce with the Standard Financial Model 1.2× ### Prebuilt for Ecommerce Businesses The [Standard Financial Model](https://www.hemrock.com/standard-financial-model) works for ecommerce out of the box. The [prebuilt revenue engine](https://www.hemrock.com/docs/revenues/) on `Revenues` handles acquisition, repeat-purchase [cohorts](https://www.hemrock.com/docs/cohort-modeling/), order volume, AOV, and cash. The `Forecast` sheet covers [cost of sales](https://www.hemrock.com/docs/forecast/), [inventory](https://www.hemrock.com/docs/inventory/), shipping, and fulfillment. The video above walks through the end-to-end structure. The rest of this page points at the specific cells you'll touch. ## When this guide applies Use the Standard Financial Model for ecommerce when you want one document covering revenues, hiring, expenses, statements, inventory, and cash. It fits DTC brands with a paid acquisition motion, wholesale + DTC hybrids, subscription box and repeat-purchase models, hardware + consumable models, and any ecommerce business you want investor-ready financials for. The free [Ecommerce Forecasting Tool](https://www.hemrock.com/ecommerce-forecasting-tool/) is a better fit if you want a revenue-only cohort model with historicals (~10x less code). See [below](https://www.hemrock.com/docs/ecommerce-standard#when-to-reach-for-the-ecommerce-forecasting-tool). ## Configure it in the Standard Financial Model The whole revenue model can run off `Get Started`. Cells to set: **Model structure** - `D10`: Base Timescale. Leave at "monthly" for ecommerce. - `D11`: Periods. Default 72 (6 years). - `D12`: Date of first period. **Revenue model type** - `D22`: Revenue model type. Set to `ecommerce`. This wires the `Revenues` sheet for transaction-style repeat purchase instead of subscription retention. - `D20`: Growth metric label (e.g. `Sessions`, `Visitors`, `Ad Impressions`). - `D21`: Revenue metric label (e.g. `Orders`, `Customers`, `Transactions`). **Growth (traffic or acquisition)** - `D26`: New Growth Units in first month. - `D27`: Growth start date (usually `=D12`). - `D28`: Initial growth rate. - `D29`: Growth rate deceleration. Default `-5%`. Ecommerce acquisition channels mature quickly; tune this up (more negative) if you're forecasting a paid channel you expect to saturate. - `D30`: Use seasonality. For ecommerce, set to `yes`. Seasonality is usually material. - `D34-D35`: CPA per paid Growth Unit and `% acquired through paid`. Most ecommerce brands run paid as the majority channel; set `D35` to `100%` if paid is everything. **Conversion (Growth Units to Orders)** - `D40`: Conversion rate. For session-to-order, 1–3% is a common _starting point_ to tune against your analytics. The default is illustrative, not a benchmark. If your Growth Unit is already "customers acquired," set conversion to `100%`. - `D41`: Conversion lag months. `0` for most ecommerce (session converts in-session). **Two segments (Segment 1 vs Segment 2)** `D44-E44` are segment names. Common ecommerce uses: - DTC vs Wholesale (different AOV, different billing, different channels) - First-purchase vs Subscription (subscribe-and-save) - Core product vs Accessories - B2C vs B2B Configure each segment: - `D45-E45`: % split of conversions to each segment. - `D46-E46`: Churn rate per period. For ecommerce, "churn" is the _inverse_ of repeat-purchase rate: if 40% of customers reorder in a given cycle, churn is `-60%`. - `D47-E47`: Churn period. `1` = monthly reorder cadence, `3` = quarterly, `12` = annual. This is your repeat-purchase cycle. - `D54-E54`: Avg Revenue per Revenue Unit (AOV). - `D55-E55`: Billing period. `1` for ecommerce (billed at order). - `D56-E56`: % billed upfront. `100%`; orders are paid at checkout. **Why segments matter for ecommerce:** DTC and wholesale have different AOV, different repeat-purchase cycles, and different cash timing. Splitting them keeps margin math honest on the `Breakdown` sheet. **Seasonality: required for ecommerce** - `D131-D142`: monthly % adjustments, Jan through Dec. `D143` sums (should stay at zero; monthly adjustments shift the shape, they don't change the annual total). - Ecommerce usually has Q4 lift (November, December), summer softness, and a post-holiday dip. Populate this early. The shape matters for inventory, hiring, and cash. - More at [Seasonality](https://www.hemrock.com/docs/seasonality/). **Overrides on `Revenues`** When you need month-specific overrides (promos, launches, stock-outs), the input rows on `Revenues` (Segment 1 in R20-R691, Segment 2 in R693-R1172): - `R114`: Manual growth adjustments (columns AB-CU) for one-time traffic events. - `R202`: Manual conversion adjustments for promos or site changes. - `R378+`: Per-month AOV overrides for launches or price changes. ## Common modifications - **Additional growth channels.** Replicate the growth block on `Revenues` for each channel, or add channels on `Forecast` with custom logic and sum them before conversion. - **Multiple SKUs or bundles.** Build a SUMPRODUCT table for weighted-average AOV, feed into `D54`. For AOV differences that matter for margins, split across the two segments instead. - **Cost of goods sold, shipping, fulfillment.** Default on `Forecast`. Add expense rows in R72-R95 using [drivers](https://www.hemrock.com/docs/drivers/): `% of Revenue Cat 1` for COGS (`R70`), `$ per Order` for shipping and fulfillment (drive off Revenue Units), `% of Revenue` for payment processing. - **Inventory.** Prebuilt on `Forecast` R613-R639. Inputs on `Get Started` cover lead times (months from PO to stock), minimum order quantities (dollar value), safety stock (minimum on-hand), and payment terms (upfront vs N days arrears). The section calculates dollar inventory needed to support the forecast. It does not unit-count SKUs, but can be extended. More at [Inventory](https://www.hemrock.com/docs/inventory/). - **Returns and refunds.** Add as a `% of Revenue` driver row on `Forecast`, or net against AOV on `D54-E54`. - **Hardware + consumables.** Use Segment 1 for the one-time hardware purchase (set `D47` churn period high so cohorts don't repeat) and Segment 2 for the consumable subscription (recurring churn cycle). Or build the hardware as a driver off Segment 2 new customers. - **Custom revenue logic.** Build it outside and link in. See [Integrating models](https://www.hemrock.com/docs/integrating-models/). ## When to reach for the Ecommerce Forecasting Tool The [Ecommerce Forecasting Tool](https://www.hemrock.com/ecommerce-forecasting-tool/) is ~10x less code and purpose-built for cohort-based repeat-purchase modeling. Use it when you only need a revenue forecast, not full statements; when you want to load real historicals on the `Historicals` sheet and calibrate the retention curve against actual per-cohort reorder data; or when you want separate AOV for new vs repeat customers (`D17` vs `D18`) and separate CAC for acquisition vs reactivation (`D31` vs `D32`), built in without editing segments. Both models use cohorts. The Ecommerce Forecasting Tool exposes the per-cohort retention curve more directly; the Standard Model wraps it inside a full P&L. ## Edit with AI Start with the [universal context primer and Standard Model template primer](https://www.hemrock.com/docs/ai/). Paste them into Claude for Excel before anything specific.