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Guide

How to forecast demand for a DTC brand

A practical method you can run without a data scientist — and how to turn the forecast into orders.

In short: To forecast demand for a DTC brand: (1) start from each SKU's recent sales velocity, (2) adjust for seasonality and promotions, (3) add other channels (Amazon, wholesale) for total demand, and (4) express it as weekly demand you can plan coverage and replenishment against. SpyGlass automates all four steps.

Step 1 — Start from per-SKU velocity

Use recent units sold per week per SKU as your base signal — not a blended catalog average. Velocity is the honest starting point because it reflects what customers actually buy.

Step 2 — Adjust for seasonality and promos

Layer in known seasonality and planned promotions. A hero SKU during a seasonal peak or a creator push will run well above its baseline velocity; plan for it or you'll sell out.

Step 3 — Add every channel

DTC isn't the whole story. Add Amazon and wholesale demand so your total demand — and the finished goods it consumes — is complete. Channels share inventory; forecast them together.

Step 4 — Convert to a plan

Express demand as weekly units, compare to weeks-on-hand coverage, and generate reorders that respect lead times and MOQs. See how SpyGlass forecasts →

Frequently asked questions

What's the simplest way to forecast DTC demand?
Start from per-SKU weekly sales velocity, adjust for seasonality and promos, add other channels, and express it as weekly demand to plan against.
How far ahead should I forecast?
At least your replenishment lead time plus safety stock — usually a few months for growth-stage brands.
Do I need special software?
You can start in a spreadsheet, but it breaks down across channels and locations. SpyGlass automates the forecast and connects it to replenishment.

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