A lightweight planner for small e-commerce brands. Upload your weekly Shopify sales CSV — get a forecast, reorder plan, and shipment plan with the reasoning explained, not hidden in a black box.
Built for e-commerce brands with 1–100 active SKUs, one warehouse or 3PL, and a small team running the show.
Export sales from Shopify like you already do. Drop the file in. Sales, stock positions, and SKU performance update together. No integrations to maintain.
Tell the tool what it can't see in the data. Category trends, upcoming launches, promotions, supplier issues. A sentence or two is enough.
“Category is down ~20% YoY based on competitor signals. Expecting a summer pull-forward in linen.”
“Stone variant restocking late — supplier shifted factories. Sand colour soft-launched 4 weeks ago, performing well on Instagram.”
“Planning a 15% promo on tees Jun 18–22.”
Product-line level, explained in plain English. You see what the model assumed, why it weighted recent weeks the way it did, and how your context changed the answer.
The forecast splits across sizes, colours, and variants based on your historical mix. Adjust where you have a reason to. Leave the rest. New launches handled separately, so they don't break the model.
Reorder quantities respect supplier MOQs, carton sizes, and lead times. Compatible suppliers from the same country get grouped into shared containers. You see freight options — sea, air, consolidation — and the trade-offs of each.
The one SKU that pays the rent runs dry for two weeks. You watch the revenue you forecasted disappear into a back-order page customers never come back to.
Six months of inventory sitting in a colour that didn't land. The next reorder is due before you've cleared the last one.
Tabs feeding tabs, formulas patched on a Sunday. Every reorder is a fresh round of guessing, in a file no one else can open without breaking.
Six-figure contracts, three-month onboarding, an interface that assumes a full ops team behind it.
Drops a value in your dashboard. Doesn't know about your category trend, your supplier delay, or the promo you're running next week.
Works until you change a SKU naming convention, a sheet, or yourself. One small break and the whole reorder cycle slips.
Operators don't need a number. They need a number, the reasoning behind it, and a way to push back when their gut says otherwise. Ecom Forecast is built around that loop — model proposes, you decide, the plan reflects both.
Every forecast comes with the weights, assumptions, and your context note attached. Audit it, edit it, or override it in one click.
Products with under 8 weeks of history use a comparable variant's curve. They don't drag the main model into noise.
Suggested quantities respect supplier minimums and carton multiples. No rounding gymnastics in a side cell.
Compatible suppliers in the same origin get grouped into shared containers, with utilisation visible before you commit.
Compare landed cost and lead time per option. Mix freight modes per shipment when urgency demands it.
Not 10,000. The data model, the UI, and the assumptions are tuned for the brand that ships from one warehouse.
“For three years I ran reorders on a Sunday afternoon spreadsheet. Half the time I was right. The other half, the brand paid for it — either in stockouts on the bestseller or in a pallet of the wrong colour sitting in the warehouse.”
Ecom Forecast is the tool I kept trying to find and never did. It assumes you already know your brand better than any model does. It just removes the part where you have to translate that knowledge into a planning sheet every week.
If you're running 1–100 SKUs with a small team and no full-time planner, this is built for you specifically. Not adapted from something larger.
Early access opens in waves. Join the waitlist and we'll bring you in as the next cohort opens up.
No spam. No sales calls. One email when your access is ready.