Use Cases
Glamswag planned a bigger ad budget — and forecast the inventory it would need
An online fashion retailer planned a significant increase in advertising investment — and needed to know, before the campaigns ran, how much inventory that demand would require.
More ad spend is a demand decision, not just a marketing one
Glamswag, an online fashion retailer, planned a significant increase in advertising investment. Ad spend only turns into revenue if there's stock to sell into the demand it creates — and a marketing budget can be approved in a single meeting, while inventory has to be ordered, shipped, and shelved on a timeline that doesn't move that fast. So the real question behind the spend wasn't how many dollars to commit to ads — it was how much inventory that spend would need, and whether it could be in place before the campaigns went live. Predicting that requirement was the challenge Glamswag needed to solve.
The two ways a growth plan goes wrong
A bigger ad budget can fail in either direction. Undershoot the inventory and the campaign has already been paid for by the time the shelf goes empty — the traffic arrives, and there's nothing to sell it. Overshoot and the opposite problem shows up instead: the extra units bought against the ad plan sit in a warehouse, tying up the cash the campaign was supposed to generate a return on. Neither failure is really about the ad spend; both come from getting the inventory number wrong on either side of it. Avoiding both was exactly the balance Glamswag needed to hit — enough stock to meet the demand the campaigns would create, without overbuying against a forecast that never arrives.
Forecasting against a plan, not just a past
A forecast built purely from sales history has no way to see a planned change coming — it just extrapolates forward from what already happened. Assisty's forecast can be pointed at a planned change instead: ask what a demand lift of a given size does to the numbers, and the forecast recomputes on the spot — the reorder needs move with it, not just the demand curve — rather than requiring a new spreadsheet for every version of the plan. That recompute is what turns a spend plan into an inventory number before the budget is spent, and it's computed at the level the buying decision actually happens at: predicted sales per product and per variant, over a horizon that can be set to match the campaign window and the supplier's lead time rather than a fixed lookback. The grain matters most for exactly this kind of retailer — an ad-driven demand lift doesn't land evenly across a size or colorway run, so a number that looks right for the product as a whole can still leave the one variant that's actually moving sold out while the rest of the run sits. The same forecast marks which items are on pace to run out before the horizon ends and which are already overstocked against it — the two ways a bigger ad budget can go wrong — and those at-risk items carry straight into the Smart Buying Table, ranked there by money at stake rather than by which one is simply closest to empty. And because the forecast can be questioned — asked why a number is moving, and rebuilt on a baseline that excludes any days a product was actually out of stock — a spend decision doesn't have to take the projection on faith.
Dashboards that move when the plan moves
A forecast tied to a spend plan is only useful if it stays visible while the plan is still changing. Glamswag reports its dashboards updated automatically as the sales forecast moved, so the inventory picture stayed current with the plan. Results also reached the team through a Google Spreadsheets integration, for accessibility — the same path Scheduled Reports offers today: a report synced straight to a Google Sheet on the cadence you pick, into a fresh sheet or appended to one that's already open. That schedule is built from the report already on screen — its breakdown, time range, filters, and columns carried over as-is, rather than rebuilt from scratch for the spreadsheet — and it runs daily, weekly, or monthly at whatever hour is chosen, in the store's own timezone. Run now sends a test delivery the moment the schedule is saved, every run afterward stays in history with the file it sent kept and re-downloadable any time, and a reusable profile keeps that same cadence one click away the next time a report like it needs scheduling.
Stock that matches the plan
Assisty projected the inventory requirement against the planned spend before the budget was committed.