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Catalog Specialist 5 min read·Updated Jul 19, 2026

Creating a controlled discount campaign

Pick products, set a discount and a window, and let the revert logic restore prices when it ends — no promotion can price a product into a loss.

A promotion in Magistry is a controlled object, not a pile of manual price edits: a set of products, a discount, and a schedule window, created as one campaign that knows how to undo itself. The difference matters most at the end — the classic promotion failure isn't the discount, it's the price someone forgot to restore.

Setting one up

  1. 1Pick the products. You can select directly or start from a proposal by the Promotions Strategist, which plans campaigns around what the data supports discounting.
  2. 2Set the discount. Proposals are margin-aware — a discount that would take a product below its cost floor doesn't pass, and products without verified costs can't be discounted at all.
  3. 3Set the schedule window: a start and an end, not just a start. The end is when the revert logic takes over.
  4. 4Review and confirm. The campaign is a logged decision like everything else — you can see what it will change before it changes it.

The revert logic

When the window closes, prices restore to their pre-campaign values automatically — the revert is derived from what the campaign recorded when it applied, so it restores what was actually there, not what someone remembers. Sweeps back this up: if anything is left discounted outside an active window, it gets caught and surfaced rather than quietly persisting.

Reading the results

Because the campaign has clean start and end boundaries, its effect is measurable: what the discounted products did inside the window against their baseline. That record is what the Promotions Strategist learns from — which discount depths and durations actually moved profit for your catalog, not for catalogs in general.

The end date is the most important field on a promotion. Magistry treats it that way.

// still stuck?

Talk to a human who knows your store.

Live chat Mon–Fri 09:00–18:00 CET, email with a 24-hour SLA, or a 30-minute call. Support reads the same decision_log you do.

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