Markdown optimisation is the use of data and AI to set clearance discounts. Rather than applying a blanket 30 per cent off at season end, the system works out the timing and depth of each markdown to clear stock at the best overall margin.
Models forecast how quickly an item will sell at different price points, using sales history, stock on hand, seasonality, product age and how customers have responded to past discounts. The system then recommends a price path, such as a smaller cut now and a larger one in three weeks, for each product or store.
Fashion, homewares and grocery retailers use it to avoid leaving money on the table or discounting too early. In hospitality it supports end-of-day specials on perishable food. Electronic shelf labels make it practical to change prices across stores quickly.
Check that the tool accounts for brand rules, price-match promises and Australian Consumer Law requirements on advertised discounts and "was" prices. Beware of recommendations that train customers to wait for sales. Pilot on a few categories and compare sell-through and margin against your usual approach.
It differs from dynamic pricing, which adjusts prices continuously for demand; markdown work is about clearing stock responsibly. Keep a simple record of which discounts you applied and the sell-through each produced, so the system and your buyers can learn from every season.