What is markdown optimisation in fashion retail?
The use of analytics and AI to decide when, where and how deeply to reduce prices so stock clears with the least loss of margin.
In short
Markdown optimisation is the use of data and AI to plan price reductions. It predicts how sales will respond to different discounts and recommends when, where and by how much to mark down each product, so stock clears by a target date with the smallest possible loss of margin.
How does it work in practice?
The system starts with current stock, recent sales, remaining selling weeks and business rules, such as allowed discount steps or brand guidelines. A price elasticity model estimates how many extra units each discount level would sell. An optimiser then compares scenarios and proposes a markdown plan, for example a modest first reduction in some stores and a deeper one where stock is high. Merchandisers review, adjust and approve the plan, and the cycle repeats every week.
Why does it matter for fashion businesses?
Markdowns are one of the largest levers on full-season margin. Reducing too early gives away margin on products that would have sold anyway, while reducing too late leaves stock that must be sold off cheaply. For wholesale brands the topic matters too, because retailers' markdown results drive requests for markdown support and shape future orders.
How is AI changing it?
Machine learning models can learn price response at a much finer level than rule-based approaches, taking into account size availability, weather, local demand and competing promotions. They can also suggest alternatives to discounting, such as moving stock to stores or channels where it sells better. Increasingly, markdown decisions are linked to allocation and replenishment, so the whole end-of-season process is planned together.
Common pitfalls
- Optimising revenue alone while ignoring brand perception and price consistency.
- Feeding models with incomplete stock data, for example missing returns in transit.
- Overriding recommendations without recording why, so the model cannot learn.
- Not feeding markdown results back into buying and open-to-buy decisions.
Frequently asked questions
What is the goal of markdown optimisation?
The goal is to clear seasonal stock by a set date while keeping as much margin as possible. It balances sell-through targets against the cost of each discount.
How is markdown optimisation different from dynamic pricing?
Markdown optimisation focuses on permanent price reductions to clear stock at the end of a product's life. Dynamic pricing changes prices more frequently, up or down, in response to demand and market conditions.
