Plan markdowns to clear seasonal stock while protecting margin
A SKU-by-SKU markdown cadence based on weeks of supply and sell-through, with the margin impact of each price cut.
The prompt
Help me build a markdown plan to clear seasonal inventory.
Season and exit date: [e.g. "Fall outerwear, must be out by Jan 31"]
SKU data: [PASTE: SKU/style, on-hand units, on-order units, cost, original price, current price, units sold last 4 weeks, sell-through % to date]
Margin target for the season: [e.g. "maintained margin of 52%"]
Channels: [stores / online / outlet / marketplace]
Constraints: [e.g. "brand MAP rules", "no more than 3 price changes", "vendor markdown allowance available"]
Steps:
1. Calculate weekly rate of sale, weeks of supply against the exit date, and projected ending inventory at current price for each SKU.
2. Sort SKUs into on track (hold full price), at risk (first markdown now), and stuck (deeper cut, move to outlet, or return to vendor).
3. Propose a cadence (e.g. 30% / 50% / 70%) with timing, using the smallest first cut likely to move the volume. State the price-response assumption you used and label it as an assumption.
4. Estimate the margin impact of each step versus holding price, and compare the result with my margin target.
5. Flag SKUs where a markdown will not help (broken size runs, wrong color, damaged) and suggest alternatives such as consolidating into fewer stores or bundling.
Return:
- A table: SKU, weeks of supply, status, recommended action, timing, projected sell-through, margin impact.
- A one-paragraph summary for my merchandise manager.
- A list of data to check before executing.
Show your calculations. Do not invent numbers I have not given; mark gaps [ADD].
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Data & Analysis prompts
What to fill in
- e.g. "Fall outerwear, must be out by Jan 31"
- e.g. "maintained margin of 52%"
- stores / online / outlet / marketplace
- ADD
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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