Holiday promotion plan
I haven't invented any numbers beyond your own. Where a number is unknown, I've marked it as an input you need to supply.
What last year's data says
At 20% off, margin per unit drops from 45% of full price to 25%, which is only 56% of the normal profit per unit. The break-even sales lift is 1/0.56 ≈ 1.8x baseline units, before ads and extra support cost.
| Discount | Margin per unit (% of full price) | Profit per unit vs. normal | Lift needed to break even |
|---|---|---|---|
| 10% | 35% | 78% | 1.3x |
| 15% | 30% | 67% | 1.5x |
| 20% | 25% | 56% | 1.8x |
| 25% | 20% | 44% | 2.25x |
Last year's tripled orders probably cleared break-even on paper. Three things probably ate into that:
- Lost sales: your three best scents sold out on day 2, so you missed demand you could have served.
- Support cost: the late-delivery emails cost time and goodwill.
- Pull-forward: some of those orders were likely bought early rather than extra. Check whether December and January dipped.
1. One-page plan
- Goal: profit from the promotion, with a secondary aim of new customers who reorder. I wouldn't aim for "orders tripled" again, because volume isn't what limited you. Stock and delivery were.
- Margin floor (my recommendation, your call): no offer below 30% of full price in margin, which means a discount of at most about 15%. Test stacked codes against this floor.
- Offer structure:
- Don't discount the three best scents. They sell anyway and they are your supply constraint. Offer them at full price, or only inside bundles with a cap.
- Discount the rest of the range by 10–15%. Pair the offer with a bundle, such as "3 candles for X", where the slow scents carry the discount.
- Gift with purchase or free shipping above a threshold. Either one raises order value and protects your price better than a deeper percentage. Set the threshold above your typical order. I need your average order value and shipping cost to size it.
- Early access for your email list, 24–48 hours before the public launch. This rewards repeat customers and spreads out the first-day rush.
- Ads (2,000): I'd put most of it into retargeting and your own list, because those audiences are cheapest. Hold back about 20–25% as a reserve for the mid-campaign check. Broad prospecting for new customers is the riskiest use. I'm not assuming a cost per order, so track it in the first 48 hours and adjust.
- Window: 4–5 days around Black Friday and Cyber Monday, not a full week. A shorter window concentrates demand but caps the support load. Confirm the dates for each market (see the calendar).
2. Stock and the 3-week lead time
This is where last year went wrong, and the lead time is why you need to act now.
- Order production by about Oct 20. Stock then arrives around Nov 10, with a buffer before Black Friday (Nov 27, 2026). An order placed after Nov 3 can't arrive in time.
- Size the order from a range, not one guess. Take your normal daily units (I need this number), multiply by roughly 1.5x, 2x and 3x over the promotion days, then split by scent. Your 1,800 units should be allocated by scent against that forecast. Don't assume they are spread evenly across scents.
- Decide the sell-out rule in advance. For example: the best scents get a waitlist or a "back on [date]" label, and a substitute scent is suggested in a bundle. Don't leave a sold-out item on a promotional page.
- Ask your maker for the cost of a bigger order and check the cash needed. Overstock of candles keeps, but cash is limited.
3. Calendar (confirm every date for the US and Germany)
| When | Stage | Must be true before the next step |
|---|---|---|
| Oct 7–12 | Pull last year's data, set the margin floor, pick the offer | Baseline daily units and per-scent sales known |
| By Oct 20 | Place the production order | Quantities set per scent |
| Oct 20–Nov 13 | Build the email list, plan the creative, set up site and codes | Codes tested, including stacking |
| ~Nov 10 | Stock arrives; count it | Actual stock by scent confirmed |
| Nov 16–23 | Teaser emails; write support answers; confirm carrier cutoffs | Delivery promises are true for each country |
| ~Nov 25 | Early access for the list | |
| Nov 27–30 | Public sale (Black Friday to Cyber Monday) | Check at hours 6, 24 and 48 |
| Dec 1 onward | Close; ship; send "order by [date] for Christmas" messages | Shipping cutoffs published |
| Dec 7 | First review of sales | |
| Mid to late Jan | Final review once the return window closes | Refunds counted |
Germany also has strong Advent-season buying, with the first Advent on Nov 29. Ask yourself whether a second, smaller moment makes sense there. Also check whether your US and German customers ship from the same stock and how long delivery really takes to each country.
4. Readiness checklist (open items for you)
- [ ] Every offered price clears the margin floor after fees, shipping and returns
- [ ] Stacked codes tested for the worst case
- [ ] Stock by scent counted and compared to the forecast range
- [ ] Sell-out rule decided (waitlist, substitute, hide)
- [ ] Packing capacity per day known, since last year's delays were here
- [ ] Delivery dates promised on the site match carrier peak-season times, for the US and Germany separately
- [ ] Pre-written support replies for delivery, returns and price adjustments
- [ ] Checkout and payment methods tested under load
- [ ] Terms written: exclusions, end time and time zone, return rules, what price returns to
- [ ] Reference prices: for "was" prices, the EU and Germany have specific rules, including showing the lowest price from the previous 30 days. The US has FTC guidance on reference prices. Please verify the current rules for both, and don't use a "was" price that wasn't real.
5. Risks
- Baseline unknown. If you can't say what a normal week sells, you can't say whether the promotion made money. Get that number first.
- A smaller discount may lift sales less than 1.5x. Your 3x last year was at 20%. Treat any lift I mention as an assumption.
- Supply: if the order slips past Nov 10, you repeat last year's problem. Keep a fallback of limiting best-scent bundles.
- Delivery to Germany is a cross-border risk, including customs and VAT, if you ship from the US or the reverse. I don't know your setup.
- Worst case: the sale sells out of the discounted scents early, ads keep spending on traffic you can't serve, and delays produce refunds. The mid-campaign check should pause ads on sold-out items.
6. How to judge whether it was worth it
Compare against the baseline, not against zero.
Incremental profit = (contribution profit during the promotion − ad spend) − baseline contribution for the same days − pull-forward dip − later refunds and extra support cost.
Collect:
- Units, orders and revenue per day, and per scent, for the window, compared with your baseline
- Average order value and units per order
- Contribution profit after discounts, gifts and free shipping, and after the 2,000 in ads
- New vs. returning customers, and cost per new customer
- Sales for 2–3 weeks after the promotion vs. the baseline, to net out pull-forward
- Refund and return rate, rechecked after the return window closes
- Support: number of emails, topics, and hours spent
- Sell-out hours: how long each scent was unavailable
- Repeat purchase rate of new customers after 60–90 days
Decision rule: it was worth it if incremental profit is positive after the dip and refunds, with no best scent out of stock during the window. Note what to repeat, change or stop.
What I need from you
- A normal week's units and orders (the baseline), and the split by scent
- Average order value, units per order, and shipping cost per order for each country
- Whether the margin figure includes shipping and payment fees
- Where you ship from, and how long delivery takes to the US and Germany
- How many email subscribers you have
- Your cash limit for a production order
With these I can turn the forecast ranges into per-scent production quantities and set the bundle prices and free-shipping threshold.
Real run in an isolated folder with only this skill installed. Only the Skill and Read tools were enabled, so no command was run and no file was written. The store and all numbers are invented and the model had no access to a real store. The break-even figures were checked by hand afterwards. Event dates and advertising rules in the answer must be confirmed for each market before relying on them.
它做什么
先确定一个目标和一条利润底线,再帮你选优惠方式(百分比折扣、满额优惠、组合装、包邮、赠品、提前购、限时)以及哪些商品承受得起,畅销款和供货紧张的商品不参与深度折扣。它从活动日期倒推出带负责人和检查点的日历,还有一份就绪清单,涵盖利润与叠加优惠码、按需求区间看库存、履约、客服、网站和支付、各渠道口径一致以及写明的活动条款。活动结束后,它把结果与基线对照,并扣除活动后的销量下滑、后续退款和客服成本,因为热闹的活动也可能亏钱。
输出
一页纸方案、日历、带待办项的就绪清单、风险清单和复盘模板。
适合什么场景
规划节日大促或限时秒杀、决定折扣打多深,以及事后判断这次促销值不值。
低风险:纯指令文件,没有脚本,不联网、不写文件。活动日期、广告和划线价规则、消费者保护法规以及平台活动规则因国家而异且会变;Skill 只会标出来请你确认,不会断言什么是允许的。预期销量提升只是区间和假设,不是预测。它看不到你店铺的数据。试用中它给出的日期和保本数字事后用手算核对过,但日期仍需针对每个市场确认。AIBars 原创(MIT)。已用一个虚构的香薰蜡烛店试用过一次。