How to plan purchases of seasonal goods: find seasonality in the data, calculate the order volume, split purchasing into waves and prepare the website, feed and ads for the peak in time.
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Purchases of seasonal goods are planned from sales history: take last year's demand by week, adjust it for growth and promotions, add safety stock and subtract current stock and shipments in transit. Orders are split into several waves so as not to freeze money in stock that may not sell.
Start with your own data: sales by week or month over several years, if you have them. A peak that repeats in the same periods indicates seasonality. New stores may lack history, so add external sources:
Distinguish three types of demand: calendar-based (holiday gifts), natural (gardening season) and weather-dependent (heaters, umbrellas). The last one is the hardest to forecast, so a smaller stock is kept for it and fast reorders are agreed on.
For each season it is useful to have a working calendar in which supply lead times are counted back from the peak date. The table shows the logic, and the specific timelines depend on the supplier and logistics.
| Stage | What to do | What to check |
|---|---|---|
| Forecast and budget | Compile weekly sales, stock levels and promotions of the last season, build a forecast by product and category | How many sales were lost due to out-of-stock items, suppliers' minimum batches |
| First purchasing wave | Order the core assortment that sold steadily | Delivery times with a buffer for delays |
| Preparing the website and ads | Update categories, the feed, banners, launch campaigns | Availability and prices match on the website, in the feed and in the ads |
| Peak season | Monitor stock daily, place reorders | Sell-through speed, load on the warehouse and support |
| Post-season sale | Lower the price in stages, put together bundles | Margin after the discount, cost of storing leftover stock |
| Results | Compare the forecast with the actual figures for each product | Forecast errors worth taking into account next year |
The basic formula is simple: the order volume equals the sales forecast for the period plus safety stock minus current stock and minus shipments in transit. For example, if 200 units are expected for the period, safety stock is 20, there are 30 in the warehouse and nothing in transit, you should order 190 units.
The forecast is adjusted for four things:
Safety stock depends on demand fluctuations and supplier reliability: the more unstable the sales and the longer the lead times, the larger the stock. Calculate most carefully the products that bring in most of the revenue. Simpler rules are enough for the rest.
A single large purchase ties up money and increases the risk of leftover stock. Waves reduce this risk:
Negotiate terms that reduce risk: partial return or exchange of unsold goods, deferred payment, consignment sales. For new items, collect pre-orders and back-in-stock notification sign-ups: this is a cheap demand signal. If the supplier's minimum batch exceeds the forecast, compare the cost of the surplus with the profit you will lose due to a shortage.
Search engines need time to index and evaluate pages, so seasonal categories and guides are published in advance, a few weeks or months ahead depending on the niche. Keep the URLs of seasonal pages the same every year: the page accumulates links and history. After the season, leave it in place and update the content, and for out-of-stock products show the expected arrival date and a notification sign-up.
In the Google Merchant Center feed, the availability status must match stock levels, otherwise ads lead to unavailable products. Increase budgets gradually: campaigns need data to learn. Pause ads for out-of-stock items. State peak delivery times on the website, in the cart and on the terms page.
Leftover stock is sold off in stages: first a small discount, then a bigger one, then bundles and collections. Take storage costs and shelf life into account. Products without a shelf life are sometimes more profitable to keep until the next season if there is warehouse space. For each item, record the forecast, the actual figures, the date of the first shortage and the reason for the deviation. These records improve the next forecast more than any formulas.
The sell-through rate shows what share of the purchased stock you sold during the season. The share of full-price sales shows how much you had to cut prices. The number of days out of stock and the estimate of lost sales show how much you missed out on due to shortages. Inventory turnover helps compare products with each other. Calculate these metrics by product group and for the store as a whole.
A high sell-through rate and many days out of stock indicate that purchasing should be increased next year. A low sell-through rate and deep discounts indicate overstocking. Compare the cost of the two mistakes: a shortage costs lost profit and disappointed customers, a surplus costs frozen money, warehouse space and discounts. For products with a high margin and stable demand, a shortage is usually more expensive; for fast-changing and fashion items, the surplus becomes more expensive.
If a product does not sell after discounts, consider bundles, free gifts with purchase, selling on marketplaces and passing the batch on to partners. Frozen stock is sometimes more profitable to turn into cash quickly than to store until the next season.
Compare the results with the plan and update the calendar: move the date of the first wave if the goods arrived late, review supplier terms, adjust stock by product group. Add reminders to update seasonal pages and launch ads. Then the new season starts with a ready calendar and accumulated data.
Count back from the start of the peak the production or dispatch time, delivery, receiving, publishing on the website and a buffer for delays. The specific figures depend on the supplier.
Rely on search trends, supplier data and competitors' experience, order a trial batch and collect pre-orders. After the first season you will have your own data.
No. Keep the URLs, update the content and show when the next delivery is expected. This way the page keeps its history and gains rankings faster in the new season.
There is no universal number. The stock depends on demand volatility and supplier reliability. Start with a small buffer and adjust it based on the last season's data.
Pass current stock levels to the ads: a feed with availability, automatic pause rules, budget limits by item. Ads are scaled up after the goods arrive.
Seasonal demand is as predictable as the data you collect: weekly sales, out-of-stock periods, promotions, queries. This data is the basis for the forecast, purchasing waves and the calendar for preparing the website and ads. A forecast is never exact, so keep a budget reserve for reorders and record the results of each season. Each next forecast builds on previous records, so accurate data brings more and more value over time. If you need help, LightSEO, a digital agency from Mukachevo, will help prepare your website for the peak with SEO promotion of your online store and set up Google ads in line with your stock levels.
