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As the days grow shorter, the bakery assortment changes: plum tarts and vermicelles make a comeback, pumpkin bread and heartier snacks gain popularity, while ice cream and light summer items fall out of favor. The fall season is a strong sales period for many businesses—but only if the transition is timed right.
Getting the timing just right is the real challenge. If you switch over too early, you’ll be stuck with seasonal merchandise. If you wait too long, you’ll miss the first cool weeks, when demand is already shifting.
Why Fall Is So Hard to Plan For
The start of the season isn't a specific date. The plum season doesn't begin on September 1, but rather when the fruit is ripe and customers are in the mood for it—and that can vary by weeks from year to year.
The weather fluctuates wildly. A golden October day at 22°C sells differently than a cold, wet one at 8°C. Hardly any other season has such wide fluctuations from one day to the next as fall—and planning errors are correspondingly significant.
Vacations and holidays are piling up. Fall breaks, which vary by region, are changing customer traffic patterns. Added to this are local events such as markets, meat festivals, and fall fairs, which have a significant impact on individual locations.
What the Data Tells Us About Fall
Sales data from recent years provides the answers to the most important questions about the fall season: When does demand for Swiss tarts start to pick up? How sharply do sandwich sales drop when temperatures fall? Which store responds most strongly to the fall break?
It’s nearly impossible to analyze these patterns manually—there are too many items, too many locations, and too many overlapping factors. AI recognizes them automatically. GoNina analyzes sales data from the point-of-sale system, combines it with weather forecasts, holidays, and school breaks, and provides a daily forecast for each item and location for the next seven days.
The start of the season is therefore no longer estimated but derived from the data—including store-specific variations. And the daily weather effect is automatically factored into every order recommendation.
Specific Recommendations for Fall Planning
Add seasonal items early. Plum tarts, pumpkin products, and fall pastries should be clearly listed as separate items in the point-of-sale system—this is the only way to build a usable sales history for next year.
Plan the transition gradually. Instead of replacing the summer assortment on a specific date, it’s worth allowing for an overlap period of two to three weeks during which both assortments are carried in adjusted quantities.
Stay flexible in response to the weather. Especially in the fall, it pays to plan based on the weekly forecast rather than the calendar. A warm fall weekend still calls for summer-sized portions.
Businesses that use GoNina reduce their surplus by up to 52% and increase their revenue by up to 6%—effects that are particularly noticeable during transitional seasons such as fall.
Frequently Asked Questions
How do I plan for seasonal items that are only available for a few weeks?
The AI uses the item’s data from the previous year and the sales trends of similar seasonal products. Starting on the first day of sales, current figures are factored in, so the forecast adjusts to actual demand within days.
What if fall turns out to be unusually warm or cold?
That's exactly why weather data is included in the forecast. The suggestions aren't based on the calendar, but on the actual weather conditions for the coming days.
Conclusion
The fall season rewards businesses that plan for the transition based on data rather than the calendar. Those who automatically factor in the start of the season, weather conditions, and holidays into their forecasts can take full advantage of the busy fall weeks—without ending up with unsold Swiss pastries. You can read more about seasonal patterns in the article on seasonality in the bakery industry.
Our comprehensive guide to AI sales forecasting for bakeries provides a complete overview.
