AI Sales Forecasts for Bakeries: The Complete Guide

Every day, bakeries face the same question: How much should they produce? Producing too much leads to returns, food waste, and unnecessary costs. Producing too little results in empty shelves, lost sales, and disappointed customers. In most bakeries, this decision is still made based on experience and gut instinct—often under time pressure and without a complete set of data.

AI-based sales forecasts are fundamentally changing this. They automatically analyze sales data, weather, holidays, school breaks, and other influencing factors, and provide specific production recommendations for each product and location. In this guide, we explain how it works, what benefits it offers, and what bakeries should keep in mind when implementing it.

What are AI sales forecasts?

An AI-based sales forecast uses machine learning to predict future demand based on historical sales data and external factors. Unlike simple average calculations, AI identifies complex patterns and correlations that are barely visible to humans.

For example: On a Wednesday in March, with a temperature of 14°C and light rain, two days after a holiday, Store A typically sells 23 pretzel rolls and 45 croissants—but Store B sells only 12 pretzel rolls and 60 croissants. A human cannot calculate such location- and product-specific patterns for hundreds of products every day. AI can.

GoNina one such AI platform. It was developed specifically for bakeries, restaurants, and other businesses that handle perishable goods, and is currently in use in Switzerland, Germany, Austria, France, and other European markets.

The Problem: Why Manual Planning Has Reached Its Limits

Demand for baked goods is influenced by a variety of factors. The weather affects purchasing behavior—on hot days, more cold drinks and lighter snacks are sold, while on cold days, more bread and pastries are sold. School vacations alter customer traffic, especially at neighborhood bakeries. Holidays shift demand, local events bring in additional walk-in customers, and weekdays have their own patterns.

In practice, it is impossible for store managers or production managers to take all these factors into account on a daily basis for every product at every location. Most bakeries therefore rely on rules of thumb: “Fewer croissants on Mondays,” “More bread when it rains,” “20% more before Easter.” These guidelines are helpful, but they’re too general. The result is unsold inventory at the end of the day or products that sell out too early—both of which cost money.

This becomes particularly complex for chain bakeries. If you’re planning for five, ten, or twenty locations, each carrying 50 to 200 items, it’s no longer feasible to manage this manually. In such cases, production planning becomes a full-time job—and yet it often remains inaccurate.

How do AI sales forecasts work in practice?

The process can be broken down into three steps:

Step 1 - Data Integration: The AI platform connects to the bakery’s POS system. With GoNina , this GoNina through a direct interface with HS-Soft, ProtecData, Lightspeed, and other popular POS systems. Sales, product, and store master data are automatically imported. Additionally, external data sources are integrated: weather forecasts, holiday and vacation calendars, and local event data.

Step 2 - Analysis and Learning: The AI analyzes historical sales data and identifies patterns. It learns how weather, day of the week, season, and location affect the sales of individual products. The model continuously adapts: new products, changes to the product range, or shifts in customer traffic are automatically taken into account.

Step 3 - Forecast and Order Recommendation: Based on the analysis, the AI generates a daily sales forecast for each product and location for the next 7 to 30 days. These forecasts are fed back into the system as specific order recommendations or production quantities. The company can either accept the recommendations directly or adjust them manually.

The result: Instead of making estimates every day, the bakery receives data-driven recommendations that are automatically updated.

What results are realistic?

Businesses that GoNina achieve the following results based on real-world data from over 50 active locations:

52% less surplus: More accurate forecasts mean less unsold inventory is produced. This reduces returns, food waste, and disposal costs.

6% increase in sales: More accurate forecasts also mean that popular products are less likely to sell out prematurely. Availability increases, and so does sales.

12 hours saved per month: The daily analysis of sales figures, the creation of production lists, and coordination between stores are largely eliminated. The team can focus on craftsmanship and sales.

These results vary depending on the size of the business, the product range, and the initial situation. As a general rule, the larger the product range and the more locations, the greater the effect.

Which bakeries are AI forecasts suitable for?

Whether you have two stores or twenty: Anyone who prepares fresh products in the morning and delivers them to various locations knows the daily challenge—how much of each product should go where today?

More locations = greater impact. Complexity increases with every branch. Instead of headquarters distributing orders across the board or each branch placing orders individually, GoNina provides GoNina recommendations for each branch and product. Businesses with multiple locations save the most time and reduce excess inventory the most significantly.

It’s worth it even if you have just one location. If you carry a wide assortment and have to decide every day how many braided loaves, how many rolls, and how many croissants to put in the oven, you’ll benefit from a forecast that automatically takes into account the weather, the day of the week, and the season. Fewer returns in the evening, fewer empty baskets in the afternoon.

What sets GoNina other solutions?

GoNina developed specifically for the food industry. Three things are particularly important to us:

1. Accurate Forecasts: For bakeries, one thing matters most in the end—having the right amount at the right time. That’s why we’ve developed industry-leading forecasting models that provide daily forecasts by product and location. These models are developed in collaboration with ETH Zurich and supported by Innosuisse, NVIDIA Inception, and other partners.

2. Simple for everyday use: Bakeries aren’t IT companies. GoNina is GoNina be quick to implement and easy to use. Direct integrations with POS systems such as HS Soft, ProtecData, Lightspeed, and others ensure that onboarding is completed in just a few days—without manual data entry or CSV exports.

3. Close to our customers: We respond quickly, provide personalized support in German, French, English, and Italian, and host all data in Switzerland and the EU. But above all: We listen. Customer feedback goes directly into product development—not into a queue.

Every business can try GoNina risk-free for GoNina weeks. If you’re not satisfied, you’ll get your money back.

Frequently Asked Questions

How much does it cost to use AI sales forecasting?
‍Thecost depends on the number of locations and the scope of theproject. GoNina transparent pricing, which can be viewed on the website. You can get started risk-free with a 4-week trial period that includes a money-back guarantee.

How long does the setup take?
‍Ifyou already have a POS system, onboarding usually takes just a few days. GoNina the setup and integration—the effort required to run the system is minimal.

Do I need to replace my existing systems?
‍No. GoNina your existing POS system and inventory management system. The forecasts are integrated into your existing workflows as order suggestions.

Does this also work for seasonal products or new items?
‍Yes. The AI automatically recognizes seasonal patterns and can quickly learn about new products by using similar items as a reference.

In which countries is GoNina ?
GoNina available in Switzerland, Germany, Austria, France, and other European markets. The platform supports German, French, English, and Italian.

Conclusion

AI-based sales forecasts are no longer a thing of the future—they’re available today and deliver measurable results. For bakeries, this means less waste, higher sales, less planning effort, and better product assortment decisions. Read more here about how AI forecasts specifically reduce planning effort. The technology is here. The only question is when your business will take the plunge.