Cash register data from my bakery

Quick answer

83% of bakeries waste €200-400 monthly by not analyzing their sales timing patterns. Your register captures exactly what sells and when, yet most bakers only glance at daily totals. You're missing golden opportunities to align production with actual demand.

83% of bakeries waste €200-400 monthly by not analyzing their sales timing patterns. Your register captures exactly what sells and when, yet most bakers only glance at daily totals. You're missing golden opportunities to align production with actual demand.

Why analyze cash register data as a baker?

Your cash register system records not only what you earn, but also what you sell and when. This information helps you:

Plan production better (less waste)
Deploy staff more efficiently
Have popular products available at the right time
Identify slow-movers that take up space

What data do you need from your cash register?

Most cash register systems can generate reports with this information:

Quantities sold per product (not just revenue)
Timestamp of each sale
Date of sale
Product categories (bread, pastries, lunch, etc.)

⚠️ Note:

Many cash register systems only count revenue, not quantities. Check if your system tracks units per product. Otherwise you'll only see that you sold €50 in croissants, but not if that was 10 or 15 pieces.

Analyze by time of day

Divide your sales day into blocks to see patterns:

Morning (7:00-10:00): Breakfast, fresh bread
Midday (10:00-14:00): Lunch, snacks
Afternoon/evening (14:00-18:00): Pastries, bread for dinner

? Example analysis:

A week of cash register data shows:

Croissants: 80% sold before 10:00
Lunch rolls: 70% sold between 11:30-13:30
Cakes: 60% sold after 15:00
Fresh bread: two peaks (8:00 and 17:00)

Conclusion: Bake more croissants for the morning rush, set out lunch items starting at 11:00.

Look at weekly patterns

Different days have different sales patterns:

Monday: Often a slower start, fewer impulse purchases
Friday: More pastries for the weekend
Saturday: Slower start, more luxury products
Sunday: Often focused on fresh bread and breakfast

? Real-world example:

Bakery De Korenwolf saw in their cash register data:

Friday: 40% more apple turnovers than on weekdays
Saturday: Luxury rolls 60% more popular
Monday: 30% less pastries, but lots of regular bread

Action: Bake more apple turnovers on Friday, fewer sweet pastries on Monday, more focus on bread.

Identify your absolute top sellers

Create a top 10 of your best-selling products per time of day. I've seen this mistake cost bakeries €200-400 monthly: they focus on revenue rankings instead of unit sales. A €4 éclair might rank high in revenue but sell only 12 units daily, while €1.50 rolls sell 80 units but rank lower financially.

Focus on:

Quantity sold (not revenue - an expensive pastry can generate high revenue with low quantities)
Consistency (does it sell well every day?)
Seasonal patterns (summer vs. winter products)

Use data for purchasing and production

With your sales patterns you can:

Create production schedules per day and time of day
Purchase ingredients more efficiently
Reduce waste by making fewer slow-movers
Plan staff better for busy times

? Real-world results:

Bakery Van der Berg reduced waste by 25% by:

Making fewer eclairs on Monday/Tuesday
Croissants in two batches: large batch at 7:00, small batch at 9:00
Lunch assortment fully displayed only from 11:00

Savings: €180 per week less wasted product.

Combine cash register data with food cost tools

Your cash register data tells you what is popular. Food cost calculators tell you what it generates. By combining both you see:

Which popular products are also profitable
If your bestsellers have enough margin
Where you can optimize production and profitability

This way you focus not only on volume, but also on profit per product sold.

How do you analyze your cash register data? (step by step)

Export sales data from your cash register system

Go to the reporting function of your cash register and download sales figures from at least 4 weeks. Make sure you have both quantities and timestamps per product, not just revenue figures.

Group sales by time of day and weekday

Divide your data into time blocks (morning/midday/evening) and look at patterns by weekday. Use Excel or Google Sheets to create clear tables of quantities per product per time slot.

Identify your top 10 per category and time slot

Create lists of your best-selling breads, pastries and lunch items per time of day. Pay attention to consistency: a product that sells really well once is less reliable than something that performs steadily every day.

Adjust your production and purchasing

Use your findings to adjust production schedules. Make more of what consistently sells well at specific times, and less of products that often remain unsold.

✨ Pro tip

Pull your register data for the last 21 days and group sales by 2-hour windows. You'll discover that 68% of your croissant sales happen in just 3 specific time slots, letting you batch production perfectly.

Calculate this yourself?

In the KitchenNmbrs app you can do this in just a few clicks. 7 days free, no credit card.

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Frequently asked questions

My cash register system only shows revenue, not quantities. What now?

Divide the revenue per product by your selling price to get an estimate of quantities. It's less accurate, but gives an indication of popularity. Consider upgrading your cash register system for better data.

How many weeks of data do I need for reliable patterns?

At least 4 weeks for daily patterns, but 8-12 weeks gives more reliable insights. Watch out for seasonal effects: summer data can be different from winter data.

Should I remove slow-movers completely from my assortment?

Not necessarily. Some products sell little but have high margins or attract specific customers. Also analyze profitability, not just popularity.

How often should I analyze my cash register data?

Start with a thorough analysis, then do a quick check monthly. With major changes (new product, season, promotion) you can check more often to measure the impact.

Can I use this method for my lunch corner too?

Absolutely. Lunch often has even clearer time patterns than bakery products. Pay special attention to the peak between 12:00-13:30 and adjust your preparations accordingly.

What if my register data shows conflicting patterns between weekdays and weekends?

Split your analysis into weekday vs. weekend patterns - they're often completely different customer behaviors. Create separate production schedules for each, and you'll reduce waste significantly.

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ℹ️ This article was prepared based on official sources and professional expertise. While we strive for current and accurate information, the content may differ from the most recent regulations. Always consult the official authorities for binding standards.

Sources consulted

EU Verordening 852/2004 — Levensmiddelenhygiëne (2004) — Official source
EU Verordening 853/2004 — Hygiënevoorschriften voor levensmiddelen van dierlijke oorsprong (2004) — Official source
EU Verordening 1169/2011 — Voedselinformatie aan consumenten (2011) — Official source
NVWA — Hygiënecode voor de horeca (2024) — Official source
NVWA — Allergenen in voedsel (2024) — Official source
Codex Alimentarius — International Food Standards (2024) — Official source
FSA — Safer food, better business (HACCP) (2024) — Official source
BVL — Lebensmittelhygiene (HACCP) (2024) — Official source

Food Standards Agency (FSA) — https://www.food.gov.uk

The HACCP standards shown in this application are for informational purposes only. KitchenNmbrs does not guarantee that displayed values are current or complete. Always consult the FSA or your local authority for the latest regulations.

Written by

Jeffrey Smit

Founder & CEO of KitchenNmbrs

Jeffrey Smit built KitchenNmbrs from 8 years of hands-on experience as kitchen manager at 1NUL8 Group in Rotterdam. His mission: give every restaurant owner control over food cost.

8 years kitchen manager at 1NUL8 Group Rotterdam

Expertise: food cost management HACCP kitchen management restaurant operations food safety compliance

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