Most restaurant owners think they know their customers, but the numbers often reveal a completely different story. Your target audience can shift gradually without you noticing - until you look at the right data patterns. These numerical signals will show you exactly who's really sitting at your tables.
The signals in your revenue patterns
Your target audience determines when, how much, and what your guests order. If this changes, you'll see it directly in your numbers.
💡 Example: From business to casual
Restaurant De Eik saw this shift after corona:
- Average bill: from €45 to €32
- Peak: from Tuesday-Thursday to Friday-Saturday
- Alcohol: from 35% to 18% of revenue
- Desserts: from 60% to 25% of guests
Conclusion: Business guests replaced by families
Average bill value per day
Check your average bill value per day of the week. Large differences point to different target audiences per day.
- Monday-Thursday higher: Lots of business guests
- Weekend much higher: Tourists or special occasions
- Friday-Saturday lower: Younger target audience or families
- All days equal: Fixed local customer base
Alcohol and side dishes ratio
The percentage of your revenue that goes to alcohol and side dishes reveals a lot about your guests. From tracking this across dozens of restaurants, I've seen clear patterns emerge.
💡 Example: Alcohol percentage analysis
Different target audiences, different percentages:
- Business lunch: 15-25% alcohol
- Date night: 30-40% alcohol
- Families with children: 8-15% alcohol
- Young adults (18-25): 35-50% alcohol
Calculate it this way: (Alcohol revenue / Total revenue) × 100
Order times and length of stay
Arrival patterns and dining duration show their lifestyle and needs.
- 12:00-13:30 peak: Business lunch crowd
- 17:30-19:00 peak: Families with children
- 20:00-21:30 peak: Couples and friends
- After 21:30 still busy: Younger target audience
⚠️ Note:
Seasons affect patterns. Always compare the same months from last year, not last month.
Dish popularity shifts
Menu preferences tell you exactly who's sitting at your tables.
💡 Example: Dish analysis
Bistro Het Plein saw this shift:
- Carpaccio: from 15% to 6% of orders
- Burger: from 8% to 22% of orders
- Fish of the day: from 12% to 4%
- Kids menu: from 2% to 18%
Signal: From upscale to family dining
Payment behavior patterns
How your guests pay gives insight into their profile and comfort level.
- Lots of cash: Older target audience or tourists
- Contactless >90%: Younger, tech-savvy guests
- Many split bills: Friend groups
- Few split bills: Couples or business
Reservation patterns
Booking behavior shows their planning style and flexibility.
💡 Example: Reservation analysis
Different patterns per target audience:
- Business: 2-5 days ahead, weekdays
- Families: 1-2 days ahead, weekends
- Young adults: Same day or walk-ins
- Seniors: 1-2 weeks ahead, fixed times
What to do with these insights
If you see signals that your target audience is changing, adjust your strategy:
- Adjust menu: More/fewer luxury options
- Reconsider prices: Does it match your new target audience?
- Service level: More formal or more casual
- Marketing channels: Where do you reach your new guests?
A system like KitchenNmbrs helps you track these patterns automatically, so you notice trends faster than if you had to calculate everything manually.
How do you analyze your numbers for target audience changes?
Gather data from the past 6 months
Pull your revenue figures per day, including number of guests, average bill value, and most popular dishes. Compare this with the same period last year to rule out seasonal influences.
Calculate ratios per day of the week
Break down your weekly revenue by day and calculate percentages. Also check alcohol percentage per day: (alcohol revenue / total revenue) × 100. Large differences point to different target audiences.
Analyze dish popularity trends
Create a top 10 of your most ordered dishes now vs. 6 months ago. Shifts from luxury to casual (or vice versa) show your target audience change most clearly.
✨ Pro tip
Track your no-show percentage over a 6-week period by day of the week. Business guests rarely no-show (under 5%), while young adults average 15-20% no-shows. This metric provides an additional confirmation of audience shifts you might be seeing in other data.
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
How often should I analyze my target audience data?
Review these patterns every 3 months for meaningful trends. Monthly checks won't show significant changes, but quarterly analysis reveals real shifts. After major events like renovations or menu changes, check sooner.
What if my numbers give conflicting signals?
You likely serve multiple target audiences on different days or times. Break down your analysis by day of the week - weekday guests often differ dramatically from weekend customers.
My average bill is dropping but revenue is rising. What's happening?
You're attracting more guests who spend less per person. This typically signals a shift toward a broader, more price-conscious audience. Verify that your dishes remain profitable at these lower check averages.
Which metrics matter most for audience identification?
Focus on three key indicators: average bill by day of the week, alcohol percentage of total revenue, and your top 5 dish sales. These three data points paint a clear picture of your customer base.
How can I distinguish temporary trends from permanent shifts?
Examine at least 3 months of data for reliable patterns. Temporary fluctuations from weather, holidays, or local events usually mirror the same period last year. Permanent changes persist across multiple quarters.
Should I completely overhaul my menu if my audience changes?
Make gradual adjustments rather than dramatic changes. Test 2-3 new dishes that appeal to your emerging audience first. Monitor their performance before making wholesale menu modifications.
📚 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
- Warenwetbesluit Bereiding en behandeling van levensmiddelen (2024) — Official source
- WHO — Foodborne diseases estimates (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.
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