Menu engineering combines sales figures with profitability to optimize your menu. But customer feedback tells you why dishes are or aren't popular. By combining both, you calculate not only which dishes generate the most revenue, but also how to make them even more profitable.
The basics: menu engineering matrix
Menu engineering divides your dishes into 4 categories based on popularity and profitability:
- Stars: Popular and profitable (promote)
- Plowhorses: Popular but not profitable (raise price or lower costs)
- Puzzles: Profitable but not popular (improve marketing)
- Dogs: Not popular and not profitable (remove from menu)
💡 Example matrix:
Restaurant with 8 main courses, data from 3 months:
- Steak: 35% of sales, 42% margin → Star
- Pasta: 25% of sales, 28% margin → Plowhorse
- Duck breast: 8% of sales, 48% margin → Puzzle
- Chicken: 12% of sales, 22% margin → Dog
Adding customer feedback to the mix
Sales figures tell you what's happening, but not why. Customer feedback provides context:
- Why isn't a dish popular? Too expensive, unclear description, poor presentation?
- Why is a dish popular? Large portions, unique flavor, good value for money?
- What would make customers order more? Different cooking method, different garnish?
⚠️ Important:
Collect feedback systematically through reviews, direct conversations, or short surveys. Random comments give a skewed picture.
Margin calculation per feedback category
Combine your menu engineering data with feedback to calculate the impact on margin:
💡 Example: Pasta (Plowhorse):
Current situation:
- Sales: 100 portions/month
- Selling price: €16.50 (€15.14 excl. VAT)
- Ingredient costs: €5.20
- Margin per portion: €9.94
- Total monthly margin: €994
Feedback: "Portions are too small for the price"
Calculate three scenarios
With customer feedback, you can calculate different adjustments:
Scenario 1: Increase portion size (implement feedback)
- Ingredient costs rise to €6.80
- Margin per portion drops to €8.34
- But sales increase to 140 portions (40% more due to satisfaction)
- New monthly margin: €1,168 (+17%)
Scenario 2: Raise price
- New price: €18.50 (€16.97 excl. VAT)
- Margin per portion: €11.77
- Sales drop to 85 portions (-15% due to price increase)
- New monthly margin: €1,000 (+1%)
Scenario 3: Replace the dish
- New pasta with feedback elements
- Higher ingredient costs but potentially higher price too
- Calculate what's realistic
💡 Formula for scenario comparison:
Impact on total margin = (New margin per portion × New volume) - (Current margin per portion × Current volume)
Use this formula for each feedback-based scenario.
Integrating feedback into menu engineering
Make customer feedback an extra dimension in your analysis:
- Stars: What makes them so successful? Copy elements to other dishes
- Plowhorses: Why are they popular despite low margin? Can you raise the margin without losing popularity?
- Puzzles: What's holding customers back? Price, description, presentation?
- Dogs: Is there still hope through adjustments, or should they go?
Practical implementation
Here's how to implement this in your restaurant:
Monthly: Analyze sales figures and collect feedback from the past month. Identify patterns and opportunities.
Per quarter: Calculate scenarios for dishes receiving feedback. Test one adjustment at a time to measure the effect.
Annually: Major menu revision based on accumulated data and feedback.
⚠️ Important:
Always test changes on a limited basis. Don't change your entire menu at once, or you won't know what works and what doesn't.
A system like KitchenNmbrs helps you automatically track food costs and margins, so you can quickly calculate scenarios without manual calculations.
How do you combine menu engineering with customer feedback? (step by step)
Gather your menu engineering data
Determine for each dish the popularity (% of total sales) and profitability (margin per portion). Place them in the matrix: Stars, Plowhorses, Puzzles, or Dogs.
Categorize customer feedback per dish
Collect feedback from reviews, conversations, and observations. Group by dish: what customers like, what they don't, and what would make them order more?
Calculate scenarios for adjustments
For each dish with lots of feedback: calculate what adjustments mean for costs, price, and expected sales. Compare the total margin impact of different options.
Test one change at a time
Implement the most promising adjustment and measure the effect over 4-6 weeks. Only this way will you know if your calculation is correct in practice.
✨ Pro tip
Start with your 3 best-selling dishes. If you optimize those based on feedback, you've already captured 60-70% of your menu impact without overwhelming amounts of 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 do I collect reliable customer feedback about my dishes?
Combine different sources: online reviews, direct conversations with guests, and observation of what comes back on plates. Ask specifically about dishes, not generally about 'the food'.
What if feedback contradicts my sales figures?
Look at the source. Negative feedback is often louder than positive experiences. If a dish sells well despite criticism, the criticism might come from a small group.
How often should I update my menu engineering analysis?
Monthly for the figures, quarterly for thorough analysis with feedback. Your menu and customers are constantly changing, so your data needs to stay up-to-date.
Can I use this method for beverages and desserts too?
Yes, the same principles apply. Just note that beverages have different margins (pour cost 18-25%) and desserts are often impulse purchases that receive less feedback.
What if a Star dish suddenly receives negative feedback?
Investigate immediately what has changed: ingredients, preparation, presentation, or staff. Stars are your goldmine, so solving problems quickly prevents revenue loss.
📚 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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