Menu engineering paired with customer feedback analysis reveals which dishes generate maximum revenue and shows exactly how to boost their profitability. Sales data tells you what's happening, while customer insights explain why. Together, they create a roadmap for optimizing margins across your entire menu.
The basics: menu engineering matrix
Menu engineering sorts 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 show what's happening. Customer feedback reveals why:
- Why isn't a dish popular? Too expensive, confusing description, poor presentation?
- Why is a dish popular? Generous portions, unique flavor, excellent value?
- What would increase orders? Different cooking method, better garnish, adjusted seasoning?
⚠️ Important:
Collect feedback systematically through reviews, direct conversations, or brief surveys. Random comments create a distorted picture.
Margin calculation per feedback category
Merge your menu engineering data with feedback to calculate margin impact:
💡 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
Customer feedback lets you calculate different adjustments:
Scenario 1: Increase portion size (address feedback)
- Ingredient costs rise to €6.80
- Margin per portion drops to €8.34
- But sales jump to 140 portions (40% increase from 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 incorporating feedback elements
- Higher ingredient costs but potentially higher price too
- Calculate what's realistic for your market
I've seen restaurants ignore feedback on popular dishes, and it's a mistake that costs the average restaurant EUR 200-400 per month in lost margin opportunities.
💡 Formula for scenario comparison:
Impact on total margin = (New margin per portion × New volume) - (Current margin per portion × Current volume)
Apply this formula to each feedback-based scenario.
Integrating feedback into menu engineering
Make customer feedback an additional 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 boost margin without losing popularity?
- Puzzles: What's stopping customers? Price, description, presentation?
- Dogs: Is there hope through adjustments, or should they disappear?
Practical implementation
Here's how to implement this system:
Monthly: Analyze sales figures and collect feedback from the past month. Spot patterns and opportunities.
Per quarter: Calculate scenarios for dishes receiving feedback. Test one adjustment at a time to measure results.
Annually: Major menu revision based on accumulated data and feedback.
⚠️ Important:
Always test changes on a limited scale. Don't overhaul 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
Focus on your top 5 selling dishes and analyze their feedback patterns over the past 8 weeks. These dishes represent 65-75% of your total food revenue, so optimizing them delivers maximum margin impact with minimal menu disruption.
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'. Focus on actionable feedback rather than vague comments.
What if feedback contradicts my sales figures?
Look at the source and volume of feedback. Negative feedback is often louder than positive experiences. If a dish sells well despite criticism, the criticism might come from a vocal minority.
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 evolving, so your data needs to stay current.
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.
Should I weight feedback from repeat customers differently than one-time diners?
Absolutely. Repeat customers understand your menu better and their feedback often reflects long-term trends. However, don't ignore new customer perspectives as they reveal first-impression issues you might miss.
📚 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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