Case Study – Optimizing a Burger Restaurant Menu with MaxDiff
Case Study – Optimizing a Burger Restaurant Menu with MaxDiff
The challenge
A burger restaurant wanted to redesign its menu to maximize customer satisfaction and average ticket value. With too many formulas, some underperformed while kitchen complexity increased. Which combos should stay, which should be removed, and what price points work best?
The solution
A MaxDiff study tested 12 menu formulas — each with a specific price — across all customers and the key lunch segment. The results reveal which combos drive the most preference and where to focus the menu.
Study impact: After menu optimization based on MaxDiff results, the restaurant increased its average ticket by +15% and reduced food waste by 20% by eliminating low-demand combos.
ℹ️About the real study behind this case
This case study was derived from a real study conducted by MaxDiffPro. It has been anonymized for confidentiality: the tested options and results shown here do not correspond exactly to reality. The actual study had the following characteristics:
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Country
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Items tested
18
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Respondents
~340
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Timeline
5–7 days
The timeline depends on the complexity of the study and the target audience.
Popularity Ranking of Menu Formulas
Bubble Chart – Perception Map
ⓘ Understanding this chartThis chart shows how menu formulas relate to each other in customers' minds. Bubble size represents overall preference. Items close together are perceived as similar and may substitute each other. Items further apart tend to be complementary.
Bubbles combine preference strength (size) and strategic positioning (x/y) to identify formulas that are both popular and complementary on the menu.
Product Mix Report – Recommended Menu Portfolio
ⓘ How to read this chartThis chart identifies the optimal combination of menu formulas. The first item is the most preferred individually. Each additional formula is selected because it adds the highest incremental preference when combined with the previous ones. Bars show the incremental contribution of each formula, while the line represents the cumulative preference generated by the mix.
Recommended core menu: Classic Burger, BBQ Bacon, Veggie and Swiss Raclette formulas cover the widest range of customer preferences with minimal overlap.
Business impact
By streamlining the menu to focus on high-preference formulas, the restaurant improved kitchen efficiency, reduced waste, and increased the average ticket value.
Average ticket
+15%
Food waste reduction
-20%
Customer satisfaction
+18%
Run a Similar Study for Your Product
MaxDiff helps teams identify which messages, features, or ideas truly resonate with customers.
Typical study: 15–25 items tested · 150–300 respondents · Results in 3–5 days
