Before you label any dish a “star” or a “dog,” you need two clean numbers: how often it sells and how much it truly contributes after direct costs. When popularity and profitability are calculated consistently, the menu engineering matrix becomes a practical decision tool instead of a guessing game.
The goal is simple: measure sales mix (popularity) and contribution margin (profitability) using the same time period, the same item definitions, and the same cost rules for every item. That consistency is what makes the classifications meaningful.
Popularity in menu engineering is typically measured by how often each item sells compared to the rest of the menu in the same category. This is commonly expressed as a sales mix percentage.
In most restaurants, popularity is judged within a category because comparing a main course to a side dish (or a cocktail to a coffee) can distort the results.
A widely used rule of thumb is to treat “above average” popularity as anything at or above the category average. Some operators apply a small adjustment factor to avoid labeling too many items as popular, but the key is to apply the same rule across the category every time.
Profitability for the matrix is typically based on contribution margin (sometimes called gross profit per item): the selling price minus the direct cost to produce that item. Food cost percentage can be useful for monitoring, but it can mislead when used as the main profitability measure.
To keep it fair, base your costs on standard recipes and portion sizes. If the kitchen plates “by eye,” you’ll get numbers that look precise but don’t reflect reality.
Most operators get inconsistent results because items are not defined the same way in sales data and costing. Decide your rules once, then apply them across the board.
For bars and cafés, the same principle applies. Your direct costs are the pour cost and standard garnish for a cocktail, or the coffee dose, milk portion, and cup/lid for takeaway drinks.
A practical workflow used in many restaurants is to run menu engineering as a repeatable monthly or quarterly routine, not a one-time project. It usually looks like this:
When this cycle is repeated, you’ll spot patterns quickly: items that sell well but need cost control, items with strong margins that need better visibility, and items that are draining space.
Say your burger category sold 1,000 units in 6 weeks. The Classic Burger sold 220 units, so its sales mix is 22%. If your category has 8 burgers, the average sales mix is 12.5%, so the Classic is above average on popularity. If it sells for 14 and costs 5.20, its contribution margin is 8.80. Compare 8.80 to the average burger contribution margin to decide if it’s above or below average on profitability.
If an Iced Latte is ordered constantly but your milk portion is inconsistent, the calculated margin will be unreliable. Standardize the recipe first (espresso dose, milk volume, cup size), then recost. Only after that should you classify it, because the matrix will otherwise point you to the wrong fix.
A signature cocktail may look profitable on paper, but if it’s often sold during a standing happy hour discount, its effective selling price is lower. Use the typical selling price customers actually pay during the analysis period, not the full menu price, or you will overstate profitability.
Digital menu and management systems can reduce the “messy data” problem by helping keep item names, variants, and availability consistent across locations and menus. For example, a platform like Menuviel can support cleaner item management by keeping one item record with standardized options and visibility rules, which makes it easier to compare performance over time without duplicate or mismatched items.