🔮 rest-revenue

Menu Engineering

Menu Engineering classifies every dish into one of four classic quadrants — Star, Puzzle, Plow Horse or Dog — by comparing its popularity (quantity sold) and profitability (contribution margin %) against your menu's own averages, so you know exactly which dishes to promote, reprice, reposition, or reconsider.

📍 Menu path: Revenue & Pricing → Menu Engineering

👤 Who uses it: All roles with the Reports feature enabled

Overview

This uses the standard menu-engineering model: Popularity is quantity sold versus the average quantity sold across all items; Profitability is contribution margin % versus the average margin % across all items — both averages computed from your own menu, not an external benchmark.

The four quadrants: Star (high popularity + high profit → promote prominently, feature on the menu, train staff to upsell), Plow Horse (high popularity + low profit → raise price slightly or reduce portion cost), Puzzle (low popularity + high profit → rename, reposition or bundle since guests aren't finding it), and Dog (low popularity + low profit → consider removing, revamping, or making a limited special).

Every classified item shows its quantity sold, revenue, cost, margin and margin % for the selected date range, alongside its assigned quadrant and a one-line recommended action.

Because both thresholds (average quantity, average margin %) are computed from your own current menu and date range, the same dish can shift quadrants between periods as sales patterns and costs change — this is a snapshot, not a permanent label.

A date-range filter controls which sales window feeds the analysis, so you can compare, for example, last month's classification against this month's.

Before You Start

You must have the Reports feature enabled on your plan.
Products need accurate cost data (recipe/ingredient costing) for the margin % figures to be meaningful — a dish with no cost data set will skew its own margin calculation and potentially the averages.
Enough sales history in the selected date range is needed for the popularity comparison to be meaningful — a very short or quiet window can misclassify normally-strong items as low popularity.

Step-by-Step Guide

1 Run a menu engineering review

Open Menu Engineering and set the date range you want to analyse (e.g. the last full month).
Review the four quadrant groups — Star, Puzzle, Plow Horse, Dog.
For each Star, note it as a promotion candidate; for each Dog, consider whether to revamp, reprice, or drop it from the menu.

2 Fix underpriced popular items (Plow Horses)

Open the Plow Horse group — these are dishes guests order a lot but that carry thin margins.
For each one, either raise its price slightly or work with the kitchen to reduce its portion cost.
Re-run the analysis in a later period to confirm the change moved it toward Star.

3 Rescue high-margin items nobody orders (Puzzles)

Open the Puzzle group — these dishes are profitable per order but rarely chosen.
Consider renaming them, repositioning them higher on the menu, or bundling them into a combo to increase visibility.

Every Field & Button, Explained

Field / Button	What it does
`Star / Puzzle / Plow Horse / Dog`	The four classification quadrants, each with a recommended action shown directly on the matrix.
`Quantity Sold`	Units of that dish sold in the selected date range; compared against the average across all items to determine popularity.
`Margin %`	Contribution margin percentage (revenue minus cost, as a percentage) for that dish; compared against the average margin % across all items to determine profitability.
`Recommended action`	A one-line strategy per quadrant — Promote prominently (Star), Raise price/reduce cost (Plow Horse), Rename/reposition/bundle (Puzzle), Consider removing/revamping (Dog).
`Date range filter`	Controls which sales window feeds both the popularity and profitability calculations for every item.

Tips & Best Practices

Make sure every active menu item has accurate cost data before relying on this matrix — a dish with missing or wrong cost data can land in the wrong quadrant and mislead your pricing decisions.
Re-run the analysis periodically (e.g. monthly) rather than treating a classification as permanent — quadrants shift as ingredient costs, seasonal demand and pricing change.
Start with your Dogs and Plow Horses when time is limited — those two quadrants usually offer the clearest quick wins (drop/revamp vs. reprice).

Troubleshooting & FAQ

A dish I know sells well shows up as low popularity.

Popularity is relative to the average quantity sold across all items in the exact date range selected — check that the range is representative (not an unusually quiet period) and that the item wasn't 86'd or off-menu for part of it.

Margin % looks wrong for an item.

Margin is calculated from that product's cost data — verify the item has an accurate recipe/ingredient cost set; a missing or stale cost figure will distort its margin % and its resulting quadrant.

The same dish landed in a different quadrant than last month.

This is expected — both thresholds are recomputed from your own menu's current averages each time you change the date range, so shifts in sales mix or costs between periods can move a dish between quadrants.