Product Architecture

Two layers of menu intelligence.

We format transactional POS records to highlight exactly which menu items deserve attention next.

Engine 01

Sales Popularity Engine

Analyzes sales volume and mix percentage for every product on your menu. Items are dynamically classified into Stars, Plowhorses, Puzzles, and Dogs based on statistical baselines of popularity.

Classification Example:

“House Margarita classified as Star (high popularity). Chicken Wings flagged with sales volume drift (sales velocity decreased 12% recently).”

Live Classification Matrix

★ Stars (High Popularity)18 items
Plowhorses (High Volume)14 items
Engine 02

Menu Review Support

Consolidates sales trends into a short, evidence-backed list of items to examine. Once updates are implemented, track sales volume over the following weeks to see how your changes performed.

Outcome Tracking:

“Reviewing menu change outcome: tracking sales velocity and transaction volume over 30 days to verify stable demand.”

RevenArc Menu Review and Outcome Tracking
Onboarding Timeline

Onboard with supported POS.

No developers required. No complex APIs to build.

1

Connect POS

Connect Square directly (or drop a POS CSV export). We format transaction history once data finishes loading.

2

Passive Pull

RevenArc parses your historical transactions and imports available POS sales records.

3

Matrix Ready When Loaded

Your full matrix is ready once supported venue data finishes loading and validation completes.