Commercial Diagnostics · Real Client

Artisan Bakery — Structural Sales Analysis

01

This is a real client engagement with a confidential artisan bakery. The brief was deliberately open: read the year, surface what matters, and propose levers that work inside the existing system — no price increases, no new customer acquisition, no new SKUs.

The analysis revealed a strikingly concentrated commercial structure: 79% of all transactions contain only 1 or 2 products, and the top 3 products generate ~80% of total revenue. The business is deeply dependent on a small SKU core, and its growth ceiling is not customer count — it is basket size.

A modelled scenario projected that converting just +5% of single-product tickets into two-product tickets would add ~241K in annual revenue (local currency) (≈152 additional tickets per year), without touching prices, marketing spend, or the product range. Product affinity analysis surfaced the natural pairings to anchor that conversion.

Skills & Tools

Python (pandas, EDA), Excel, scenario modelling, market basket analysis

Analysis

Exploratory data analysis, ticket architecture mapping, product concentration (Pareto), revenue vs. volume divergence, product affinity / market basket analysis.

Key insights
  • 79% of transactions contain only 1–2 products — growth lever is inside existing volume, not new customers
  • Top 3 products generate ~80% of total revenue — significant economic dependency on a small SKU core
  • +5% conversion from 1→2 products projected to add ~241K (local currency) annually (≈152 tickets/year)
PythonExcelEDAReal Client
Setting the scene: a full commercial year (2025) of a confidential artisan bakery, read end-to-end to find growth levers inside the existing system — no price hikes, no new customers.
Setting the scene: a full commercial year (2025) of a confidential artisan bakery, read end-to-end to find growth levers inside the existing system — no price hikes, no new customers.
The headline finding: 79% of tickets contain only 1 or 2 products. The growth ceiling isn't customer count — it's basket size.
The headline finding: 79% of tickets contain only 1 or 2 products. The growth ceiling isn't customer count — it's basket size.
Confirmation in value: most tickets cluster in the lowest price brackets. The same picture as quantity — confirming that lifting the average ticket is the highest-leverage move.
Confirmation in value: most tickets cluster in the lowest price brackets. The same picture as quantity — confirming that lifting the average ticket is the highest-leverage move.
Market basket analysis surfaces the natural product pairings — the concrete anchors for a +1 product upsell at the counter, no scripts required.
Market basket analysis surfaces the natural product pairings — the concrete anchors for a +1 product upsell at the counter, no scripts required.
The bottom line: converting just +5% of single-product tickets into two-product tickets projects ~241K in extra annual revenue (≈152 tickets/year) — entirely inside the existing system.
The bottom line: converting just +5% of single-product tickets into two-product tickets projects ~241K in extra annual revenue (≈152 tickets/year) — entirely inside the existing system.
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