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Coffee Shop Sales Analysis

Coffee Sales Dashboard

Table of Contents


Project Background

Maven Roasters is a fictitious coffee shop operating across three locations in New York City. Transaction records spanning multiple months were analysed to identify revenue trends, peak performance windows, and product preferences across locations.

Data Structure

The dataset consists of a single table with 149,115 records covering transaction-level sales data across three New York City locations.

Column Description
transaction_id Unique transaction identifier
transaction_date Date of the transaction
transaction_time Time of the transaction
transaction_qty Number of items purchased
store_id Unique store identifier
store_location Store location (e.g. Lower Manhattan, Hell's Kitchen)
product_id Unique product identifier
unit_price Price per unit ($)
product_category High-level category (e.g. Coffee, Tea, Bakery)
product_type Product type within category (e.g. Gourmet Brewed Coffee)
product_detail Specific product name and size

Key Findings

Revenue & Orders

  • $698K total revenue from 149K orders — Average Order Value of $4.69
  • June peaks at $166K — 118% higher than February ($76K), driven by seasonal foot traffic

Location Performance

  • Hell's Kitchen leads at $236K — consistently the top performer across all months
  • All three locations show steady growth, with no significant underperformer

Product Performance

  • Barista Espresso is the top product at $91K — 193% more than the lowest top-10 product (Drip Coffee at $31K)
  • Coffee Beans have the highest AOV at $22 — nearly 5x the overall AOV of $4.69
  • Coffee is the most popular category at $58K in sales; Packaged Chocolate is the weakest at $487

Peak Hours & Days

  • Sales peak at 10 AM with 18K orders — 30x more than the slowest hour (8 PM at 603 orders)
  • No clear peak day — all weekdays average 21K orders consistently

Coffee Preferences

  • Gourmet Brewed Coffee leads with 16K orders (29% of all coffee orders)
  • Premium Brewed Coffee is the least popular at 8K orders (14%)

Dashboard

Coffee Sales Dashboard

Recommendations

  1. Capitalise on Coffee Beans' high AOV — at $22 AOV, a "Buy One Get One" seasonal promotion would encourage bulk purchases, particularly during colder months when home brewing increases
  2. Drive revenue in slow months — January and February are the weakest months; birthday drinks and loyalty reward cards could boost engagement and revenue during the quiet winter period
  3. Optimise late evening hours — 8 PM records only 603 orders vs 18K at peak; end-of-day discounts could convert foot traffic into sales
  4. Rotate underperforming categories — Packaged Chocolate at $487 is significantly behind; replacing or refreshing it with new offerings could generate fresh interest

About

Comprehensive analysis of coffee shop sales utilizing Pandas for data cleaning and exploratory data analysis (EDA), complemented by Streamlit for creating interactive data visualization dashboards.

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