Allan Notes

Coffee Sales Project Documentation

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Allan
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Table of contents

Project Overview

The main objective of this coffee sales project was to understand the basics of Excel, including data cleaning, using XLOOKUP, and visualising data with pivot tables. This project aimed to provide hands-on experience in handling sales data, performing analysis, and generating insights to inform business decisions.

Data Collection

The data for this project was sourced from Twitter, comprising sales data along with customer details. This data included information on sales volume, customer demographics, and product types.

Data Analysis

Tools and Methods

The primary tool used for data analysis was Excel. The data was cleaned and organised using various Excel functions. XLOOKUP was utilised for data matching and retrieval, and pivot tables were employed for data visualisation and analysis.

Key Metrics

The key metrics focused on in this analysis were:

  • Total sales over time

  • Top 5 customers

  • Sales by country

This project was carried out in order to analyse the sales of coffee.

The steps carried out have been carefully documented in this post;

STEP 1:

(order sheet)

(customer sheet)

From the tables above, we can see that the data we need in sheet 1 (the order sheet) is found in the other two sheets (customer and product sheet).

This leads us to perform our first task of finding the missing data using

X-LOOKUP:

IF FUNCTION TO ERADICATE THE 0 SPACE

The complete table:

The sales were obtained by multiplying the unit price by the quantity.

FORMATTING: DATES (CONVERT TO DD,MMM,YYYY) , SIZE (ADDED KG), UNIT PRICE AND SALES ( ADDED DOLLARS)

Findings

Main Findings

From the analysis, it was discovered that the top three customer countries were the USA, Ireland, and the UK. These countries showed the highest sales volumes.

The data revealed that the years 2019 and 2020 experienced high sales, indicating a significant increase in coffee purchases during these periods.

Recommendations

Based on the findings, the following recommendations were made to improve coffee sales:

  1. Targeted Marketing: Focus marketing efforts on the USA, Ireland, and the UK, as these countries have shown the highest sales volumes.

  2. Seasonal Promotions: Given the high sales in 2019 and 2020, it may be beneficial to investigate the specific periods within these years that saw peaks in sales and introduce seasonal promotions or special offers during those times.

  3. Customer Loyalty Programmes: Implement loyalty programmes to retain the top customers and encourage repeat purchases.

Conclusion

Overall Impact

This project provided valuable insights into coffee sales patterns and customer demographics. The hands-on experience with Excel tools and functions enhanced the ability to clean, analyse, and visualise data effectively.

Lessons Learned

  • Understanding and cleaning raw data is crucial for accurate analysis.

  • Excel functions like XLOOKUP and pivot tables are powerful tools for data analysis and visualisation.

  • Identifying key metrics and focusing on them can uncover significant trends and patterns.

Future Steps

  • Further analysis could be conducted to understand the reasons behind the high sales in 2019 and 2020.

  • Additional data sources could be incorporated to provide a more comprehensive view of the sales landscape.

  • The recommendations provided should be implemented and monitored to gauge their effectiveness in improving sales.

This documentation captures the essence and outcomes of the coffee sales project, demonstrating the practical application of Excel in data analysis and decision-making.

excel