Analysing Customer Purchase Patterns

LINK TO GITHUB:

https://github.com/franklintheanalyst1/franklintheanalyst1/blob/main/Customer%20purchase%20records.xlsx

TOOL USED:

EXCEL

SOURCE ATTRIBUTION:

Gabriel James( Data analyst Tutor @ DataAfrik/LightHall)

INTRODUCTION:

The analysis of this customer purchase records dataset aims to extract business insights to understand the performance of the best and worst customers, best and worst delivery agents, top 10 products etc.

BACKGROUND & MOTIVATION

This was my first excel project in 2023 and as a data analyst. Kudos to my tutor @ Gabriel James who taught us well during the bootcamp. I was excited to take on this project and can't wait to show you all the business insights I extracted.

DATASET COLLECTION

The dataset collected contained different variables like customer name, date/time, outlet type, producer, product, category, quantity, unit price, shipping status, delivery agent, state, country, currency, sales channels.

DATASET LIMITATION

1. Removing unnecessary columns

2. Converting all currency denomination to USD

3. Calculating the total sales.

4. Classifying order quantities to low end, mid-end and high end

ANALYSIS

This is the raw dataset of the customer purchase records dataset.

After cleaning the data by :

• Removing duplicates

• Removing unnecessary columns

• Converting all currency denomination to USD

• Calculating the total sales.

• Classifying order quantities to low end, mid-end and high end

Here's a sample of the cleaned data

RESULTS

9 business questions were asked and answered using PIVOT TABLE

Create a chart to show the 10 least loyal customers

What percentage of sales come from each outlet type?

What producers account for the 5 lowest sales figure?

Average order quantity per category group

Make a chart showing the shipping status by outlet type

Show the 10 worst performing delivery agents

Most popular states by sales channel

10 VIP customers

Percentage of sales volume by sales channel and country

CONCLUSION

With all the above business insights, the owner or stakeholders of the business can make informed decisions from the customer purchase records dataset.

REFERENCES

1. Data Science for Business" by Foster Provost and Tom Fawcett

   - This book provides insights into how data can be used in business contexts, including customer purchase data analysis.

   - [Link to Book](https://www.oreilly.com/library/view/data-science-for/9781449374273/)