This project inspired from a Linked In community member Anh Leimer , who took part in a coding competition and won it with this dashboard.
The dataset was provided on her Github repository.
Dataset was pretty clean and to cover up with the missing dates, a list of dates have been generated using M code in Power Query.
Since, November , December and January are considered the peak time for Christmas sales
so a separated conditional column is added to show the Xmas Seasons for each year .
1: Purpose: This dashboard provides insights into customer segments, shopping behavior, and regional performance during the holiday season.
2: Metrics and KPIs:
Key Metrics: Total Sales, Quantity Sold, and Profit for the Latest Season, including year-over-year (YoY) growth comparisons.
Customer Segmentation: Visualizes which customer age group and gender drove the most sales, with segmented pie charts.
Shopping Channels: Indicates customer preferences for in-store, online, and Xmas market shopping channels.
Top Countries: A bar chart ranks countries by sales, showing where the highest revenue was generated.
3: Key Insights:
Customer Preferences: Customers aged 18 and over were the primary segment driving sales.
Regional Success: Countries like Sweden, the Netherlands, and Germany led in sales, providing a clear target for potential marketing efforts.
1. Dashboard Focus: Pricing and promotional effectiveness on sales quantity and unit pricing.
2. Metrics and KPIs:
Price Impact: Scatter plots show the relationship between average unit price and quantity sold across different customer demographics (Adult, Children, Teen).
Quantity Sold by Channel and Month: Visualizes trends in quantity sold by channel, and highlights high-demand months.
Customer Gender & Time Analysis: Heatmaps illustrate shopping patterns based on gender, day of the week, and time of day.
3. Key Insights:
Promotional Timing: Higher sales volumes in December, with a mix of in-store and online shopping.
Gender & Time Trends: Notable concentration of shopping activity during morning hours, helping in planning promotional timings.