Objective

The festive season is upon us, and the holiday gifts market is gearing up for its most significant sales period of the year. However, navigating the holiday rush and maximizing profits can be daunting. That's where I come in!

I will give valuable insights into customer behavior during the Christmas season and provide by using a comprehensive dataset of anonymized Christmas sales data spanning various product categories, customer demographics, and marketing campaigns.

The Dashboard should be able to answer these questions:

1. Predict future sales:

• What could be the most popular Xmas sale products in the upcoming year?
• Which country had the most Xmas sales in history?
• Which purchase type would be the trend based on historical data?

2. Identify customer segments:

• Based on purchase history and demographics, which customer segments could drive the Xmas sales most?
• For each customer segment, what was their favorite Xmas purchase item?
• Recommend strategies for customer acquisition and retention based on segment insights.

3. Identify potential promotional opportunities (Optional):

• Analyze historical sales data and promotional activity to identify effective discount strategies and promotional offers.
• Recommend the optimal timing and duration of promotions for various product categories and customer segments.
• Predict the impact of different promotional strategies on sales performance.

4. Develop a data-driven approach to pricing:

• Analyze the relationship between product price, sales volume, and customer behavior.
• Develop dynamic pricing strategies to optimize profits and maintain market competitiveness.
• Recommend pricing adjustments for individual products based on demand and market trends.

Data Set

The provided data contains:

• An Excel file with all the Data
• Data were taken from FP20 Christmas Trend Challenge

BUILDING THE DASHBOARD

Following the objective, I wanted to create a Summary dashboard focused on Revenue where you can:

• Filter by Customer Age Ranges
• By Gender
• By Years
• By Product Names

I wanted to see if there is a difference between the years. And I created a table containing each Xmas and the Products Sold to calculate the Increase from 2018 to 2021. This allowed me to find out the most trending product.

I also added Scatterplots to identify the Avg Unit Prices and Quantity bought depending on the Christmas budget. Ans a scatterplot that shows how the sold Units correlate with the Avg. Unit Prices. This should give me a feeling if expensive products are sold less and show me the distribution of the Unit Prices.

Design & Visualization

The design is a typical dashboard design, that can be used to get a feeling for what’s going on. So an exploratory one in Christmas Style- As I used a Christmas Theme in Background I also decided to go with Red and Green in the Dashboard- What I usually try to avoid, but this time it fits perfectly to the design.

Definition of technical Terms

• Revenue = Sum of total Sales
• Profit = Total Sales minus the Costs
• Unit Price = Price for which the product is sold
• Sales Volume = Quantity Sold

Used KPIs

• Revenue
• Avg Unit Price
• Avg Units sold per Customer
• Quantity Sold = Sales Volume
• Increase = Change Christmas 2021 to Christmas 2018
• Percentage of Revenue per Product
• Percentage of Profit per Product

INSIGHTS

The Insights I gained are summed up in the additional pictures. Please find them below.

SUMMARY, PERSONAL LEARNINGS AND CHALLENGES

I wanted to build really focused visualization, that can provide all the information required. This needed a lot of trial and error, because it was not so easy to put that many information in.

Overall, I enjoyed working on it, because it was a real interesting project where I worked with Qlik for the first time.

I hope you also enjoy the project! If you have any feedback – you’re welcome!

Best, Jasmin