SalesPulse: Dynamics & Patterns (XMAS Sales Analysis)

Tools used in this project
SalesPulse: Dynamics & Patterns (XMAS Sales Analysis)


About this project


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. Here I'm helping a retailer navigate through.

The mission is to utilize the data analysis expertise to uncover hidden trends and patterns within the dataset.

About the Dataset:

A comprehensive dataset of anonymized Christmas sales data spanning various product categories, customer demographics, and marketing campaigns. Data provided as part of the FP20 Analytics Data Challenge.

Tools Used:

Excel (Data Cleaning)

Tableau (Data Visualization)


Since Europe is mentioned, assuming the Currency to be in EUR.

I have split the time into “Morning, Afternoon, Evening, and Night” for better clarity.

Dashboard Brief:

The dashboard should be able to answer the below 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?
  1. 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.
  1. 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.
  1. 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.

Insights & Analysis:

  • "Sweden" records the highest sales in history, followed by "Netherlands" and "Germany". On digging deep, it is the same trend for "In-store" sales. For Xmas market Sales, "Belgium" tops the list followed by "Italy". And for "Online" sales, "Netherlands" records the highest sales.
  • In the digital era, it is pleasantly surprising to see "In-store" and "Cash" purchases being the most preferred Purchase type so far. However, it might be because people prefer a personal touch for Xmas gifts and hence the Store visits. Also, since the Children category records the highest sales, maybe children prefer to check their collection in person.
  • The Children Category records the highest Sales, followed by teens. However, there are no major Sales differences among teens and Adults. Also, on comparing the Gender, both Males and Females recorded almost the same Sales figures with a minimal difference.
  • The Sales saw an Upward trend since the start, but there was a dip in 2020 following the global lockdown due to the Pandemic. The Sales did see an upward trend the following year, but it is yet to rebound to the pre-COVID sales figures.
  • The Most Popular Product Category is "TOYS" followed by "CLOTHING". With a record sale for "Barbie Doll", it sure seems like the trend will continue in the upcoming year as well. For the Adult segment, the "Dolce Gusto Coffee Machine" and "Ray Ban Sunglasses" seem popular. The "JBL Headphones" is the most popular ones among teens.
  • December's festive peak propels sales to yearly highs, while January shows a sharp contrast, reflecting the afterglow of holiday shopping and the stark impact of January's slowdown.
  • Sales trend during different parts of the day where Customers are inclined towards shopping at the Start of the day rather than at Night.
  • Price vs Sales Volume: "As product prices increase, sales volumes tend to decrease, with Toys and Video Games showing a resilient demand even at higher price points."
  • Profitability by Price Point: “While there is a general increase in profit with higher unit prices across product categories, some categories like Technology and Video Games achieve substantial profits at higher price points, indicating a potential market tolerance for premium pricing”.

Business Suggestions (Actionable Insights):

  • Launch exclusive early bird promotions in November to capitalize on pre-holiday shopping momentum.
  • Offer a special discount to first-time customers to encourage brand loyalty.
  • Create time-sensitive deals on bestselling items to create urgency and boost turnover.
  • Expand the toy selection with a range of affordable options to cater to budget-conscious shoppers.
  • Implement in-store-only specials to increase foot traffic and sales further.
  • To incentivize non-cash payments, introduce a cashback program for credit/debit card transactions.
  • To leverage the sales potential beyond peak hours, roll out evening and night-time specials to attract late shoppers.

Conclusion (Personal Experience):

Working on this project taught me a plethora of valuable lessons. It was tough to decide on what to present in the dashboard as I had to focus on the important stuff and not get carried away by unnecessary details. Typically, I present my insights as a document, but this time, I decided to try something new by using Canva for presentation. It was my maiden attempt, and I'm well aware that there's room for improvement, which I'm excited to explore. Moreover, I've previously incorporated stories into each chart within the dashboard, but this time, I embedded them in the presentation as a narrative. Presenting the story in this format has been a different experience - all part of the challenge!

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