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Championing advanced data analysis, I'm crafting a dynamic sales analysis and forecasting solution. From an intuitive KPI dashboard to precise 15-day forecasts using time series analysis, the aim is clear: empower strategic decisions for business growth and operational efficiency.

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alokrrbal/Trendify-Sales-Dashboard

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Trendify-Sales-Dashboard

Problem Statement

The challenge at hand is to use advanced data analysis techniques, particularly time series analysis, to create an impactful sales analysis and forecasting solution. This involves developing an intuitive dashboard with key performance indicators, conducting insightful data analysis to assess current sales strategies, and implementing time series analysis for accurate sales forecasting over the next 15 days. The ultimate goal is to distill these findings into actionable insights and recommendations, facilitating informed and strategic decision-making for the supermarket's growth and enhanced operational efficiency.

Steps followed

  • Data Loading:
    • Loaded the sales data into Power BI for analysis.
  • Data Cleaning:
    • Removed blank values and unnecessary columns.
    • Addressed errors, including replacing #N/A values with 0 for efficient analysis.
  • Average Delivery Date Calculation:
    • Created a new column, "Average Delivery Days," using Power BI DAX queries.

Snap of new calculated column (Average Delivery Days) ,

new column

A card visual was used to represent this Average Delivery Days.

AVG-Delivery date

Report Snapshot (Power BI DESKTOP)

Sales Dashboard -

Dashboard-1

Forecast Dashboard -

Dashboard-2

Insights

Product Performance:

  • Consumer products are the highest selling category, contributing 48% to total sales.
  • Home office products have the lowest sales, accounting for only 19%. Suggested strategies include running targeted campaigns or offering discounts to boost sales in this category.

Regional Contribution:

  • East and West regions contribute the most to sales, with 33% and 29% respectively. Tailoring marketing efforts to these regions may further enhance sales.

Payment Preferences:

  • Cash on Delivery (COD) is the preferred payment method for 43% of customers. Consider incentivizing online or card payments through discounts to diversify payment channels.

Seasonal Sales Trends:

  • n 2019, the highest sales occurred in December, reaching $166,185. In 2020, the highest sales were in the month of December, but at $79,411. Seasonal variations may need consideration in future planning.

Profit Analysis:

  • In 2019, the highest profit was earned in October, totaling $9,275. In 2020, the highest profit occurred in December, reaching $17,885.

Top-Selling Sub-Category and Category:

  • The highest selling sub-category is phones, generating $0.20 million in sales.
  • The overall highest selling category is Office Supplies.

Shipping Preferences:

  • Standard class shipping is the most preferred method by customers.

Store Performance Metrics (2019-2022):

  • Total products sold: 22,000
  • Total profit earned: $175,000
  • Average delivery time: 4 days
  • Total sales: $1.6 million

Recommendations

  • Consider targeted campaigns or discounts to boost sales of home office products.
  • Focus marketing efforts on the East and West regions to capitalize on the highest-contributing areas.
  • Introduce discounts for online and card payments to encourage diversification of payment channels.
This analysis provides a comprehensive overview of Trendify's sales data, offering valuable insights for strategic decision-making. The interactive dashboard created will serve as a dynamic tool for ongoing analysis and monitoring.

About

Championing advanced data analysis, I'm crafting a dynamic sales analysis and forecasting solution. From an intuitive KPI dashboard to precise 15-day forecasts using time series analysis, the aim is clear: empower strategic decisions for business growth and operational efficiency.

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