Interactive Excel dashboard analyzing sales performance across regions, products, managers, time periods, and customer locations. Built entirely in Microsoft Excel using pivot tables, calculated columns, slicers, charts, and a consolidated dashboard to uncover trends and support data-driven business decisions.
- Monitor key sales metrics (average sales, total revenue, transaction volume)
- Identify top-performing regions, suburbs, product categories, and sales managers
- Reveal seasonal patterns (monthly & day-of-week trends)
- Create an intuitive dashboard for quick insights and filtering
- Provide actionable recommendations for marketing, inventory, and performance optimization
- Microsoft Excel (100% of the project – no Power BI, SQL, or external tools)
- Features used: Tables, Calculated Columns, PivotTables, PivotCharts, Slicers (connected), Dashboard layout
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Data Loading & Preparation
- Import raw data into Excel
- Convert range to Excel Table (Ctrl + T) → name it
SalesTable
-
Calculated Columns
- Added in table columns (using formulas):
Year= YEAR([Order Date])Month= TEXT([Order Date], "mmmm")Day= TEXT([Order Date], "dddd")Average Sales= AVERAGE([Sales Amount])
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Key KPIs & Summary
- Created a summary area with formulas (COUNT, SUM, AVERAGE) for:
- Total Transactions
- Total Revenue
- Average Sales per Transaction
1. INSERT PIVOT TABLES
* Go to insert>Pivot Table, select "Salestable" as the source and place each pivot table on a new sheet.
* Create separate pivot tables for:
- Average of sales in each year by state
- Top five Suburb
- Top ten average sales by category from 2016-2018
- Top ten best selling manager
- Percentage of sales by each month
- Five best selling days of the year.
* Average of sales in each year by state
- Row: State
- Column: Financial Year
- Values: Sales
* Top five suburb
- Row: Suburb
- Filter: Financial Year
- Values: Sales
* Top ten average sales by category from 2016-2018
- Row: Category'
- Column: Financial Year
- Values: Average Sales
* Top Ten best selling manager
- Row: Manager
- Column: Financial Year
- Values: Sales
* Percentage of sales by each month
- Row: Month2
- Values: Sales
* Five best selling days of the year
- Row: Day
- Column: Year
- Values: Financial Year
1. Average of sales in each year by state <Column Chart>
This analysis covers yearly sales performance, state comparisons and regional patterns. In 2015 NSW led with an average of $867,
followed by VIC at $737.
2. Top five Suburb <Bar Chart>
Helps to analyze how different suburbs contribute to overall sales. This helps to identify high-performing regions and areas that
may need more attention.
3. Top Ten average sales by Category <Column Chart>
It analyzes which product categories contribute most to revenue. From 2016-2018 Shoes contributed the most to revenue ($1,189),
topping the list of top ten average sales by category.
4. Top Ten best selling manager <Stacked Column Chart>
It evaluates sales performance at the individual level. It helps to identify the top ten best selling manager.
5. Percentage of sales by each month <Stacked Line Chart>
It helps to understand seasonal trends and forecast demand, compare across months see consistency.
6. Best five selling days of the year < Column Chart >
It helps to find the days that generated the highest sales. Useful for identifying successful campaigns or seasonal surges.
- Financial Year slicer connected to **all** pivot tables and charts
- Allows dynamic filtering across the entire dashboard
- **Regional Performance**
NSW leads average sales ($867 in 2015 → $971 in 2016); VIC and NT follow closely. ACT lags significantly.
- **Top Locations**
Campbelltown is the highest-performing suburb (over $1.7M in sales) — strong market presence here.
- **Product Categories**
Shoes dominate average sales — prioritize inventory and promotions for this category.
- **Seasonality**
March and August are peak months (~11% each of annual sales); October and November are lowest (~5%) — plan inventory/marketing accordingly.
- **Day-of-Week Trends**
Best-selling days identified — optimize staffing/promotions on high-volume days.
Business Recommendations
- Focus marketing budget and inventory on NSW, VIC, and Campbelltown
- Investigate and support underperforming regions (e.g., ACT)
- Stock more Shoes and plan seasonal promotions for March/August
- Align sales team training and incentives with top performers
- Download or clone the repository
- Open
SALES ANALYSIS EXCEL PROJECT.xlsxin Microsoft Excel - Enable content/macros if prompted (for slicers)
- Use the Financial Year slicer on the Dashboard sheet to filter all visuals
- Explore pivot tables and charts on individual sheets for deeper analysis
This Excel-based sales analysis project reveals clear patterns in performance across regions, products, sales managers, and time periods. Key findings include:
- NSW consistently leads in average sales (rising from $867 in 2015 to $971 in 2016), followed by VIC and NT, while ACT significantly underperforms.
- Campbelltown stands out as the top-performing suburb (over $1.7M in total sales).
- Shoes dominate average sales among product categories — a clear priority for inventory and promotion.
- March and August are peak months (~11% of annual sales each), while October and November are the weakest (~5%).
- Certain days of the week show stronger sales — ideal for targeted staffing and promotions.