Each template includes essential columns, pre-set formulas, and instructions to make it functional right away.?
Purpose: Track stock levels, reorder points, and supplier information.
| Product Name | SKU | Category | Stock Qty | Reorder Point | Unit Price ($) | Supplier | Reorder Status |
|-------------------|------------|---------------|---------------|-------------------|--------------------|-----------------|--------------------|
| Apple | SKU001 | Fruits | 50 | 20 | 1.00 | Supplier A | Reorder Not Needed |
| Milk | SKU002 | Dairy | 10 | 5 | 2.50 | Supplier B | Reorder |
Reorder Status Formula:
Automatically flags low stock items:
[
=IF(D2<C2, "Reorder", "Reorder Not Needed")
]
Conditional Formatting:
Purpose: Track daily sales by product and calculate revenue automatically.
| Date | Product | Units Sold | Unit Price ($) | Revenue ($) |
|-----------------|-------------|----------------|--------------------|-----------------|
| 2025-01-01 | Bread | 50 | 2.00 | 100.00 |
| 2025-01-01 | Butter | 20 | 3.00 | 60.00 |
Revenue Calculation Formula:
Calculates revenue for each product:
[
=C2 * D2
]
Daily Total Revenue:
Add a SUM formula at the bottom to calculate daily totals:
[
=SUM(E2:E10)
]
Purpose: Plan weekly shifts and calculate total hours worked.
| Employee | Day | Shift | Hours |
|------------------|--------------|-------------|-----------|
| John Doe | Monday | Morning | 8 |
| Jane Smith | Monday | Evening | 6 |
| John Doe | Tuesday | Afternoon | 7 |
Total Hours Worked Formula:
Calculate total hours for each employee:
[
=SUMIF(A:A, "John Doe", D:D)
]
Conditional Formatting:
Highlight employees exceeding a set threshold (e.g., 40 hours):
Purpose: Estimate future revenue and compare against actual performance.
| Month | Projected Revenue ($) | Actual Revenue ($) | Variance (%) |
|------------------|--------------------------|-------------------------|-------------------|
| January | 10,000 | 9,500 | -5.00% |
| February | 12,000 | 13,000 | 8.33% |
Variance Calculation Formula:
[
=\frac{(C2-B2)}{B2} * 100
]
Chart:
Purpose: Track customer purchases, identify loyal customers, and calculate lifetime value (CLV).
| Customer Name | Total Purchases ($) | Purchase Frequency | Customer Lifetime Value (CLV) ($) |
|--------------------|-------------------------|-------------------------|----------------------------------------|
| John Doe | 1,200 | 10 | 12,000 |
| Jane Smith | 800 | 8 | 6,400 |
CLV Formula:
[
{CLV} = {Total Purchases} * {Purchase Frequency}
]
Customer Segmentation:
Use filters to group customers based on purchase value (e.g., High-Value Customers).
Purpose: Summarize retail operations with key metrics and visualizations.
| Metric | Value |
|----------------------------|------------------|
| Total Revenue ($) | 50,000 |
| Total Units Sold | 2,000 |
| Average Order Value ($) | 25 |
| Low-Stock Products | 15 |
Use line graphs to show revenue trends.
KPI Calculations:
Average Order Value:
[
=\frac{{Total Revenue}} / {{Total Orders}}
]
Total Units Sold:
[
=SUM(C2:C100)
]
Purpose: Analyze seasonal trends and identify sales peaks.
| Month | Product Category | Revenue ($) |
|------------------|----------------------|-----------------|
| January | Electronics | 15,000 |
| January | Clothing | 8,000 |
Summarize revenue by month and category.
Seasonal Chart:
Use trusted sites like Vertex42, Template.net, or Microsoft Office Templates.
Build Your Own:
Copy the structures provided above into Excel or Google Sheets.