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Weighted Average Contribution Margin Calculator

Weighted Average CM Formula:

\[ \text{Weighted CM} = \sum (\text{Product CM} \times \text{Sales Mix}) \]

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1. What is Weighted Average Contribution Margin?

The Weighted Average Contribution Margin is a calculation that takes into account the different contribution margins of products and their proportion in total sales. It provides a more accurate picture of overall profitability than a simple average.

2. How Does the Calculator Work?

The calculator uses the weighted average formula:

\[ \text{Weighted CM} = \sum (\text{Product CM} \times \text{Sales Mix}) \]

Where:

Explanation: The equation multiplies each product's contribution margin by its sales mix percentage (as a decimal), then sums these values to get the weighted average.

3. Importance of Weighted Average CM

Details: This metric is crucial for businesses with multiple products as it helps in break-even analysis, pricing decisions, and understanding overall profitability.

4. Using the Calculator

Tips: Enter contribution margin in USD for each product and their respective sales mix as a decimal (e.g., 0.25 for 25%). Ensure sales mix values sum to 1 for accurate results.

5. Frequently Asked Questions (FAQ)

Q1: What is contribution margin?
A: Contribution margin is the selling price per unit minus the variable cost per unit. It shows how much each product contributes to covering fixed costs.

Q2: Why use weighted average instead of simple average?
A: Weighted average accounts for different sales volumes of products, giving more importance to products that sell more.

Q3: How is sales mix determined?
A: Sales mix is calculated by dividing a product's sales quantity by total sales quantity of all products.

Q4: Can I add more than two products?
A: This calculator handles two products. For more products, the same formula applies but with additional terms.

Q5: What's a good weighted average CM?
A: This varies by industry. Higher values are generally better, but compare with industry benchmarks for meaningful analysis.

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