Usage Instructions
About the ROAS Calculator
ROAS (Return on Ad Spend) is an important metric for measuring ad campaign efficiency, helping you evaluate the profitability of advertising activities. This tool quickly calculates core metrics such as ROAS and profit by entering ad revenue and ad spend, and supports calculating more detailed conversion funnel metrics through auxiliary data.
Key Features
- Real-time calculation: Calculate and display key metrics such as ROAS, profit, and profit margin in real-time as you input data
- Detailed metrics: Support calculating conversion funnel metrics like CPA, CPC, CVR, CTR (requires filling in corresponding auxiliary data)
- Data insights: Automatically generate insights and optimization suggestions based on calculation results
- Auto-save: Form data is automatically saved locally, and data won't be lost on refresh
- Multi-currency support: Supports multiple currencies (CNY, USD, EUR, etc.)
Calculation Formulas
- ROAS (Ratio) = Ad Revenue ÷ Ad Spend
- ROAS (Percentage) = (Ad Revenue ÷ Ad Spend) × 100%
- Ad Profit = Ad Revenue - Ad Spend
- Profit Margin = (Ad Profit ÷ Ad Revenue) × 100%
- Cost Per Acquisition (CPA) = Ad Spend ÷ Conversions (requires Conversions)
- Cost Per Click (CPC) = Ad Spend ÷ Clicks (requires Clicks)
- Conversion Rate (CVR) = (Conversions ÷ Clicks) × 100% (requires Conversions and Clicks)
- Click-Through Rate (CTR) = (Clicks ÷ Impressions) × 100% (requires Clicks and Impressions)
Usage Tips
- Keep ROAS above 2.0: If ROAS is below this value, consider optimizing ad creative, audience targeting, or bidding strategy
- Monitor conversion rate: If clicks are high but conversions are low, focus on optimizing landing page experience and conversion process
- Control acquisition costs: If CPA or CPC is too high, consider optimizing ad creative or adjusting bidding strategy
- Compare different scenarios: You can input different parameters multiple times to compare ROAS differences between different ad strategies
- Reference optimization suggestions: The optimization suggestions provided by the system are based on data analysis and can be used as decision references
- Unify data basis: It's recommended to confirm the statistical time range and data units first to ensure all data is on the same dimension