Model baseline monthly website revenue and four fixed uplift scenarios. This is an assumption model, not measured revenue loss or ROI.
Use metrics from the same reporting period and the same conversion definition.
10,000 visitors/month
$50 revenue per conversion
Illustrative Combined Monthly Uplift
$5,600/month
Each fixed assumption is calculated against the baseline and then added. Real effects can overlap and should not be treated as independent.
Simple 12-month annualization before costs: $67,200 per year
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It calculates baseline monthly revenue as visitors multiplied by conversion rate multiplied by average value per conversion. It then calculates four separate uplifts using fixed traffic, bounce, conversion-rate, and mobile assumptions and adds them together. The output is a hypothetical revenue scenario, not measured incremental revenue.
No. Return on investment requires the incremental benefit and the investment cost over a defined period. This calculator does not ask for implementation cost, operating cost, gross margin, timing, discounting, taxes, or attribution. Add those inputs in a separate business case before reporting ROI.
The four scenarios assume 15% more traffic, retention of 20% of current bounced visits with those visits converting at the baseline rate, a 0.5 percentage-point conversion-rate increase, and 10% more conversions across an assumed 60% mobile traffic share. These are model inputs, not forecasts or benchmarks validated for your website.
The interface adds them arithmetically, but real effects can overlap. Speed changes can affect conversion and bounce rate, SEO traffic can have a different conversion rate, and mobile visitors are part of total traffic. Use the combined value only as a sensitivity case and model dependencies explicitly before making a decision.
Use revenue per completed conversion for the same period and conversion definition as your traffic and rate. For ecommerce, that may be average order value. For leads, use a defensible expected revenue per lead based on qualified-lead, close-rate, and deal-value data. Do not substitute lifetime value without matching the time horizon.
Replace fixed assumptions with analytics, experiments, search data, margins, and implementation estimates from your business. Separate incremental traffic from conversion effects, model a realistic ramp and time horizon, include recurring costs and risk, and calculate a low, central, and high case. Measure the actual result after launch.