Pricing Sensitivity Simulator

Simulate how changes in price might affect potential revenue, considering different estimated conversion rates for each price point. Understand the trade-offs between price and conversion.

Current Scenario

$
%

New Scenario

$
%

Revenue Simulation Results (Based on 1,000 Visitors)

Current Revenue(Estimated)

$5,000.00

Projected Revenue(New Price)

$4,800.00

Revenue Change(% and $)

-4.0%

(-$200.00)

Understanding Pricing Sensitivity

Pricing sensitivity measures how customer demand changes in response to changes in price. A high sensitivity means a small price change causes a large change in demand (or conversion rate), while low sensitivity means demand is less affected by price adjustments. This simulator helps you explore potential outcomes based on your assumptions.

How the Simulation Works

The tool calculates potential revenue for both your current and proposed pricing scenarios based on a given number of visitors (or impressions, leads, etc.):

  • Estimated Revenue: Number of Visitors * Conversion Rate * Price

It compares the estimated revenue from the current price and conversion rate against the projected revenue from the potential new price and its associated estimated conversion rate.

For example:

  • Current: 1,000 Visitors * 5% Conversion * $100 Price = $5,000 Revenue
  • New Scenario: 1,000 Visitors * 4% Conversion * $120 Price = $4,800 Revenue
In this case, despite the higher price, the lower conversion rate leads to slightly less overall revenue. The simulator shows you this potential trade-off.

Why Simulate Pricing Sensitivity?

  • Optimize Pricing: Explore price points to potentially maximize revenue, balancing price increases with potential conversion drops.
  • Understand Trade-offs: Visualize the relationship between price elasticity and revenue impact.
  • Inform Decisions: Provide data points (based on your estimates) when considering price changes or A/B tests.
  • Scenario Planning: Quickly test different hypotheses about how conversion might react to price adjustments.

Important Considerations

  • Estimates are Key: The accuracy of the simulation depends entirely on how accurately you can estimate the conversion rate at the new price point. This is often the hardest part and may require market research, testing, or analysis of historical data.
  • External Factors: Real-world results can be influenced by competitor pricing, market conditions, product changes, and marketing efforts not captured in this simple model.
  • Visitor Base: Ensure the 'Number of Visitors' input represents the relevant audience size for the conversion event (e.g., website visitors for a sign-up conversion, qualified leads for a sales conversion).

Use the calculator above to input your current figures and experiment with potential pricing changes and their estimated impact on conversions and revenue.