Monadic Price Testing
The gold standard for pricing research. Simulate split-cell surveys where each respondent sees only one price to measure true purchase intent without bias.
Test Cells
Revenue & Conversion Analysis
Optimal Price
Maximizes Total Revenue
Conversion Peak
Highest Intent Recorded
Revenue vs Conversion
The crossing point of Volume and Value.
The Revenue Winner
The chart highlights $24.99 as the revenue winner. Even if conversion is lower, the higher price compensates.
Elasticity Curve
Observe the slope of the Purchase Intent line. If it drops steeply between two prices, you've hit a psychological barrier.
Sample Validity
Ensure your survey sample matches your actual target customer. Random internet respondents will skew cheap.
Execution Steps
Define your price points (cells). Usually 3-5 distinct prices.
Input the 'Sample Size' (respondents per cell) and the resulting 'Purchase Intent %' from your survey.
The tool calculates the Revenue per 1000 Impressions (RPM) for each price point.
Identify the price that maximizes revenue, not just conversion rate.
Pro Strategy
- Monadic testing requires large sample sizes (N=200+ per cell) to be statistically significant.
- Use this for new-to-world products where customers don't have a strong internal reference price.
- Always ask 'Why?' after the purchase question to understand the value drivers behind the decision.
Core Concepts
Monadic Design
A survey design where respondents are split into groups, and each group sees only ONE concept/price. This eliminates 'comparison bias'.
Purchase Intent
The percentage of respondents who select 'Definitely would buy' or 'Probably would buy' (Top 2 Box score).
Revenue Efficiency
A high price might convert lower, but if the margin is high enough, it generates more total profit. This tool visualizes that trade-off.
What is Monadic Price Testing?
Monadic Testing isolates the price variable. By randomly assigning respondents to different price cells, we assume the groups are demographically identical. Any difference in purchase intent is therefore caused by the price alone. This produces the cleanest demand curve possible.
Best For
- • Finalizing a launch price for a major product.
- • Testing a price increase where risk of churn is high.
- • Validating results from a Van Westendorp study.
Limitations
- • Expensive due to high sample size requirements.
- • Does not simulate competitive context (unless competitors are shown in the concept card).
Alternative Methods
Van Westendorp
Cheaper, requires fewer respondents, but less precise for specific conversion forecasting.
Conjoint Analysis
Better if you want to test different feature configurations alongside price.
Industry Applications
See how this methodology generates real revenue uplift in different sectors.
Energy Drink Launch
Brand wanted to launch at a premium $3.99 price point vs market standard $2.99.
Ran a Monadic test with 4 cells ($2.99, $3.49, $3.99, $4.49).
Subscription Box Pricing
Considering a price hike from $29 to $39.
Monadic test revealed a sharp drop-off (40% reduction in intent) at $39, but stable demand at $34.