Plot four price-sensitivity curves: Too Cheap, Cheap/Good Value, Expensive/High, and Too Expensive. The intersections reveal: Point of Marginal Cheapness, Optimal Price Point, Indifference Price Point, and Point of Marginal Expensiveness.
1) At what price would it be so cheap you doubt the quality? 2) At what price is it a bargain? 3) At what price is it getting expensive? 4) At what price is it too expensive? Plot the cumulative responses to find optimal pricing.
200-500 respondents from your target audience produce reliable results. More is better but diminishing returns beyond 500. Ensure respondents represent your actual user base, not just anyone — pricing sensitivity varies dramatically by segment.
Yes, and it is especially useful for setting initial prices or evaluating price changes. Frame questions around the monthly subscription price. Combine with actual A/B price testing for validation — stated willingness-to-pay often differs from actual behavior.
The core promise of benefit that explains why a user should subscribe. A strong value proposition is consistently reinforced across onboarding, paywalls, and messaging, connecting to user needs to premium features.
A form of ad attribution that credits conversions to an ad that was viewed (but not clicked) prior to the app install. It's particularly relevant for channels like YouTube, OTT, or display, where ad exposure influences user decisions indirectly.
The organic growth that occurs when users bring in other users through referrals, content sharing, or social features. Measured by metrics like the K-factor, virality helps reduce CAC and amplify the impact of lifecycle loops.
When a user intentionally cancels their subscription. Typically, due to cost sensitivity, unmet expectations, or perceived lack of value. Differentiated from involuntary churn, which occurs due to failed payments or technical issues.
Botsi automatically shows the right price to every user. Stop guessing and start growing.