Strategy question
How would you redesign Lovable's credit-based pricing to reduce bill shock?
- Lovable
- Strategy
- Hard
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What this question tests
Pricing and UX redesign to fix a specific, named customer complaint, usage-based bill shock, without abandoning the underlying model.
How to approach it
- Clarify the root cause: users cannot predict how many credits a prompt or iteration will consume before running it, so costs feel unpredictable.
- Add upfront cost transparency: show an estimated credit cost before a user confirms an expensive action, similar to a price preview.
- Add spending controls: let users set a soft cap or alert threshold, with a warning before they cross it mid-session.
- Consider a hybrid model: a flat monthly allotment covering typical usage, with credits only for unusually large or repeated regenerations.
- Add a post-hoc breakdown showing exactly what consumed credits in a session, so users learn to use credits more efficiently over time.
- Define success as reduced billing-related support tickets and reduced cancellation tied to unexpected charges.
What a strong answer includes
- Targets the actual root cause (unpredictability) rather than just lowering the price, which does not fix the trust problem.
- Proposes concrete UX fixes (cost preview, spend caps, usage breakdown) that are buildable, not just a vague 'better pricing'.
- Suggests a hybrid flat-plus-usage model as a middle ground that keeps the business upside of usage pricing while reducing shock.
- Uses support-ticket and churn data tied to billing as the success metric, directly tied to the complaint.
- Recognizes this is a trust issue as much as a pricing issue.
Common mistakes
- Proposing to just lower credit prices without addressing the predictability problem.
- Ignoring the business need to keep usage-based revenue upside.
Likely follow-up questions
- How would you set a reasonable default spend cap?
- Would you keep pure usage pricing or move to a hybrid model?
- How would you communicate this change to existing users?
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More questions from Lovable
Learn the skill behind it
Chapters of the AI PM course that teach what this question tests.
- Chapter 4: Discovery and strategy for AI products
- Chapter 9: Prove it paid off: outcomes, economics, and pricing
- Chapter 14: Get the job: the AI PM interview loop