Decision Briefing
Monetize the new AI feature as a subscription or credit packs?
Start with credit packs to learn willingness-to-pay; introduce a $20/mo tier only once 4-week retention crosses a threshold you set in advance.
Medium
Models converge on starting with credits while retention is still being learned, but split on whether a subscription would itself help retention by anchoring habitual use.
Charging by usage when retention is uncertain protects the user from buyer's remorse and protects you from anchoring valuation on an MRR number your product has not yet earned.
- Strong agreement
A subscription locks in revenue but also masks the retention signal you actually need right now.
If you bundle access for $20/mo, you stop being able to tell whether users came back because they wanted to or because they had already paid. That is the exact metric your next pricing decision depends on.
- 3Supports
- Split opinion
Credit packs will create friction that depresses adoption among casual users.
If true, you under-monetize the long tail that would have paid $20/mo without thinking. If false, the friction actually filters for the engaged users whose behaviour you most want to learn from.
- 1Supports
- 1Conditional
- 1Opposes
Retention is the binding constraint — pricing decisions made before retention is understood compound badly in both directions.
Whichever model you launch with becomes the default the market expects from you; switching later costs goodwill and forces an explanation.
A $20/month price point is plausible for this feature but not yet defensible without willingness-to-pay data from real buyers.
Risk tolerance
Whether the cost of churned subscribers exceeds the cost of slower revenue growth from credits
One model treats subscription churn as recoverable through better onboarding; another argues churned subscribers leave louder traces (refund requests, negative reviews, attribution to the brand) that a credit-pack user simply does not generate.
Evidence conflict
Whether users perceive credits as fairer or as more confusing than a flat subscription
Models disagree on what the analogous products' data shows. One reads credit packs as friction the market has consistently rejected outside gaming; another points to the recent shift among AI tools toward usage-based pricing as a signal that the norm is moving.
The strongest counter
A subscription tier gives your team — and your investors — an MRR base you can plan around. Credits make pipeline forecasting a guessing game right when the company most needs to know whether this is a real business or a curiosity.
Minority report
One voice argued you should not monetize at all yet. Every dollar of revenue right now is a distraction from the only thing that matters (retention), and pricing experimentation should happen after you have a non-trivial cohort of retained users to experiment on.
What price elasticity looks like for this audience — no one has tested $9 vs $19 vs $29 with real buyers yet.
Whether the early users' twice-then-drop retention pattern reflects feature gaps, wrong-audience product-market fit, or a missing follow-up trigger after the second session.
Ship three credit-pack price points within two weeks, instrumented for purchase rate and reuse — let the data, not benchmarks, set the price.
Commit in writing to the 4-week retention number you would trust before adding any subscription tier — pick the number before you see the data.
Talk to five users who dropped after two sessions and five who came back; the pricing model should follow that signal, not a comparison spreadsheet of what other AI products charge.