Jonathan Parra, founder of Tapas Growth, explains why app category predicts test results better than the app itself, how to sequence design, packaging, and price tests, and why the ugly paywall keeps winning.
Jonathan has designed close to 4,700 paywalls. He walks through the testing order he uses with clients, the five paywall placements every new app should ship before optimizing anything, and the exit questionnaire that replaced his old discount ladder. He also gets specific on numbers: a healthy app loses half its trial starts, win-back campaigns aimed at those cancelers convert at 5 to 6 percent, and removing a free plan can push conversion from 2 percent to 12 percent while gutting your traffic.
What you'll learn:
• Why app category, not app quality, is the first thing Jonathan looks at when predicting a test outcome
• How product polish and a clear ICP change the size of the win you can expect
• Why he turns down clients he doesn't think he can make money for
• How to decide between freemium and a hard paywall using your marginal cost per free user
• Why AI apps with real inference costs should start with a hard paywall and a 3 to 7 day trial
• How to gate the expensive part of your product and leave the cheap part free
• Why design tests come before packaging tests, and packaging before price
• How a design winner sets up a price increase that doubles ARPU
• What changed in his testing workflow now that LLMs can crunch the data
• How device signals like battery level and network type get used as demand scores
Key Takeaways:
• Marginal cost decides your monetization model. If a free user costs you nothing, keep them and monetize later. If every action fires an LLM call or streams video, a hard paywall with a short trial is the honest answer. The middle path is gating the expensive feature and leaving the cheap one open, like charging for photo-to-macros and giving away water logging.
• Design, then packaging, then price. A design winner can double conversion rate. Once you have it, raising price walks conversion back toward where it started while ARPU stays doubled. Price testing first just trades conversion for revenue with no ceiling raised.
• The ugly paywall wins and you have to accept it. Jonathan is a trained UX designer and says CRO is a different game entirely. Dense, loud, in-your-face layouts beat minimal ones often enough that he stopped arguing with the data, especially in the companionship and character AI space.
• Ask instead of guessing. His old exit flow was a fixed ladder: extended trial, then 33 percent off. It cannibalized revenue from people who would have paid more. Now an exit questionnaire asks why they bailed, and the offer matches the answer. Price complaint gets a discount. Trial complaint gets a longer trial.
• Half your trials cancel, and nobody markets to them. Jonathan targets users with an active entitlement and auto-renewal switched off. Those campaigns convert at 5 to 6 percent, which adds 2.5 to 3 points to overall conversion. It's the largest high-intent audience most apps ignore.
• Discount depth is a sequencing decision. Don't open with 80 percent off. Save the steep offers for expired users and Black Friday. A downgrade to a cheaper tier often keeps the customer without cheapening the brand, and a first-year-only discount lets you rebill at full price later.
• Weekly-only pricing is a speed run. ARPU looks great and churn is brutal. Jonathan will use weekly plans as paid intro offers or for genuinely short-use ICPs, but apps that sell nothing else ride viral traffic until the cohorts stop stacking.
Links & Resources
• Tapas Growth: https://tapasgrowth.com/
• Jonathan Parra on X: https://x.com/jondeparra
• Jonathan Parra on LinkedIn: https://www.linkedin.com/in/jondeparra/
• Jonathan's guest post on Retention.blog: https://www.retention.blog/p/expert-paywall-tips
Timestamps
00:00 Intro: 4,700 paywalls and counting
01:00 What Jonathan got wrong early at Superwall
03:30 Predicting test results before you run them
05:30 Using category benchmarks to diagnose an app
07:00 The two times he was wrong, and working for free
09:30 Freemium vs hard paywall, decided by cost
13:00 Gating the expensive feature, freeing the cheap one
14:00 Test order: design, packaging, price
17:30 Demand scores from device attributes
18:30 Age-based price testing and why it's risky
20:30 What changed post-AI in the testing workflow
23:30 Why the ugly paywall wins
27:30 Building a real exit flow
28:30 The questionnaire that replaced the discount ladder
31:00 The exact questions he asks
34:30 The five paywalls every new app should ship
38:30 Trial cancelers: the 5 to 6 percent win-back
40:30 Downgrades, discount depth, and brand
42:00 Transaction abandon tactics
44:00 Winning back expired subscribers
48:30 Email, push, SMS, and where the ceiling is
51:30 Weekly plans and the TikTok wall
54:00 Biggest packaging win: multi-page paywalls
Jonathan has designed close to 4,700 paywalls. He walks through the testing order he uses with clients, the five paywall placements every new app should ship before optimizing anything, and the exit questionnaire that replaced his old discount ladder. He also gets specific on numbers: a healthy app loses half its trial starts, win-back campaigns aimed at those cancelers convert at 5 to 6 percent, and removing a free plan can push conversion from 2 percent to 12 percent while gutting your traffic.
What you'll learn:
• Why app category, not app quality, is the first thing Jonathan looks at when predicting a test outcome
• How product polish and a clear ICP change the size of the win you can expect
• Why he turns down clients he doesn't think he can make money for
• How to decide between freemium and a hard paywall using your marginal cost per free user
• Why AI apps with real inference costs should start with a hard paywall and a 3 to 7 day trial
• How to gate the expensive part of your product and leave the cheap part free
• Why design tests come before packaging tests, and packaging before price
• How a design winner sets up a price increase that doubles ARPU
• What changed in his testing workflow now that LLMs can crunch the data
• How device signals like battery level and network type get used as demand scores
Key Takeaways:
• Marginal cost decides your monetization model. If a free user costs you nothing, keep them and monetize later. If every action fires an LLM call or streams video, a hard paywall with a short trial is the honest answer. The middle path is gating the expensive feature and leaving the cheap one open, like charging for photo-to-macros and giving away water logging.
• Design, then packaging, then price. A design winner can double conversion rate. Once you have it, raising price walks conversion back toward where it started while ARPU stays doubled. Price testing first just trades conversion for revenue with no ceiling raised.
• The ugly paywall wins and you have to accept it. Jonathan is a trained UX designer and says CRO is a different game entirely. Dense, loud, in-your-face layouts beat minimal ones often enough that he stopped arguing with the data, especially in the companionship and character AI space.
• Ask instead of guessing. His old exit flow was a fixed ladder: extended trial, then 33 percent off. It cannibalized revenue from people who would have paid more. Now an exit questionnaire asks why they bailed, and the offer matches the answer. Price complaint gets a discount. Trial complaint gets a longer trial.
• Half your trials cancel, and nobody markets to them. Jonathan targets users with an active entitlement and auto-renewal switched off. Those campaigns convert at 5 to 6 percent, which adds 2.5 to 3 points to overall conversion. It's the largest high-intent audience most apps ignore.
• Discount depth is a sequencing decision. Don't open with 80 percent off. Save the steep offers for expired users and Black Friday. A downgrade to a cheaper tier often keeps the customer without cheapening the brand, and a first-year-only discount lets you rebill at full price later.
• Weekly-only pricing is a speed run. ARPU looks great and churn is brutal. Jonathan will use weekly plans as paid intro offers or for genuinely short-use ICPs, but apps that sell nothing else ride viral traffic until the cohorts stop stacking.
Links & Resources
• Tapas Growth: https://tapasgrowth.com/
• Jonathan Parra on X: https://x.com/jondeparra
• Jonathan Parra on LinkedIn: https://www.linkedin.com/in/jondeparra/
• Jonathan's guest post on Retention.blog: https://www.retention.blog/p/expert-paywall-tips
Timestamps
00:00 Intro: 4,700 paywalls and counting
01:00 What Jonathan got wrong early at Superwall
03:30 Predicting test results before you run them
05:30 Using category benchmarks to diagnose an app
07:00 The two times he was wrong, and working for free
09:30 Freemium vs hard paywall, decided by cost
13:00 Gating the expensive feature, freeing the cheap one
14:00 Test order: design, packaging, price
17:30 Demand scores from device attributes
18:30 Age-based price testing and why it's risky
20:30 What changed post-AI in the testing workflow
23:30 Why the ugly paywall wins
27:30 Building a real exit flow
28:30 The questionnaire that replaced the discount ladder
31:00 The exact questions he asks
34:30 The five paywalls every new app should ship
38:30 Trial cancelers: the 5 to 6 percent win-back
40:30 Downgrades, discount depth, and brand
42:00 Transaction abandon tactics
44:00 Winning back expired subscribers
48:30 Email, push, SMS, and where the ceiling is
51:30 Weekly plans and the TikTok wall
54:00 Biggest packaging win: multi-page paywalls