Price Power

Jacob Rushfinn
  • 5.0 (1)
  • Marketing

The Price Power Podcast is for all things growth, retention, and monetization for subscription mobile apps. We talk with amazing leaders in the industry to help share their knowledge with you. Hosted by Jacob Rushfinn, CEO of Botsi.

  1. 2d ago

    26: The truth about ChatGPT ads w/ Gabe Kwakyi

    We’re talking with Gabe Kwakyi today, who was actually our first guest! He is a mobile app OG, was previously the CEO of Lingvano, the #1 sign language app, and is now doing consulting, advising and fractional head of growth for apps. As well as building some stuff on his own. This is a pretty cool episode because Gabe has been testing ChatGPT ads, and we get to learn from his real experience about how they work, what works today, and what the future could look like. Gabe has run ChatGPT Ads tests across his own portfolio of apps and several client apps since the self-serve platform launched in May 2026. He walks through the setup, shares the context hints that flopped and the ones that drove conversions, and explains why an app icon beat every other creative he tried. He also makes the case that ChatGPT Ads will become a serious channel once OpenAI has enough conversion data; until then, most tests will fail. What you’ll learn:• How ChatGPT Ads are structured: campaigns, ad groups, ads, and the handful of targeting options available today• What context hints are and why they’re the main lever you control• Why ChatGPT Ads deliver decent CPMs, CPCs and CTRs but very few trials or purchases• How Gabe’s test across eight apps turned out, and why most apps saw zero purchases• Why users on ChatGPT’s free and Go plans may be harder to convert into subscribers• Why OpenAI’s missing conversion data, not its targeting tech, is the real blocker• How conversation “turns” affect whether a user is ready to see an ad• Which context hint patterns worked: conversation context, user goals, rejected ideas, and the “layup insertion”• Why keyword-style context hints only sometimes work• Why a plain app icon outperformed screenshots and Meta creative• What URL parameters ChatGPT passes and what the “oppref” parameter is• How to tailor your onboarding to ChatGPT traffic intent• How to tell whether ChatGPT Ads are lifting your organic ChatGPT referrals• When it’s worth testing now and when to wait• Gabe’s feature wish list for the ChatGPT Ads team Key Takeaways: Context hints are your creative. ChatGPT Ads give you almost no creative surface, so the context hint does the work that ad creative does on Meta. Gabe spends his testing budget there first and treats headline and copy as secondary. Clicks are cheap; buyers are rare. Across Gabe’s eight-app test, CTR averaged 1.68% and install rate 3.36%, but purchase conversion averaged 0.14%. Most apps saw zero purchases. Industry reports match: one review of 35 case studies found 22 with zero conversions. The blocker is data, not targeting. Meta became a great performance channel because every advertiser sent conversion events back. ChatGPT Ads launched in May 2026 and hasn’t collected enough postbacks to know which users buy. That will change as more advertisers integrate their MMPs. Target the moment, not the topic. “Users who want date ideas” brings volume. “User keeps rejecting every date idea and wants better ones” brings people who still have the problem and are open to a new solution. Gabe’s best results came from these frustrated, self-qualifying moments. Use your app icon. The ad image is a small square next to the answer. Screenshots and text-heavy banners are unreadable there. An icon looks like a product recommendation, which is what users expect. Testing is cheap, so treat it as learning. The minimum budget is $25 a day and setup takes minutes with an MMP tracking link. Gabe recommends testing every couple of months so you’re ready when performance turns, and skipping it if you need a new channel to work this quarter. Check your organic referrals. One advertiser spent $600 with no attributed conversions but saw organic ChatGPT referrals rise. If you test, watch untracked traffic and “how did you hear about us” answers. Links & Resources• Gabe Kwakyi on LinkedIn: https://www.linkedin.com/in/gabrielkwakyi/• Rhythmic apps: https://rhythmicapps.com/ Timestamps00:00 Why Gabe started testing ChatGPT Ads01:45 How the ChatGPT Ads platform works03:15 What context hints are07:30 Great clicks, low conversions: results from eight apps10:00 Free and Go users, and the missing conversion data13:00 Is ChatGPT closer to search or social?15:30 Conversation turns and the right moment for an ad17:30 Rejected ideas and the “layup insertion”20:45 Why campaigns are so volatile22:00 More context hint categories to test26:00 Personalizing onboarding by traffic intent28:30 URL parameters and tracking30:00 Why the app icon beats every other creative35:15 Is it worth testing right now?38:30 The organic referral halo41:00 Gabe’s feature wish list46:15 Have fun with it: the return of real marketing

    26: The truth about ChatGPT ads w/ Gabe Kwakyi

  2. Oct 1

    25: 13 Onboarding Principles for High-Converting Subscription Apps

    Jacob Rushfinn, CEO of Botsi, has spent a decade in consumer apps figuring out how to convert users. He compiled 13 principles for your onboarding flow that will make a difference. These are all from experimentation and research from top apps like Opal, Finch, Headway, Tiimo, Tolan, Zing, and more. What you'll learn: • Why the first screen is a drop-off point most teams never measure• How Opal, Rise Science, and Headway hook users before they tap anything• Why story-style intro screens beat any UI pattern you invent• Why simple string personalization beats complex personalization almost every time• How to make quiz questions feel like a conversation instead of a form• Why letting people build something (a pet, a name, a journal entry) raises commitment• How to show users the math on the value they'll get• How to build trust across the whole flow: answer the biggest fear, lead with emotion, back it with numbers• When to prime permission prompts and when to just fire the native one• Why there is no excuse left to skip video, with examples from Lingokids, BoldVoice, and Ladder• How to turn loading screens into selling screens• How to make the free trial impossible to miss, and what to do when users close the paywall anyway Key Takeaways:- Your first screen is a drop-off point. It can lose 10 to 30 percent of new users before they tap anything. A plain welcome, get started, log in screen works for big brands; everyone else needs a hook that's interesting and easy, like Opal's glowing rock or Finch's "Hatch a new pet" button. - Ask for the account when intent is highest. Tiimo moved account creation from right before the paywall to right after the welcome screen and lifted both account creation and trial starts. It also stops you from asking for an email and a payment back to back. Test it, or skip account creation until after the paywall. - Say the user's goal back to them. Ask the goal, ask why it matters, then repeat their words on the next screen, in the plan recap, and in the paywall headline. Zing, Tiimo, and Impulse all do this, and it rarely fails to lift conversion. - Let people build something. People value what they put work into. Finch has you design a bird, which is fun, low-effort, and raises no privacy concerns. Add presets and shuffle buttons so nobody stalls on a blank text field. - Show them the math. Turn inputs into a concrete number: Opal's five years of your life, Rise's sleep debt, Headway's 38 book summaries a month. When users hit the paywall, they should already know what they're getting. - Build trust before you ask for money. Most apps cram trust into the paywall. Better apps spread it across the flow: answer the user's biggest fear (privacy, for Flo), lead with emotion, back it with a number, and repeat your strongest social proof. - Make the trial impossible to miss. People don't read paywalls. They see a price and leave, even when the trial is visible. Trial reminders, choose-your-trial screens, and multi-page paywalls force users to notice it. When they close the paywall, follow up with a second offer. - Onboarding doesn't end at the paywall. Don't drop a new subscriber onto an empty home screen. Imprint sends you straight into your first lesson; Balance auto-starts a sleep meditation for people who picked sleep. This is what separates good trial starts from good trial conversion. Links & Resources- Price Power Podcast: https://pricepowerpodcast.com- Botsi onboarding flow library: https://botsi.com/resources/flows- Retention.blog: https://retention.blog- Jacob on LinkedIn: https://www.linkedin.com/in/jacob-rushfinn/ Timestamps00:00 Why onboarding decides whether your app is worth paying for00:45 1. Hook them on the first screen03:00 2. Borrow UI patterns people already know04:00 3. Ask for account creation when intent is highest05:30 4. Ask the user's goal, then say it back to them07:05 5. Make onboarding questions feel like a conversation08:15 6. Let people build something09:30 7. Show them the math10:30 8. Build trust before you ask for money12:48 9. Earn the permission opt-in14:15 10. Use video, because it's cheap now16:05 11. Turn loading screens into selling screens18:00 12. Make the trial impossible to miss20:20 13. Onboarding doesn't end at the paywall22:13 Recap of all 1324:15 What to test first and which metrics to watch

    25: 13 Onboarding Principles for High-Converting Subscription Apps

  3. Sep 17

    24: Failed Payments are Free Money w/ Philip Pages

    Philip Pages, founder of Redux Payments, explains why moving off Apple's in-app purchases quietly strips away a retention machine most founders never knew they had, how failed payments actually work, and when payment orchestration is worth the extra complexity. Philip has looked inside hundreds of app payment accounts, and most of them are leaving real money on the table. He walks through the difference between a customer who wants to churn and a card that simply had no funds that morning; why recovered subscribers stick around for another three to six billing cycles; and the single setting that quietly blows up Stripe accounts. Jacob and Philip also get tactical on the app-to-web paywall pattern that converts, the retry schedule that recovers cards without triggering the card networks, and a meditation app that got back six figures by changing nothing but the timing of its retries. What you'll learn • Why Apple's in-app purchase system silently recovers failed payments, and exactly what you give up when you leave it• Why most failed payments have nothing to do with a customer wanting to cancel• How recovered subscribers behave once you win them back (they stay another three to six billing cycles)• Why the "30% down to 5%" margin pitch for web billing is misleading• How to tell whether your app is even ready to test web billing• Why older, Facebook-native audiences convert better on web-to-app flows than younger ones• How to set up web payments without blowing up your Stripe or Paddle account• What chargebacks, early fraud warnings, and approval rates actually do to your account health• How merchant-of-record providers take ownership of your transactions, and what that costs you later• What payment orchestration is, and the revenue point where it starts paying for itself• How one meditation app recovered over $150K by fixing retry timing by locale• How long you should really retry a failed card, and why spamming it backfires• The compliant two-button app-to-web paywall pattern that didn't exist a year ago Key takeaways • Apple runs a retention machine you never see. Behind the scenes, Apple retries cards near paydays, fixes bank issues, and serves in-app prompts for up to 60 days. It feels like magic, but it is a system. Move to web and that system is now your job. • Most failed payments are not people trying to leave. Insufficient funds at one moment in time and random bank rejections make up the bulk of failures. Treating every failure as a lost cause writes off customers who already paid you for months. • The margin math is messier than the pitch. Providers love to say you'll save 25 to 27 percent. Philip says heavily discount that. Even so, saving 15 percent and reinvesting it in growth can compound fast, so the channel is still worth testing. • Don't touch web billing before product-market fit. Under a million in ARR with no PMF, the only job is finding PMF. Optimizing payments early is a distraction. Post-PMF, commit real budget or don't bother. • Cancel your subscriptions. The number one way apps wreck their Stripe account is leaving failed subscriptions open. They stack, they collect chargebacks, and one subscription that should have had a single chargeback ends up with seven. • Retry timing beats retry volume. One app had 64 percent of failures come from insufficient funds. Retrying by local payday instead of at random recovered over $150K. Brute-forcing the card just gets you flagged by the networks. • Orchestration is where big brands quietly win. Netflix, Spotify, and other large subscription companies route payments across multiple processors to lift approval rates. Most smaller apps have never even considered it. • The app-to-web playbook is new, and it works. Two CTA buttons, a rebuilt mini-onboarding before the paywall, and Apple Pay on by default. Philip's word for the pattern Jacob describes: gold. It did not exist a year ago. Links & resources• Philip Pages on LinkedIn: https://www.linkedin.com/in/philip-pages-a881b5139/• Redux Payments: https://www.reduxpayments.com/ 0:00 Intro02:00 Intro and Philip's first company (peaked near $3.5M ARR, then shrank)04:11 Apple's hidden failed-payment machine, and what you lose moving to web07:00 What a failed payment actually is, and why most aren't churn11:05 The real margin math behind leaving the App Store12:16 Why web billing is hitting critical mass now17:20 Matching the right user to the right payment method21:33 Getting started: providers, merchant of record, subscription management25:47 How to not blow up your Stripe account28:43 Chargeback alerts and fighting chargebacks30:40 Merchant of record: owning the transaction, and getting out34:27 Payment orchestration and cascading across processors39:06 When web billing is a mistake (pre product-market fit)44:47 App-to-web compliance and the two-button paywall playbook52:32 A failed-payment recovery teardown (the six-figure meditation app)59:02 How long to retry a failed card01:03:00 The scariest account story, and what Redux Payments does

    24: Failed Payments are Free Money w/ Philip Pages

  4. Sep 3

    23: Lifecycle Marketing Will Be Autonomous w/ CEO of OneSignal

    George Deglin, CEO and co-founder of OneSignal, explains why calendar-based lifecycle marketing holds subscription apps back, why SaaS dashboards are losing their place as the primary interface, and what autonomous lifecycle marketing looks like in practice. George walks through OneSignal's autonomy ladder, from L0 (a traditional SaaS dashboard) to L4 (a self-improving agent). He explains how each level builds customer trust, why behavioral triggers outperform scheduled messages, why email remains overlooked by consumer apps, and why companies worried about token costs should build features that cost more—not less. What you'll learn: • Why lifecycle messaging should respond to product behavior instead of a marketing calendar • Why behavioral triggers outperform scheduled sends by 4x to 9x • How product and lifecycle-team silos weaken message quality • Why email is an underused, inexpensive retention and win-back channel • What George means when he says "dashboards are dying" • What happened when OneSignal asked 20 customers whether they preferred its dashboard or Claude, Gemini, or ChatGPT How the L0-to-L4 autonomy ladder moves from assistance to recommendations and independent execution • Why most companies pursuing ML personalization are optimizing the final 5% before mastering the basics • Whether AI could mean fewer lifecycle-marketing hires • How AI inbox filtering will raise the bar for message relevance • Where app-to-web billing and RCS payment flows could go next • Why OneSignal won't charge separately for AI—and why George favors expensive AI use cases today Key takeaways: • Calendar sends are the default—and the problem. Moving from scheduled messages to behavioral triggers is a larger opportunity than adding AI-generated personalization to a weak foundation. • Email is inexpensive and still reaches users after they uninstall. The main obstacle is organizational coordination, not technology. • Dashboards may fade, but product intelligence remains valuable. Users will increasingly operate software through agents while vendors expose more configuration through APIs. • The autonomy ladder is also a trust ladder: assistance, proactive recommendations, delegated execution, and finally guarded autonomy that knows when to ask for help. • Complex personalization can move a mature program from 95% to 100%, but many teams are overlooking the fundamentals. • AI may eliminate tedious lifecycle work and reduce some hiring, while also making effective lifecycle marketing affordable for more companies. • Today's expensive AI capability may become inexpensive as model costs fall, so George argues for building ahead of the cost curve. Links & resources • OneSignal: https://onesignal.com• George Deglin on LinkedIn: https://linkedin.com/in/gdeglin• George's essay on autonomous lifecycle marketing: https://onesignal.com/blog/the-future-of-lifecycle-marketing-is-autonomous/ Chapters 00:00 Cold open and episode introduction01:00 What separates apps that win at lifecycle marketing02:25 The most underused channel in consumer apps03:15 Why teams default to paid media over email04:30 Lifecycle marketing as an extension of the product05:35 Retention, LTV, and who owns it06:55 Change, provocative claims, and pushback07:55 "Dashboards are dying"08:05 Where the idea started with browser and computer use tools10:10 Asking 20 customers: dashboard or agent?11:15 Does every tool become a transactional layer?12:40 Headless software and configuration APIs14:50 The visual feedback loop problem16:40 Previewing an email campaign inside Claude18:05 The autonomy ladder, L0 to L420:00 Moving from assistance to recommendations23:50 What customers are doing with L125:00 Saving customers hours on reports26:00 L2: the recommendation engine27:30 Democratizing customer engagement28:40 Will competitors learn from my data?30:30 AI and one to one personalization32:20 Why triggered messages perform 4x to 9x better34:15 Personalization versus segmentation35:00 The 95% to 100% problem36:25 Will AI replace marketers?40:05 Why cheaper lifecycle marketing creates more companies41:25 Does easier sending lower quality?43:00 AI filtering on the receiving end44:50 Pricing, packaging, and subscriptions46:20 App to web billing49:10 RCS payments inside the conversation51:30 Token costs and why OneSignal won't charge for AI54:30 Wrap

    23: Lifecycle Marketing Will Be Autonomous w/ CEO of OneSignal

  5. Aug 20

    22: 9x ARR, +47% ARPU, the real tests that won with Michael Bardin | Price Power Podcast Ep. 21

    Michal, product growth lead at Applica Agency, explains why moving a paywall to the point of peak anticipation beat waiting for the aha moment, how trial length changes trial starts rather than trial conversion, and why the same paywall test produced opposite results on paid and organic traffic. Michal walks through three client teardowns. A client went from a buried feature-gate paywall to an onboarding paywall and grew ARR 9x; trial start rate moved from roughly 3% to 16%. Beducated, a sex education web funnel, lifted revenue per user 47% on Meta traffic and 27% on organic after Applica discovered the two channels wanted completely different plan structures. Alux, a wealth and finance content app charging $149 a year, improved day one retention 22% and install-to-paid conversion 26% by mining users' own free-text answers out of Mixpanel and rewriting the onboarding in their words. What you'll learn: Why anticipation beats the "aha moment" as a buying triggerWhat a paywall exit-intent survey revealed about price objectionsWhy device buyers felt they were paying twice for a subscriptionHow trial duration moves trial starts but leaves conversion untouchedWhy a 14-day trial beat every discount as an exit-intent downsellHow that downsell came to drive 10-15% of total revenueWhen per-placement paywalls are worth building, and when they're notHow often to paywall a retained free user baseWhy one A/B test can land positive and negative at the same timeWhy plan length is really about how far ahead users can picture themselvesHow a weekly plan works as the web's version of a free trialWhy "Start learning" beat "Subscribe now" for conversion in 2026How to cheaply validate a post-purchase upsell before building oneHow to turn Mixpanel free-text answers into paywall copyWhy fewer options in session one improved day one and day seven retentionKey takeaways: Anticipation peaks before first use, not after. Users had just paid $300 for a device and were hopeful — more hopeful than after their first session, which feels like a mild shock. Waiting for the aha moment meant waiting for intent to decay. Trial length moves trial starts, not trial conversion. A longer window lowers cancel-anxiety and gets more people to begin; conversion rate holds steady. Trials went 3 days to 7, then added 14 days as an exit-intent downsell at the same conversion rate. Survey the people who say no. Fewer than 10% of people who closed the paywall cited price. The top reasons were not feeling ready and feeling they'd already paid via the hardware, which redirected the roadmap from discounting to trial duration. Discounting isn't the only downsell. The winning offer was more time, not less money, priced identically to the original, converting at the same rate. A single test can produce two opposite results. Beducated's first test looked ambiguous until Applica split it by campaign ID: Meta and organic-influencer traffic needed completely different plan structures. Cold traffic needed a cheap entry point; warm traffic didn't. Plan length reflects how far ahead users can picture themselves. Removing Beducated's one-month plan for organic traffic didn't hurt conversion — rare. Trusting the influencer, users moved straight to three-month and annual plans. Settled best practices are worth retesting. A CTA test Michal almost skipped — swapping "Subscribe now" for "Start learning" — lifted conversion 20-50%, a reminder that even settled wins deserve a rerun. Your users already wrote your best copy. Alux asked users what they wanted to achieve and by when; Applica pulled every Mixpanel answer, split by converters vs. non-converters, and rewrote onboarding in converters' own words. Focus beats choice in a first session. Alux's home screen offered too many paths; Applica cut it to one goal-based block until 50% completion. Day one and day seven retention both improved. Links and resources Applica: https://applica.agency Applica case studies: https://applica.agency/case-studies Michal on LinkedIn: https://www.linkedin.com/in/michael-bardin-60b224291/Pulsetto: https://pulsetto.tech Beducated: https://beducated.com Alux: https://alux.com Botsi: https://botsi.com Timestamps01:00 Intro and what Pulsetto actually is03:30 The paywall was buried behind feature gates04:30 Moving the paywall to the end of the onboarding quiz07:00 Why the industry fetishizes the aha moment08:00 The math nobody runs: if they never see it, they can't buy09:00 The result: 9x ARR09:30 Trial start rate was 3%, trial conversion was 80%10:30 The exit-intent survey and what people actually said11:45 Trial length moves starts, not conversion14:00 RevenueCat Paywall Builder and getting independent of developers15:00 The downsell that was more time instead of less money17:30 When unique per-placement paywalls are worth building20:00 How often to show a paywall to free users22:30 Trial start rate goes from 3% to 16%23:30 Beducated and the web-to-web funnel24:30 +47% RPU on paid, +27% on organic25:00 One test, two completely different results27:00 Splitting the analysis by campaign ID28:00 Removing the monthly plan and nothing happened29:45 The weekly plan as the web version of a trial32:30 The CTA test Michal did not want to run35:00 Post-purchase upsells: PDF first, then Beducated Duo37:00 Why stacking two upsells kills the second one39:20 Alux, a $149 content app that could not lower prices41:00 Mining Mixpanel for what users wrote in their own words43:30 Converter language is the best marketing copy you have45:00 Too many options in the first session47:00 Anything completed beats no completion50:45 +22% day one retention, +26% install to paid51:00 Retention problems are activation problems52:00 Wrap and credits

    22: 9x ARR, +47% ARPU, the real tests that won with Michael Bardin | Price Power Podcast Ep. 21

  6. Aug 6

    Jonathan Parra on 4,700 Paywall Tests | Price Power Podcast Ep. 21

    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 Timestamps00:00 Intro: 4,700 paywalls and counting01:00 What Jonathan got wrong early at Superwall03:30 Predicting test results before you run them05:30  Using category benchmarks to diagnose an app07:00 The two times he was wrong, and working for free09:30 Freemium vs hard paywall, decided by cost13:00 Gating the expensive feature, freeing the cheap one14:00 Test order: design, packaging, price17:30 Demand scores from device attributes18:30 Age-based price testing and why it's risky20:30 What changed post-AI in the testing workflow23:30 Why the ugly paywall wins27:30 Building a real exit flow28:30 The questionnaire that replaced the discount ladder31:00 The exact questions he asks34:30 The five paywalls every new app should ship38:30 Trial cancelers: the 5 to 6 percent win-back40:30 Downgrades, discount depth, and brand42:00 Transaction abandon tactics44:00 Winning back expired subscribers48:30 Email, push, SMS, and where the ceiling is51:30 Weekly plans and the TikTok wall54:00 Biggest packaging win: multi-page paywalls

    Jonathan Parra on 4,700 Paywall Tests | Price Power Podcast Ep. 21

  7. Jul 14

    20: Opal Killed the Quiz Funnel. What's up next?

    Opal rebuilt their onboarding to work like a chat thread instead of a quiz, and Jacob walks through the whole thing screen by screen. The rock you crack open on the first tap, the sign-in question that replaced the sign-in buttons, the moment they tell you you'll spend eighteen years of your life looking at your phone, the paywall, and the monthly plan they only offer you if you try to leave. This is a solo episode, so it goes deeper on the screens than a conversation usually allows. An app at Opal's scale doesn't ship an onboarding redesign without testing it hard first, which makes it a useful thing to study. The question isn't whether it works. It's which pieces of it would work for you. What you'll learn: • Why the first screen of your app is probably leaking more users than your paywall is• How Opal replaced the Log in / Sign up wall with a question• Why more login options usually pay for themselves once you scale• The phrasing trick that gets people to answer a demographic question honestly• Why Opal asks about your screen time before asking for screen time permissions• How they split their permission requests apart, and what they put in between• The three-beat setup: 91 days this year, 18 years of your life, then the rescue• How paywall copy pays off a goal the user selected five screens earlier• Why the trial reminder screen has almost nothing to do with reminders• What "design your trial" is really doing to the user's decision• The math behind pulling monthly off your first paywall• The exit-intent monthly offer that almost nobody runs• Why "no payment due now" keeps showing up next to the CTA• What the Law of S****y Clickthroughs says about the future of quiz onboarding• The screen-count test for whether chat onboarding fits your app Links & resources • Retention.blog full written breakdown: https://retention.blog• Opal: https://opalapp.com/• Andrew Chen, "The Law of S****y Clickthroughs": https://andrewchen.com/the-law-of-s****y-clickthroughs/• Botsi: https://botsi.com 00:00 Intro: tired of quiz-style onboarding?01:05 Opal's chat-style redesign01:28 The rock you crack open02:34 Why first-screen drop-off compounds03:15 "Have we met before?" instead of Log in / Sign up03:58 Login options and the data reassurance copy04:22 The hybrid quiz/chat question style05:31 "What best describes you?"06:21 Easing into the screen time permission07:44 91 days, 18 years, and the aha moment09:07 Splitting the permission asks apart10:00 The personalized pre-paywall screen11:38 The fist bump commitment prompt12:15 "Two plus hours" and a copy critique13:23 Social proof and the "Reclaim my time" CTA13:55 The trial reminder screen15:47 Design your trial16:13 The math on removing monthly18:06 "Not ready for a year?"18:27 The "no payment due now" checkbox20:08 Post-paywall onboarding and gamification22:15 The Law of S****y Clickthroughs23:27 Why chat UX works right now23:54 Which apps should actually test this25:19 Teaser: the onboarding and paywall library

    20: Opal Killed the Quiz Funnel. What's up next?

  8. Jun 25

    19: Lessons From Reviewing 100+ Web Funnels w/ FunnelFox CEO

    Andrey Shakhtin, founder and CEO of FunnelFox, explains why web subscriptions convert and monetize better than the app store, how to stand up a minimum viable web-to-app test, and the payment risks that can freeze your revenue once you scale. What you'll learn: • Why full-funnel conversion (impression to purchase) runs roughly 2x higher on web than in-app, and how the app store install step explains the gap• Why web LTV is about 2x in-app on annual plans and at least 50% higher on monthly• The two structural reasons web LTV is higher: quiz funnels skew toward older, higher-willingness-to-pay buyers, and you control retention end to end• How owning the payment stack lets you run custom cancellation flows and dunning (failed-payment recovery) that Apple and Google never expose• Why deterministic post-ATT attribution makes web the fastest creative-testing loop you have• Why a web funnel is the cheapest way to validate a product, sometimes before the app exists• Why free trials quietly poison your Meta optimization, and how a $1-$5 paid trial fixes the signal• The unit-economics benchmarks that matter: roughly 40-60% day-zero ROAS and a 6-month payback• Why most "amazing-looking" funnels still fail at the paywall and checkout• How to structure a paywall: outcome-based value, visualization, FOMO, price, then social proof• The real difference between refunds, disputes, and chargebacks, and why only chargebacks threaten your account•  How dispute-rate and VAMP (Visa's acquirer monitoring) thresholds can get your PSP to freeze recurring revenue•  Why chargeback-alert services and external billing (payment orchestration) are close to mandatory at scale•  How an easy refund path plus a 50% save offer lowers chargebacks and protects net revenue•  How post-purchase upsells add roughly 20% LTV without triggering disputes Key Takeaways: A web funnel is the cheapest validation you have. Test demand, pricing, even a niche for a few hundred dollars a day before committing engineering. Some teams launch with no product at all, then build the app for the niche that converts. Web's edge is deterministic measurement. With no ATT loss, every purchase ties to an exact creative, so you iterate on message and audience by real numbers instead of inferring from installs. The full funnel converts about 2x on web. You skip the app store install decision, a friction point where lukewarm users drop before they ever see the offer. Most teams miss it because they optimize to installs. Paid trials protect your ad signal. A $1-$5 charge proves the card works and sends Meta a real purchase event, so it optimizes toward payers instead of trial-tourists who never convert. The paywall is where funnels die. After ~100 funnel reviews, it's the most under-built step. "Unlock all features" is not value. Lead with a specific outcome and date, and build it like a landing page. Chargebacks can freeze everything. Refunds are harmless, but cross a provider's dispute or VAMP threshold and it can lock all stored recurring revenue. Make refunds easy and offer a 50% save to keep subscribers. Links & Resources FunnelFox: https://funnelfox.comState of Web-to-App Subscriptions report: https://funnelfox.com/state-of-web2app-2026Andrey Shakhtin on LinkedIn: https://www.linkedin.com/in/andrey-shakhtin/ Timestamps 00:00 Andrey's path: 16 years in mobile, from code to growth to FunnelFox04:30 The minimum viable web-to-app experiment08:00 What scale you need first, and validating a niche with no product10:00 Why web should complement, not replace, your other channels13:30 How web monetization differs from in-app16:00 The report: web LTV and conversion roughly 2x in-app16:40 Why web LTV is higher: older buyers and full retention control19:00 Why the app store install step kills conversion21:00 Organic vs. paid traffic funnels22:30 Free trials vs. paid trials, and the Meta signal25:30 Why web-to-app projects fail28:30 Unit economics: day-zero ROAS and the 6-month payback29:30 Diagnosing a broken funnel against benchmarks36:00 How to structure a paywall that converts41:30 Intro offers and the telecom playbook44:30 Refunds, disputes, chargebacks, and VAMP explained51:00 Defending your payment account: alerts and external billing55:30 The refund hack: offer 50% instead of losing the subscriber57:30 Upsells and lifting LTV ~20%59:30 Biggest pricing win: GLP-1 and $800 order values01:00:30 What FunnelFox does

    19: Lessons From Reviewing 100+ Web Funnels w/ FunnelFox CEO
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About

The Price Power Podcast is for all things growth, retention, and monetization for subscription mobile apps. We talk with amazing leaders in the industry to help share their knowledge with you. Hosted by Jacob Rushfinn, CEO of Botsi.

Information

  • Creator
    Jacob Rushfinn
  • Years Active
    2025 - 2026
  • Episodes
    26
  • Rating
    Clean
  • Copyright
    © 2025 Botsi Inc.
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    Price Power