Most mobile app teams are sitting on at least 20–40%+ additional revenue from their current paywall and onboarding setup.
We've worked with 27+ apps over the years. And we've seen 2 main problems hold teams back from unlocking it, again and again:
Problem 1: Random testing. Teams run tests by guessing and copying other apps, without a data-backed system in place. They inevitably pull the wrong levers first and see no meaningful uplift in trial-start, trial-to-paid, or install-to-paid conversion rates.
Problem 2: A non-existent testing cadence. Teams know the right levers to pull, but engineers and designers can't be taken off core product work. meaning nothing gets shipped in the end.
Roastmyapp's paywall & onboarding CRO program is carefully designed & battle-tested to solve them both.
While most app growth consultants and agencies stop at hypotheses, wireframes, or a strategy roadmap, we go the extra mile with full end-to-end implementation in Swift, React Native, or your no-code stack.
If you're a mobile app team wondering what it's really like to work with us, this guide covers everything for you. From the groundwork we do, to the experiments we ship, to the deliverables you walk away with. Let's dive in.
What it is: A monthly engagement where we take ownership of your mobile app's monetization metrics & post-install funnel.
What we ship: At least 3–4 paywall experiments and 1–2 onboarding funnel iterations per month.
How it works: We join your team → do intensive customer & competitor groundwork → find your highest-leverage paywall and onboarding experiments → design, code, and deploy them for you or with you.
The outcome: You move from random testing to systematic growth without pulling your engineers off core product work. You unlock 10–50%+ additional revenue per user without increasing your marketing spend.
Every experiment we run maps to one of 11 high-leverage focus areas across your monetization funnel. For each area, we track a specific set of primary metrics and pair every test with guardrail metrics, so a win in one place never quietly creates a loss somewhere else.
Note: our program also cover post-onboarding areas like cancellation flow, feature activation & retention mechanism. Meaning, we'd optimize for everything that would typically happen at D0 of your user journey.
Your store listing is the first conversion surface in the funnel. We test App Store screenshots, icon variations, and product page presentation to improve how efficiently impressions turn into installs.
Primary metrics: product page view → install conversion rate, impression → install rate.
What to potentially test: screenshot narratives and ordering, icon changes, localized store creative for high-potential geos.
70-80%+ trial starts and subscription purchases happen at D0, typically on your user's very first session. That makes onboarding the biggest monetization lever for your app.
We optimize the welcome screen block, the quiz funnel narrative, the number of screens, and how the value moment (the aha moment) and habit loop are set up, to find the best-performing onboarding variant.
Primary metrics: onboarding completion rate, install → paywall view, install → trial-start rate (day-0 conversion).
What to potentially test: quiz depth and personalization, screen count and ordering, where and how the aha moment lands before the paywall.
When & where you show the paywall matters as much as what's on it. Common placements include the end of the onboarding funnel, the very start of onboarding, gated features, and free-tier usage limits—where users can experience the app or perform an action a set number of times before their usage is paywalled.
Primary metrics: install → paywall-view rate, paywall view → trial-start conversion by placement.
What to potentially test: onboarding-end vs. onboarding-start, feature gating, usage-limit triggers, transaction and session-based placements.
This is your paywall's offering: trial length (or no trial at all), plan structure, and price points. Small packaging changes here often produce outsized revenue-per-user shifts.
Primary metrics: trial-start rate, trial-to-paid conversion, ARPU, plan mix.
What to potentially test: 3-day vs. 7-day vs. no-trial offers, weekly vs. annual anchoring, lifetime plans, price localization.
The visual architecture of the paywall: single-screen with vertical scroll vs. a multi-step paywall that breaks content across screens, headline hierarchy, layout and purchase mechanism.
Design is one of the highest-leverage moves because it controls how the offer is perceived before a single word is read.
Primary metrics: paywall view → trial-start conversion, paywall view → purchase conversion.
What to potentially test:single-screen vs. multi-step formats, social-proof-led layouts, visual hierarchy of price and CTA, in-app vs app2web checkout.
How your app speaks to your customers matters a lot more than you think. Mainly your screen headlines, feature-led vs. outcome-led framing, and where social proof appears.
For example, a paywall that leads with social proof and nothing else can outperform a feature list.
Primary metrics: paywall conversion rate, onboarding completion rate.
What to potentially test: outcome vs. feature headlines, voice-of-customer copy pulled from our research, social proof positioning at friction points.
Price-sensitive users actively look for a better deal before committing. A carefully designed promotions strategy captures that segment and unlocks extra revenue instead of losing it.
Primary metrics: offer redemption rate, incremental revenue per user, transaction-abandonment recovery.
What to potentially test: win-back offers, limited-time discounts, abandonment-triggered promotions.
Your paywall doesn't have to be one-size-fits-all.
We adapt paywall content based on users' onboarding quiz inputs, their traffic source, and even real-world context (certain tools can detect whether a user is outdoors, lying down, or standing). Matching the paywall to the person raises conversion without touching price.
Primary metrics: segment-level paywall conversion, ARPU by segment and traffic source.
What to potentially test: quiz-input-driven paywall variants, source-matched messaging, context-aware content.
Most apps drop users straight into the product the moment they subscribe.
The better approach is a deliberately designed post-purchase experience that reassures users of their purchase decision, using screens they see immediately after starting a trial or buying a subscription.
Primary metrics: trial-to-paid conversion, refund rate, D0 cancellation rate.
What to potentially test: purchase confirmation flows, trial-timeline transparency screens, first-session activation prompts after purchase.
Core feature adoption & reetention are commonly overlooked monetization levers. We help you design a habit-forming loop that users can move through continuously, bringing them back to the app again and again.
Primary metrics: D7/D30 retention, subscription renewal rate.
What to potentially test: core loop design, trigger design (notifications, streaks), reward mechanics, loop friction reduction.
The subscription cancellation flow is the last [and most neglected] conversion surface. A well-designed flow paired with the right retention offer incentivizes users who are about to churn to stay, and can unlock additional revenue on its own.
Primary metrics: save rate, churn rate, retention-offer acceptance rate.
What to potentially test: cancellation-reason surveys, pause offers, discounted retention offers.
We never start designing solutions or forming hypotheses cold. Every focus area above gets intensive groundwork first—a research layer combining internal customer context with external competitive intelligence.
Phase-1 Customer Research:
We start with your internal context. We ask app teams to share their existing research materials: user interview transcripts, surveys, App Store reviews, feature request logs, and support tickets. This tells us what your users are actually looking for and what they ideally want from you.
Then we go external. Using our own Claude-powered research skills, we mine what your competitors' customers are saying on their App Store reviews, Reddit threads, Trustpilot pages, and other public feedback. In this stage, we're looking for a specific set of signals:
— Core job-to-be-done of your app's users
— Pain points, desires, and triggers which made them finally try or buy
— Objections and hesitations, before and after purchase
— Outcome / results they actually got
— The exact words and phrases they use to describe their problem
— How they compare options, why they churn
— Which trust signals made them feel safe to pay
The output is a structured voice-of-customer worksheet that becomes the starting point for writing your onboarding and paywall copy.
Real customer language converts better than polished marketing speak. Every bit of onboarding & paywall content we write can be traced back to something a real user said.
Phase-2 Competitor Research:
Our competitor research typically covers 30–50 apps in your category, mapped screen-by-screen on a Figma board. It includes:
— Full funnel teardowns: screenshots of the entire journey — App Store listing → install → onboarding → paywall → subscription purchase. We start trials ourselves to document post-onboarding UX too.
— Ad library analysis: Meta, Apple, and TikTok ad libraries to see what creatives and angles competitors run, whether they route users to web funnels or App Store product pages, and which localized geos they're investing in (localized Apple Ads in even one country is a signal that geo is profitable).
— Monetization efficiency estimates: revenue and download estimates from Appfigures and AppMagic. Dividing revenue by downloads surfaces the apps converting unusually well. Example: high revenue on low downloads is a signal their onboarding, paywall, or monetization setup is working.
— Tier ranking: we rank competitors into 5 tiers, so we know exactly which players to keep a close eye on for new paywalls and tactics.
The goal is NOT to blindly copy competitors, but to spot common patterns across top-grossing apps and the underlying psychological persuasion triggers they use. We build our solution with evidence-backed rationales, and then test what fits your funnel.
What our stack typically looks like:
— Subscription & revenue analytics: Appstore Connect, RevenueCat, Superwall, Adapty, Purchasely or Qonversion
— Product analytics: Mixpanel, Amplitude, PostHog
— Test setup: RevenueCat/Superwall no-code builders, or custom-coded experiments in your stack (Swift / React Native / Flutter )
— Store & funnel intelligence: Appfigures, AppMagic
— Research & hypothesis generation: Claude, Figma, ScreensDesign & Mobbin
What we ask from clients at kickoff:
— Read-only access to analytics mentioned above
— Top-of-funnel context: Apple Ads keywords, UGC and creative scripts, best-performing ad creatives and angles you know convert
— Existing research materials: interview transcripts, surveys, reviews, feature requests, support tickets
— Your experimentation backlog, designs & data from previous tests
The primary goal of the program is to build systems to increase your revenue per user. In broad picture, this means moving 4 numbers:
— Install → paywall-view rate: more users actually reaching the offer
— Install → trial-start rate: better-converting day-0 onboarding funnel
— Trial-to-paid (or install-to-paid) conversion: an offer, paywall, and post-purchase UX that turns trials into revenue
— 1st subscription renewal rate: retention loops and cancellation flows that keep subscribers past week-1 or month-1 or year-1.
Here's a hypothetical scenario of what compounding wins across those metrics look like:
Health & fitness app getting 100,000 installs a month with a 60% paywall-view rate, 8% trial-start rate, and 35% trial-to-paid converts roughly 1,680 new paid subscribers monthly.
Lift paywall views to 75% (placement tests), trial starts to 11% (onboarding + paywall design tests), and trial-to-paid to 42% (pricing, packaging & post-purchase tests).
The same 100,000 installs now produce ~3,465 paid subscribers, more than 2x the revenue with zero extra marketing spend.
That's the mechanism behind the additional revenue our clients typically unlock. Teams who are sitting on untouched monetization levers are basically leaving 20–40%+ cashflow on the table.
1. Your CRO & experimentation roadmap: a google sheet that your team can use as a single-source-of-truth backlog, structured with our problem-solution-impact framework, and prioritized with a RICE scorecard so you always know what to test or ship first.
2. Our complete customer & competitor research worksheet: the full voice-of-customer output covering pain points, desires, objections, triggers, and the exact language your market uses.
3. Access to our Claude skills, internal swipe files and research materials we build during our engagement is also shared with your team for later use.
4. Hypothesis & impact brief for every experiment: what to test (and what not to test), the primary metrics we expect to move, and the trade-offs and guardrail metrics to keep an eye on.
5. Dev-ready paywall & onboarding UI designs, prototypes + [codebase/github repo if roastmyapp team's also taking on the engineering work for you]
You'll primarily be working with me, Muhammad Rahat, as your direct point of contact.
For mature-stage apps or projects that require accelerated velocity, I bring in vetted growth product managers and senior growth designers depending on scope. And when engagements include developer-heavy implementation, we bring in our specialist devs and analytics experts.
It's a deliberately small A-team that embeds easily into your existing growth team. The whole point is to increase your experiment velocity, not add coordination overhead.
The paywall & onboarding CRO program is a monthly engagement. Here's the operating rhythm:
1. We join your team. We plug into your existing team structure and cadence — as a fully embedded revenue growth partner or a fractional CRO consultant.
2. We do the groundwork. Customer research, competitor research, and analytics review to find your highest-leverage paywall and onboarding experiments to run next.
3. We design, code, and deploy. At least 3–4 paywall experiments and 1–2 onboarding funnel iterations ship per month, with implementation on RevenueCat, Superwall, or custom code.
4. We help you move from random testing to systematic growth without pulling your engineers off core product work.
Depending on your situation, we can guide your existing designers & developers, or we can bring in our own designers & developer to ship experiments for you.
Either way, we take ownership of your key monetization metrics end to end [from design, code, analytics, to test setup].
If your app team is stuck between random testing and a backlog your engineers can't get to, this paywall & onboarding CRO program was built for you.
Book a free CRO audit and we'll show you the highest-leverage paywall and onboarding experiments you're sitting on right now, on a 30-min intro call.
