Welcome to RevenueCat's Monetization Strategies Codelab!
Turning downloads into revenue is one of the biggest challenges for app developers. According to RevenueCat's State of Subscription Apps 2025, only 1.7% of app downloads convert to paying subscribers within 30 days. However, top-performing apps achieve 4.2% conversion rates, more than double the median. The difference? Strategic monetization optimization.
In this codelab, you will learn how to:
By the end of this codelab, you'll have a complete monetization toolkit to significantly increase your app's revenue.
Before you start, ensure you have a RevenueCat account with a configured project, an Android or iOS project with RevenueCat SDK integrated, products and entitlements configured in your RevenueCat dashboard, and a basic understanding of Offerings and Paywalls.
Understanding where you stand helps you set realistic goals. The median 14-day ARPU across all apps is $0.31, while top quartile apps achieve $0.89. Health & Fitness apps lead with a median of $0.44. For trial conversions, 38% of users who start a trial convert to paid, but top quartile apps with trials longer than 4 days see conversion rates exceeding 60%.
The opportunity is clear: there's significant room between median and top performance. Let's explore how to close that gap.
Your paywall is the most critical screen in your app for revenue. Even small improvements can impact performance by tens of percentage points. According to RevenueCat's research, 82% of trial starts happen on the same day a user installs an app, meaning you often get only one chance to convert.
The timing and location of your paywall significantly impacts conversion. There are several placement strategies to consider, each serving different user intents and moments in the user journey.
The Onboarding Paywall appears immediately after the user completes onboarding. This strategy captures high-intent users while their motivation is fresh. When someone has just downloaded your app, they're at peak curiosity and engagement. Apps like Mojo report that onboarding paywalls drive over 50% of their trial conversions. The key insight here is that users who just installed your app did so for a reason. They experienced a problem, researched solutions, chose your app, and took the effort to download it. This intent is powerful, and presenting your value proposition immediately capitalizes on that momentum.
The Contextual Paywall appears when users attempt to access premium features. This targets users who have demonstrated interest in specific functionality. The psychology here is different from onboarding. These users have already explored your app, found something they want, and hit a boundary. They're now making a conscious decision about whether that specific feature is worth paying for. The advantage of contextual paywalls is that users understand exactly what they're paying for, which can lead to higher-quality conversions and better retention.
The Settings Paywall is accessible from the app settings for users who want to upgrade later. This serves as a safety net for users who weren't ready initially but may reconsider. Some users need more time to evaluate your app before committing. Having an easily accessible upgrade path in settings respects this decision-making process while ensuring they can convert when ready.
RevenueCat's Placements feature lets you define unique offerings for each paywall location. This means you can show different prices, different trial lengths, or entirely different product configurations depending on where in your app the user encounters the paywall. A user hitting a premium feature gate might see a monthly option prominently, while a user in onboarding might see an annual plan with a longer trial.
One of the most effective psychological techniques is price anchoring. By showing multiple pricing options, you help users perceive value through comparison rather than evaluating a single price in isolation.
Consider this real-world example: a productivity app tested showing only an annual plan versus showing both monthly and annual options side by side. The result was a 31% increase in annual subscriptions when both options were displayed. Why? Because users could now compare. The monthly price of $9.99 made the annual price of $59.99 (effectively $4.99/month) look like an obvious bargain. Without that comparison point, users had to evaluate $59.99 against their general sense of "is this worth it," which is a much harder mental calculation.
The principle extends beyond just monthly versus annual. You can anchor with a premium tier to make your standard tier seem reasonable, or with a lifetime purchase to make annual subscriptions feel like lower commitment. The key is giving users a reference point that makes your preferred option feel like the smart choice.
Based on hundreds of paywall tests, certain elements consistently drive conversions across different app categories and audiences.
A clear value proposition explains what users get in 2-3 bullet points, focusing on outcomes rather than features. Instead of "Access to 500+ templates," try "Create professional designs in minutes." Users don't buy features; they buy solutions to their problems and improvements to their lives. Your paywall copy should speak to the transformation they'll experience.
Social proof builds trust through ratings, user counts, or testimonials. When users see that millions of others have subscribed, or read a testimonial from someone like them who got results, it reduces the perceived risk of subscribing. This is especially powerful for apps where the value isn't immediately obvious or takes time to realize.
Risk reduction emphasizes free trials, money-back guarantees, or "cancel anytime" messaging. Subscription anxiety is real. Users worry about being locked into something they might not use. Prominently communicating that they can cancel anytime, or that they won't be charged during the trial, removes a significant psychological barrier.
Urgency creates time pressure with limited-time offers, but use this sparingly and honestly. False urgency damages trust. Genuine urgency, like a seasonal promotion or a special offer for new users that truly expires, can effectively encourage immediate action from users who might otherwise procrastinate.
For more detailed guidance on these elements, see 5 Overlooked Paywall Improvements That Drive More Conversions.
Intuition-based decisions often fail in surprising ways. What seems like an obvious improvement might actually hurt conversions, while counterintuitive changes sometimes produce remarkable results. This is why paywall optimization requires data, and RevenueCat Experiments lets you A/B test different offerings to discover what actually works for your specific audience.
Paywall experiments have the potential to boost revenue by up to 40%, according to industry research. But the value of testing isn't just in finding winners. It's equally valuable in preventing costly mistakes. Many teams have confidently rolled out changes they expected to improve conversions, only to discover through later analysis that they actually hurt revenue. With proper A/B testing, you catch these issues before they affect your entire user base.
The goal of any experiment is to understand which configuration yields the highest lifetime value (LTV) per customer. This is crucial because initial conversion rate alone can be misleading. A lower price might convert more users initially, but if those users churn faster or have lower engagement, the higher price might actually produce more revenue over time. RevenueCat Experiments tracks the full subscription lifecycle, giving you visibility into these downstream effects.
The process begins in your RevenueCat dashboard. First, create the variant offerings you want to test. For example, your Control Offering might include a monthly plan at $9.99 with a 7-day trial, while your Treatment Offering tests a higher price point of $12.99 monthly with a 14-day trial. The combinations you test should be based on hypotheses about your users. Perhaps you believe a longer trial will increase conversions enough to offset any hesitation about the higher price.
Next, configure the experiment itself by navigating to Experiments in your dashboard. Select your control and treatment offerings, set your traffic allocation (typically 50/50 for faster statistical significance), and define how long you want the experiment to run. RevenueCat will randomly assign users to each variant and track their behavior over time.
The beauty of RevenueCat Experiments is that no code changes are required if you're already fetching the current offering in your app. When you call Purchases.sharedInstance.awaitOfferings(), RevenueCat automatically returns the correct offering based on which experiment variant the user has been assigned to. All the complexity of user assignment, tracking, and analysis happens server-side. Your app simply displays whatever offering it receives, and RevenueCat handles the rest.
While price testing is the most common experiment, the experimentation framework supports much broader exploration of your monetization strategy.
Subscription duration is a fundamental variable to test. Some audiences prefer the lower commitment of monthly subscriptions, while others are drawn to the savings of annual plans. Some apps have found success with weekly subscriptions for highly engaged users. Testing weekly versus monthly versus annual helps you understand your users' preferences and price sensitivity.
Trial length significantly impacts both conversion and retention. The intuition that longer trials are always better doesn't hold universally. Compare 3-day, 7-day, and 14-day trials for your app. Some apps find that shorter trials create urgency that drives faster decisions, while others need longer trials to demonstrate value. Habit-forming apps like fitness trackers often benefit from longer trials because users need time to experience the transformation.
Introductory pricing offers another dimension to explore. Test different discount levels to find the sweet spot: 50% off the first month versus a free trial versus a pay-up-front annual discount each appeals to different user psychologies. Some users are skeptical of "free" and prefer a small upfront commitment, while others won't try anything without a no-risk free trial.
Paywall design encompasses layout, copy, images, and call-to-action buttons. Even small changes like button color, headline text, or the order in which plans are displayed can meaningfully impact conversion. RevenueCat Paywalls combined with Experiments lets you test these visual elements without app updates.
RevenueCat tracks the full subscription lifecycle, not just initial conversions. When analyzing your experiment results, consider several key metrics together.
Initial Conversion Rate tells you what percentage of users who see the paywall start a trial or subscribe. This is your top-of-funnel metric and the most immediate indicator of whether a change is working.
Trial-to-Paid Conversion reveals how many trial users actually become paying subscribers. A variant might have a higher trial start rate but lower trial-to-paid conversion, resulting in fewer paying customers overall. This is why looking at the complete funnel matters.
Revenue per Customer is the ultimate metric that combines conversion rate, price, and retention. A higher price with slightly lower conversion might still produce more revenue. RevenueCat's dashboard shows you realized LTV for each variant, accounting for all these factors.
Retention patterns can differ between variants. Do higher-priced subscribers retain better because they're more committed, or do they churn faster because expectations are higher? Only by tracking long-term behavior can you answer these questions.
Wait for statistical significance before declaring a winner. RevenueCat's dashboard shows confidence levels to help you make informed decisions. Ending experiments too early based on preliminary results can lead to wrong conclusions that hurt your business long-term.
For more testing ideas, see 10 Price Test Ideas for Your Subscription App.
Not all users are the same, and treating them identically leaves money on the table. A user in their first session has different needs, different price sensitivity, and different decision-making context than a user who's been using your app for 30 days. RevenueCat Targeting lets you serve different offerings to different audiences, enabling sophisticated personalization without complex app-side logic.
Research shows that personalizing your paywall with something as simple as a user's first name can boost conversions by up to 17%. But personalization goes far beyond names. You can customize pricing, trial lengths, feature bundles, and messaging based on user attributes and behavior.
The underlying principle is relevance. When users see an offer that feels tailored to their situation, they're more likely to perceive it as valuable and act on it. A power user who's been using your app daily for a month sees the value clearly and might respond best to premium annual pricing. A new user who just installed might need an extended trial to experience that same value before they're willing to pay.
RevenueCat Targeting supports multiple dimensions that you can combine to create sophisticated audience segments.
Country and Region targeting enables localized pricing for different markets. Users in countries with lower average incomes might convert better at lower price points, while users in high-income countries might actually perceive higher prices as indicating higher quality. Regional targeting also allows you to respect local purchasing power and competitive dynamics.
Platform targeting recognizes that iOS and Android users often have different behaviors and price sensitivities. Research consistently shows differences in average spending between platforms. You might offer different price points or emphasize different billing periods based on platform.
App Version targeting lets you test new offerings with users on the latest version before rolling out broadly. This is useful for introducing new products or pricing strategies gradually.
Custom Attributes provide the most powerful targeting capability. You can send any data to RevenueCat about your users, such as their engagement level, how many days since install, which features they've used, or how they discovered your app, and then create targeting rules based on these attributes.
Regional pricing is one of the most impactful targeting strategies. Create different offerings for different countries, with prices adjusted to local purchasing power. In your RevenueCat dashboard, create targeting rules that serve specific offerings based on the user's country. Your app code doesn't need to know about any of this; it simply requests the current offering, and RevenueCat returns the appropriate one based on the user's location.
Engagement-based offers recognize that users at different stages of their journey respond to different value propositions. By tracking session count or feature usage as custom attributes, you can create targeting rules that serve different offerings to different engagement levels. Power users who've had 10+ sessions might see premium annual pricing because they clearly see value. New users with fewer than 3 sessions might receive an extended trial to give them more time to experience that value.
Win-back targeting helps you recover churned subscribers. RevenueCat automatically tracks subscription status, so you can create targeting rules that serve special discount offerings to users whose subscriptions have expired. These users already know your app and chose it once; a compelling win-back offer might bring them back.
Platform-specific pricing acknowledges the behavioral differences between iOS and Android users. You might find that Android users are more price-sensitive and respond better to lower price points, while iOS users convert better on annual plans. Configure separate offerings per platform in your targeting rules to optimize for each audience.
For 24 detailed targeting strategies, see 24 Ways to Optimize Pricing, Packaging, and Paywalls Using Targeting.
The real power emerges when you combine these features. You can run experiments within specific targeted segments, learning what works for different user types simultaneously.
For example, create a targeting rule for "power_users" based on high session counts. Within that segment, run an A/B test comparing premium pricing strategies. Separately, target "new_users" with a different experiment testing trial lengths. This approach lets you optimize for different user segments in parallel, building a nuanced understanding of your diverse user base.
The first price a user sees is one of the most powerful conversion levers available to you. Introductory offers and free trials reduce the perceived risk of trying your subscription, giving users a chance to experience value before committing financially. RevenueCat makes it easy to configure and display introductory offers across platforms.
To maximize conversions, you need to leverage introductory offers, offer codes, and promotional offers effectively. RevenueCat Paywalls make it easy to configure and display these offers to the right customers at the right time, without writing endless custom logic. For a comprehensive guide on supercharging your paywalls with offers, check out Unlocking Growth: How to Supercharge Your Paywalls with Offers.
Free Trials give users full access for a period before being charged anything. This is ideal for apps that need time to demonstrate value, such as habit-building apps, learning platforms, or productivity tools where the benefit compounds over time. The psychology is powerful: users can experience your full premium offering without risk, and by the time the trial ends, they've (ideally) integrated your app into their routine.
Pay Up Front offers require one reduced payment for multiple periods, such as $0.99 for 3 months. This model creates some initial commitment, which can actually increase conversion-to-paid rates compared to free trials. Users who pay even a small amount feel more invested and are more likely to continue. It's also useful for apps where a longer evaluation period is beneficial but you want to filter for users with genuine intent.
Pay As You Go offers provide a reduced rate each period for a number of periods, like $0.99/month for the first 3 months. This model eases users into your full pricing gradually, reducing sticker shock while still collecting some revenue during the introductory period. It works well when you want to demonstrate ongoing value and let users see what they're getting each month.
You configure introductory offers in App Store Connect for iOS and Google Play Console for Android. Each platform has its own mechanics, but RevenueCat normalizes these differences for you. Once configured in the stores and linked to your RevenueCat products, the SDK automatically handles eligibility checking and displays the appropriate offer information.
When presenting offers on your paywall, clarity is essential. Users should immediately understand what they're getting: how long the introductory period lasts, what they'll pay (if anything), and what the price becomes afterward. Ambiguity about pricing creates anxiety and reduces conversions. Display the introductory offer prominently, but always show the regular price they'll pay after, typically phrased as "then $X/month" or similar.
RevenueCat Paywalls handle much of this automatically when you use the built-in paywall components. The offer information is rendered based on what's configured in the stores, ensuring accuracy and reducing the risk of displaying incorrect pricing.
Not all users are eligible for introductory offers. Once a user completes an introductory offer for any product in a subscription group, they're typically no longer eligible for introductory offers on other products in that group. RevenueCat provides eligibility checking so you can accurately display whether a user qualifies for the introductory pricing.
This matters for your paywall design. If you're showing a "7 Days Free" badge but the user isn't actually eligible, you've created a negative experience when they discover they can't get the offer. RevenueCat's SDK provides eligibility information so you can conditionally show offer details only to eligible users.
The right trial length varies significantly by app category and business model. Understanding the tradeoffs helps you make informed decisions and design good experiments.
Short trials of 3-4 days create urgency and work well for apps with an immediate value proposition. If users can experience the core benefit quickly, a short trial pushes them toward a decision while their intent is still high. Dating apps, entertainment apps, or apps with immediately compelling features often succeed with shorter trials.
Medium trials of 7 days represent the most common choice and provide a balance between demonstration time and decision urgency. A week gives users enough time to experience your app across different contexts and days while still feeling like a defined evaluation period.
Long trials of 14+ days suit apps where value realization is gradual. Fitness apps, habit trackers, language learning apps, and similar products benefit from longer trials because users need time to experience the transformation your app enables. A user won't see results from a fitness app in 3 days, so a longer trial makes sense.
According to RevenueCat's State of Subscription Apps 2025, over half (52%) of all trials are now offered for 5-9 days, up from 48.5% in 2023. Shorter trials of 4 days or less are declining. This suggests the industry is converging on medium-length trials, but your optimal length depends on your specific app and should be validated through experimentation.
Acquiring a new subscriber costs significantly more than retaining an existing one. Every subscriber who churns represents not just lost revenue, but wasted acquisition cost. RevenueCat's Customer Center helps you reduce churn by intercepting users before they cancel and offering alternatives that might keep them as customers.
Customer Center is a self-service UI that helps subscribers manage their subscriptions directly within your app. Users can see their current plan, change subscriptions, restore purchases, and yes, cancel. But the real power lies in what happens during that cancellation flow.
When a user initiates cancellation, Customer Center presents a survey asking why they're leaving. Based on their answer, you can present targeted retention offers designed to address their specific concern. A user canceling because of price sees a discount offer. A user canceling because they don't use the app enough sees tips for getting more value or an option to pause. This intervention happens at exactly the right moment, when the user has decided to cancel but hasn't yet completed the action.
Why do retention offers work? Because cancellation is often not a firmly decided conclusion but a tentative decision open to reconsideration. Users frequently cancel not because they hate your product, but because of circumstantial reasons: tight budget this month, temporarily not using the app, or frustration with a specific issue. A well-timed offer that addresses their stated concern can flip that decision.
The cancellation moment is also unique because you're not asking users to do something new. They've already subscribed, used your app, and presumably found some value. You're simply giving them a reason to continue something they've already started. This is psychologically easier than acquiring a new subscriber who has to make a fresh commitment.
In your RevenueCat dashboard, you configure the cancellation survey options that users see. Common reasons include "Too expensive," "Don't use the app enough," "Found a better alternative," "Missing features I need," "Technical issues," and "Just trying it out."
Each reason represents a different objection that requires a different response. "Too expensive" is a clear signal for a discount offer. "Don't use the app enough" might warrant tips for getting more value, or an option to pause the subscription for a month. "Missing features" is an opportunity to collect feedback and potentially offer to notify them when specific features ship.
The survey serves dual purposes: it enables targeting of retention offers, and it provides valuable feedback about why users leave. Even if you can't save every canceling user, the aggregated data tells you what to improve.
For users who select "Too Expensive", a discount is the obvious response. Offer 20-50% off the next billing period, or present a downgrade option to a cheaper tier if you have one. The key insight is that some revenue is better than no revenue. A user paying half price for another few months might eventually convert back to full price, and you avoid the acquisition cost of replacing them.
For users who select "Don't Use Enough", the issue isn't your app's value but rather the user's engagement. Consider offering to pause their subscription for a month rather than cancel entirely. Alternatively, surface tips for getting more value from the app, or highlight features they might not have discovered. If you can re-engage them, you've solved the underlying problem rather than just delaying the cancellation.
For users who cite "Missing Features", use this as a feedback opportunity. Collect the specific features they need and offer to notify them when those features become available. You might not save the subscription today, but you've gathered valuable product feedback and created a potential win-back opportunity.
For iOS apps, RevenueCat integrates with Apple's Retention Messaging API. This powerful feature lets you reach subscribers at the exact moment they choose to cancel through iOS Settings, outside of your app entirely. When a user goes to their iPhone settings and taps to cancel your subscription, you can display a message or incentive directly within Apple's system subscription management screen.
This extends your retention reach beyond users who cancel within your app. Configure retention messages in the RevenueCat dashboard alongside your Customer Center settings to create a comprehensive cancellation interception strategy.
Track these metrics to understand the impact of your retention efforts. Save Rate measures the percentage of users who view a retention offer and don't cancel. Offer Acceptance Rate shows which specific offers resonate with users. Post-Save Retention reveals whether "saved" users continue subscribing long-term or just delay their cancellation briefly.
This last metric is crucial. If users accept a discount but cancel immediately afterward anyway, your retention offers might be delaying rather than preventing churn. True success means users who accept retention offers continue for multiple billing cycles.
For more strategies, see Churn in Subscription Apps: Top 5 Cancellation Reasons.
When users dismiss your paywall without subscribing, you have one more opportunity to convert them. Secondary offers, sometimes called exit intent offers or downsells, can capture users who were interested but not quite convinced at the initial price or offering.
Users who view your paywall have already demonstrated meaningful intent. They were curious enough to reach the paywall, they read your value proposition, and they considered subscribing. They're warm leads, fundamentally different from users who never engaged with premium features at all. The exit intent offer gives you a second chance before they leave entirely.
Research from e-commerce shows that exit-intent popups with discounts can lead to 37% more purchases. The psychology is straightforward: users who were on the fence might convert if given a slightly better deal or a different option that better matches their needs.
The key is understanding that dismissing a paywall isn't necessarily a hard "no." It's often a soft "not now" or "not at this price" or "I need more time to decide." A thoughtfully designed secondary offer addresses these hesitations directly.
Discounted Same-Tier offers the subscription they were just considering at a reduced price. This directly addresses price objection. If the user wanted your premium offering but hesitated at $9.99/month, seeing a "Special offer: $6.99/month for your first 3 months" might be exactly what they need to convert. The messaging should acknowledge their hesitation, "Wait! Before you go, here's a special offer just for you," making it feel personalized rather than like a standard popup.
Downsell to Lower Tier recognizes that sometimes users want less than your full offering. If your primary paywall promoted a comprehensive Premium tier, the secondary offer might highlight a Basic tier with fewer features but a more accessible price point. Some revenue is better than none, and users who start with a basic plan might upgrade later once they experience value.
Extended Trial addresses users who aren't convinced of your app's value yet. Instead of discounting the price, extend the evaluation period. "Need more time to decide? Here's a 14-day extended trial." This is particularly effective when combined with the understanding that your app's value takes time to realize. Users who weren't ready to commit after a 7-day trial might convert after 14 days of building the habit.
Show the secondary offer only once. If users learn that dismissing the paywall always triggers a discount, you've trained them to always dismiss first. This destroys your primary paywall conversion rate and conditions users to expect discounts. Track whether a user has seen the secondary offer and only present it on their first paywall dismissal.
Create genuine urgency. The secondary offer should feel temporary and special. "This offer expires in 10 minutes" or "One-time offer for new users" creates pressure to decide now rather than leaving and forgetting. But the urgency must be real. If users can dismiss and get the same offer next time, the urgency is fake and damages trust.
Make dismissal easy. Users who still aren't interested after seeing the secondary offer should be able to leave without friction. A clear "No thanks, I'll pay full price later" button respects their decision. Trapping users or making them feel pressured creates negative sentiment that hurts your brand.
Configure it in RevenueCat. Create a dedicated offering for your secondary/exit intent offer in the RevenueCat dashboard. This keeps it separate from your primary offerings and makes it easy to A/B test different secondary offer strategies. You can then use Experiments to compare different approaches: discount versus extended trial versus downsell.
There's an inherent tension in secondary offers. Every user who converts on the secondary offer at a discount is a user who might have converted on the primary offer at full price. However, the counter-argument is that many users who dismiss would never have converted at full price anyway, so capturing them at a discount is pure upside.
The right balance depends on your specific metrics. Monitor not just total conversion rate, but also revenue per user and long-term retention. If secondary offer converters retain as well as primary converters, the discount might be worthwhile. If they churn faster, you may be attracting lower-quality subscribers.
Testing is essential here. Compare having a secondary offer versus not having one, and measure the impact on both immediate revenue and long-term metrics.
Now that you understand each component of RevenueCat's monetization toolkit, let's discuss how to combine these strategies into a cohesive system and implement them in a sensible order.
A well-optimized monetization system works as follows. When a user triggers a paywall, you first update their user attributes based on their behavior and engagement level. This ensures targeting rules have current data to work with. RevenueCat then returns the appropriate offering based on any targeting rules and active experiments. The user sees a personalized paywall with pricing and trial lengths optimized for their segment.
If the user subscribes, you've successfully converted them. Your focus shifts to retention, Customer Center stands ready to intercept any future cancellation attempts with targeted retention offers.
If the user dismisses the paywall, you check whether they've seen a secondary offer before. If not, present the exit intent offer, whether that's a discount, a downsell, or an extended trial. If they convert on the secondary offer, they become a subscriber (albeit at different terms). If they dismiss again, they leave unconverted for now, but you've made every reasonable effort.
For churned users who return, targeting rules detect their expired subscription status and present win-back offers designed to bring them back.
Trying to implement everything at once is overwhelming and makes it hard to measure the impact of individual changes. Instead, follow a phased approach.
Weeks 1-2 focus on foundation. Set up a basic paywall using RevenueCat Paywalls, implement multiple placements (onboarding, feature gate, settings), and configure introductory offers. Get the basics working smoothly before adding complexity.
Weeks 3-4 introduce testing. Set up your first A/B test with Experiments. Start with something impactful like pricing (annual vs monthly comparison) or trial length. Run the experiment long enough to achieve statistical significance, analyze results, and iterate based on learnings.
Month 2 adds personalization. Implement Targeting for regional pricing, which often provides significant uplift with minimal complexity. Add user attributes for engagement-based targeting. Test different offerings for different segments, learning what resonates with each audience.
Month 3 builds retention and advanced features. Implement Customer Center with cancellation surveys and configure retention offers for common cancellation reasons. Add secondary/exit intent offers for paywall dismissals. Set up win-back campaigns for churned users.
Monitor these metrics to measure your progress across the entire funnel.
Trial Start Rate measures the percentage of paywall views that start trials, with a target of 10-15% for most apps. Trial-to-Paid Conversion tracks what percentage of trials convert to paid subscriptions, where 40-60% indicates a healthy funnel. Initial Conversion Rate shows the percentage of installs that become subscribers, with top-performing apps achieving 2-4%.
Monthly Churn measures subscribers who cancel each month, where less than 5% is a good target. Lifetime Value (LTV) captures total revenue per subscriber over their lifetime, which varies significantly by category. Average Revenue Per User (ARPU) looks at revenue across all users, helping you understand overall monetization effectiveness.
Monetization optimization is never "done." Establish a regular cadence for review and improvement.
Weekly, review active experiment results and paywall analytics. Are your experiments reaching significance? Are there unexpected trends?
Monthly, analyze churn reasons from Customer Center surveys and evaluate retention offer performance. What are users telling you about why they leave, and are your retention efforts working?
Quarterly, review your overall monetization strategy and plan major tests. Step back from tactical optimization to consider strategic questions: Are you in the right price range? Should you introduce new tiers or bundles? What have you learned about your users?
Congratulations! You've explored the complete RevenueCat monetization toolkit, from paywall optimization through A/B testing, personalization, introductory offers, churn reduction, and secondary offers.
The difference between median and top-performing apps is substantial, with top apps achieving more than double the conversion rates. But this gap represents opportunity. By systematically applying these strategies, you can move toward top-tier performance.
Data beats intuition. Changes that seem obviously better sometimes hurt conversions, while counterintuitive approaches sometimes win. Always test your assumptions with Experiments before rolling out broadly. The investment in proper testing prevents costly mistakes and reveals winning strategies you might not have discovered otherwise.
Small improvements compound dramatically over time. A 10% improvement in trial conversion combined with a 10% improvement in retention results in far more than 20% more revenue when you consider the compounding effect on lifetime value. Each optimization you make amplifies the value of every other optimization.
Start with one strategy and master it before moving to the next. We recommend beginning with paywall optimization since it has the most immediate and visible impact. Then add A/B testing to validate your changes and discover what resonates with your audience. Layer in personalization as you learn more about your different user segments. Finally, implement retention strategies to protect the subscribers you've worked hard to acquire.
Documentation to deepen your technical understanding:
Paywalls, Experiments, Targeting, Customer Center, and Subscription Offers.
Blog Posts with detailed strategies and case studies:
The Essential Guide to Mobile Paywalls, 10 Price Test Ideas, 24 Ways to Optimize Using Targeting, How Four Paywall Redesigns Boosted Conversions, and Unlocking Growth with Introductory Offers.
Benchmarks to understand where you stand:
State of Subscription Apps 2025.
Now go optimize your monetization and grow your revenue! 💰🚀