Glossary

A/B testing (also called split testing) is a method of comparing two or more variations of a product experience — such as a paywall design, landing page layout, pricing structure, or onboarding flow — to determine which version performs better against a defined metric. In mobile app monetization, A/B testing is used extensively to optimize conversion rates, trial starts, subscription sign-ups, and revenue per user. Traffic is randomly split between variants, and statistical analysis determines whether differences in performance are meaningful or due to chance. Effective A/B testing requires a clear hypothesis, a single variable change per test, sufficient sample size, and patience to reach statistical significance before drawing conclusions.

The number of users who have signed up for a recurring payment plan to access premium or additional features within the app. These subscriptions typically involve monthly or yearly payments, and give users access to features that are not available to non-subscribers.

Active users is a fundamental metric that counts the number of unique individuals who engage with your mobile app within a specific time period. This metric serves as a key indicator of app health, user engagement, and growth potential. By tracking active users across different time frames—daily (DAU), weekly (WAU), and monthly (MAU)—app developers and marketers can measure product stickiness, evaluate marketing effectiveness, and make data-driven decisions to optimize user acquisition and retention strategies.

Ad servers play a crucial role in housing a campaign's various creative elements like images, audio, and videos, and deciding which versions to present to particular audiences. Additionally, advertisement servers collect essential information on ad performance, such as impressions and clicks, which can offer valuable insights to a UA manager.

Alternative payment methods refer to any billing mechanism that allows mobile app users to complete purchases outside of the default App Store or Google Play in-app payment systems. These include web-based checkout pages, direct carrier billing, third-party payment processors like Stripe or Paddle, and regional payment solutions. For subscription apps, alternative payment methods have become increasingly important as regulatory changes — such as the EU Digital Markets Act and rulings in Epic v. Apple — have opened the door for developers to process payments outside the traditional app store ecosystem. By routing users to a web checkout, developers can reduce or entirely avoid the 15–30% platform commission, significantly improving unit economics. However, implementing alternative payment methods requires careful consideration of user experience friction, compliance with evolving app store policies, and the technical infrastructure needed to handle billing, receipts, and entitlements across platforms.

Annual Recurring Revenue (ARR) is the total value of recurring subscription revenue normalized to a one-year period. For mobile subscription apps, ARR is calculated by multiplying Monthly Recurring Revenue (MRR) by 12, or by summing the annualized value of all active subscriptions. ARR is one of the most important metrics for subscription businesses because it provides a predictable baseline of revenue, making it essential for financial planning, investor reporting, and company valuation. Unlike total revenue, ARR excludes one-time purchases, refunds, and non-recurring fees, providing a cleaner view of the sustainable revenue engine. Growth-stage subscription apps track ARR trajectory closely, as consistent month-over-month ARR growth signals product-market fit and effective monetization strategy.

App installs are a measure of the popularity and success of an app and one of the most essential metrics to keep an eye on in mobile app marketing. High install rates coupled with low uninstall rates indicate a healthy app with engaged users, while high uninstall rates could indicate problems with the app's design, functionality, or user experience.

App Links are special URLs that take users directly to a specific screen or piece of content inside a mobile app, rather than opening a web page in a browser. When a user clicks an App Link and has the corresponding app installed, the app opens immediately and displays the relevant content. If the app is not installed, the user is redirected to a fallback web page or an app store listing. App Links streamline the mobile user experience by removing unnecessary steps between clicking a link and reaching the desired in-app destination.

App retention refers to the capacity of an application to sustain users' engagement and activity for a specified duration after they have downloaded and installed it on their devices. It gauges the proportion of users who revisit the app after their initial download and reuse it. Essentially, app retention is an indicator of user loyalty and demonstrates the app's ability to deliver a positive user experience and satisfy user requirements over time. Retention rates are typically measured on Day 1, Day 7, and Day 30. High app retention rates are critical for the success of an app because they suggest that users perceive value in the app and are inclined to continue using it in the future.

App size refers to the amount of storage space a mobile application occupies, measured at different stages of its lifecycle from download to active use. Understanding and managing app size is crucial for mobile developers because it directly impacts user acquisition, retention, and overall app performance. App size encompasses multiple dimensions including download size (compressed data transferred from app stores), install size (uncompressed data after installation), and storage size (total space used during active use including caches and user data).

App Analytics is a segment within App Store Connect that is solely focused on measuring the performance of iOS apps. It offers insights on how users interact with the app, providing crucial data on user engagement, retention, conversion rates, and revenue. To fully comprehend your app's performance and develop an effective app growth strategy, it's essential to know and analyze the key metrics. With Apple App Analytics, mobile app developers can gain insights into the number of app downloads, user retention rates, frequency of app usage, and the amount of money spent on in-app purchases. This data can guide developers in making informed decisions that can enhance their app's performance, user experience, and revenue generation.

The App-Specific Shared Secret from Apple is a distinctive 32-character key to receive receipts for auto-renewable in-app subscriptions.

App Store Optimization (ASO) is the process of improving the visibility and conversion rate of a mobile app within app store search results and browse pages. ASO encompasses keyword research and optimization of app metadata — including the app title, subtitle, keyword field, and description — as well as optimizing visual assets like the app icon, screenshots, and preview videos. The goal is to increase organic discovery so that more users find and install the app without paid advertising. ASO also includes ongoing efforts like localizing listings for different markets, encouraging positive reviews, and monitoring category rankings. For subscription apps, ASO directly impacts customer acquisition cost (CAC), since higher organic visibility means a greater share of installs come at zero marginal cost. Effective ASO requires treating the app store listing like a conversion funnel: first capturing impressions through keyword relevance, then converting those impressions into page views through compelling icons and titles, and finally converting page views into installs through persuasive screenshots, descriptions, and social proof.

App Store visibility refers to how easily and frequently your mobile app appears to potential users across the App Store and Google Play. It includes your app's presence in search results, category rankings, top charts, and editorial features. The higher your visibility, the more likely users are to discover, tap on, and download your app. Visibility is shaped by a combination of keyword relevance, listing quality, user ratings, download velocity, and ongoing optimization efforts. In a marketplace with millions of competing apps, visibility acts as the bridge between your product and its audience. Without it, even the most innovative app risks going unnoticed. App Store visibility is not a one-time achievement but a continuous process driven by App Store Optimization (ASO), paid advertising, user engagement signals, and strategic content updates.

An app title is the official name of your mobile application as it appears in app stores, serving as the primary identifier users encounter when discovering your app. This critical metadata element appears prominently at the top of your app's store listing, adjacent to the app icon, and represents one of the most influential factors in app store optimization (ASO). The app title carries the highest weight in app store search algorithms, making it essential for both discoverability and conversion. Beyond its technical importance for search rankings, the app title creates the crucial first impression that determines whether potential users will explore your app further or scroll past it. In a marketplace with millions of competing applications, your title must instantly communicate your app's value proposition while incorporating strategic keywords that match user search behavior. Both the Apple App Store and Google Play Store limit titles to 30 characters, requiring developers to carefully balance branding, keyword optimization, and clarity within this constrained space.

App Tracking Transparency (ATT) is Apple's privacy framework, introduced with iOS 14.5 in April 2021, that requires apps to request explicit user permission before tracking their activity across other companies' apps and websites. When an app wants to access a user's IDFA (Identifier for Advertisers) for targeted advertising or cross-app attribution, it must display a system prompt asking the user to opt in. Industry-wide opt-in rates have hovered around 20–35%, meaning the majority of iOS users are now untrackable via traditional deterministic methods. ATT fundamentally disrupted mobile attribution and user acquisition by limiting the data available for campaign optimization, audience targeting, and performance measurement. This shift forced the industry to adopt new attribution frameworks like SKAdNetwork, invest in first-party data strategies, explore probabilistic modeling, and seek alternative monetization channels — such as web-based funnels — that operate outside the ATT-restricted ecosystem. For subscription apps, ATT's impact on attribution accuracy has made it significantly harder to measure true LTV by acquisition channel, increasing the importance of predictive modeling and server-side analytics.

Server validation, also known as server-side receipt validation, is a process used to ensure that purchases made within an app are authentic. This is achieved by using an encrypted file, in PKCS#7 format, which contains information about all in-app purchases. To authenticate purchased content, you can include receipt validation code in your app or server. App Store receipt validation involves sending a request to Apple's servers to verify the purchase and determine whether it was valid. This is particularly important for auto-renewable subscriptions as you need to know when they expire in order to provide or block access to your content. Receipt validation is also used when users need to restore a purchase, such as when they reinstall your app.

ARPDAU, or Average Revenue Per Daily Active User, measures the average revenue generated by each active user on a daily basis. This granular monetization metric is particularly valuable for apps expecting frequent user engagement, such as mobile games, social apps, and subscription-based services. Unlike broader metrics like ARPU, ARPDAU provides immediate visibility into how app changes, promotional events, or monetization adjustments impact daily revenue generation. ARPDAU stands for Average Revenue Per Daily Active User. It is a key performance indicator (KPI) that calculates the average amount of revenue an app generates from each user who actively engages with the app on a given day. This metric captures revenue from all monetization sources, including in-app purchases (IAP), subscriptions, and in-app advertising (IAA).

ARPPU, or Average Revenue Per Paying User, measures the average revenue generated by users who actually make payments within your app. Unlike ARPU which includes all users, ARPPU focuses exclusively on paying customers – providing a clearer picture of how much value your monetizing users deliver. This metric is essential for subscription apps, freemium games, and any business where only a portion of users convert to paying customers.

ARPU stands for Average Revenue per User, and it refers to the average amount of revenue an app generates from each active user. App growth teams that develop subscription or revenue-driven apps often include ARPU as a key performance indicator to measure their financial success. By calculating ARPU, you can determine the average amount of money you earn from each user. While ARPU takes into account the revenue earned from both paying and non-paying users, there is another similar metric used specifically for subscription-based apps. This metric is known as ARPPU (Average Revenue per Paying User), which only considers the revenue generated by users who have made a payment.

When an iOS app user tries to purchase a product or service within the app, the In-App Purchase (IAP) system of the App Store is used to initiate the transaction. If the payment is declined or there is a connectivity issue, the transaction is marked as "failed". In the same way, when a subscription renewal payment fails, the subscription enters the billing retry state. During this state, the App Store periodically retries the transaction with increasing intervals to give the user time to complete the purchase. This continues until the transaction is successful, the user cancels it, or the product/service is no longer available.

The percentage of users who stop using your mobile app over a specific time period. Churn rate is the inverse of retention rate and serves as a critical health indicator for any app business. For subscription apps, tracking churn is essential since even small reductions in churn can significantly impact revenue and customer lifetime value (LTV). Churn rate, also known as attrition rate, measures the percentage of users who stop using your mobile app over a specific period. In the context of mobile applications, churn represents users who disengage from your app—whether they uninstall it completely, cancel their subscription, or simply stop opening and interacting with it.

Cohort analysis is a method of analyzing data that involves grouping data sets by shared characteristics or experiences, typically within a specific time frame. The purpose of cohort analysis is to track changes or patterns in behavior over time and to gain insights into the factors that influence those changes.

Mobile app conversion rate (CR or CVR) is the percentage of users who achieve a specific goal within the app, such as making a purchase, creating an account, subscribing to a service, or completing a survey. Conversion rates are an important metric for mobile app developers and marketers as they indicate the effectiveness of the app in driving user engagement and achieving business goals. A higher conversion rate typically means that the app is successfully guiding users towards the desired action, while a lower conversion rate may indicate that there are issues with the user experience or the app's marketing strategy.

Cost Per Action (CPA) is a performance-based pricing model in which an advertiser pays only when a user completes a specific post-install action, such as making a purchase, starting a free trial, or subscribing to a service. Unlike CPI, which measures cost at the install level, CPA ties advertising spend directly to business outcomes further down the funnel. For subscription apps, common CPA events include trial starts, first subscription payments, or registration completions. CPA is particularly useful for evaluating the true efficiency of user acquisition campaigns, since an install alone doesn't generate revenue — what matters is whether the user converts into a paying subscriber. By optimizing toward CPA rather than CPI, growth teams can focus ad spend on channels and creatives that deliver users with higher intent and better downstream conversion behavior, even if those channels have a higher cost per install on the surface.

CPI stands for Cost Per Install, meaning the cost that an advertiser pays each time a user installs their mobile app after clicking on an ad. CPI is a performance-based pricing model, which means that the advertiser only pays for results that directly contribute to their business goals, such as app installations. This pricing model is particularly popular among mobile app developers who want to promote their apps and acquire new users.

Cost Per Mille (CPM), also known as cost per thousand impressions, is an advertising pricing model where advertisers pay a fixed rate for every 1,000 times their ad is displayed to users. "Mille" is Latin for thousand. CPM is one of the most common buying models in digital advertising, particularly for brand awareness campaigns and display advertising. In the mobile app ecosystem, CPM is used both by app developers buying ads to acquire users and by app publishers selling ad inventory within their apps. For user acquisition, CPM campaigns are typically less performance-oriented than CPI or CPA models, since the advertiser pays for visibility rather than a specific action. However, CPM can be effective for reaching large audiences at scale and building brand recognition. For app publishers monetizing with ads, CPM represents the revenue earned per 1,000 ad impressions served — also called eCPM (effective CPM) — and is a core metric for evaluating ad monetization performance across different ad networks and formats.

Creative fatigue occurs when an advertising audience has been exposed to the same ad creative too many times, resulting in declining click-through rates, rising cost per install, and diminishing campaign performance. In mobile user acquisition, creative fatigue is one of the most common reasons for campaign degradation over time. As users see the same images, videos, or messaging repeatedly, they begin to ignore the ads — a phenomenon sometimes called "ad blindness." Detecting creative fatigue early is critical for maintaining efficient UA spend. Key indicators include a decline in CTR while impressions remain stable, rising CPIs, and lower conversion rates from impression to install. Growth teams combat creative fatigue by maintaining a pipeline of fresh creatives, systematically rotating ad variations, testing new concepts and formats, and segmenting audiences to control frequency exposure. Apps running web funnel campaigns face similar dynamics — landing page designs and value propositions must be periodically refreshed to sustain conversion rates.

Cross-selling in the mobile app context refers to the practice of promoting complementary products, features, or subscription tiers to an existing user who has already made a purchase or is subscribed to a plan. Unlike upselling, which encourages upgrading to a higher-priced version of the same product, cross-selling introduces adjacent offerings that add value alongside what the user already has. For example, a fitness app might cross-sell a meal planning add-on to a user subscribed to a workout program, or a language learning app might promote a business vocabulary module to a user enrolled in conversational courses. Cross-selling is particularly effective on web-based checkout pages and post-purchase confirmation screens, where users are already in a buying mindset. When implemented well, cross-selling increases average revenue per user (ARPU) without requiring new user acquisition, making it one of the most efficient revenue growth levers for subscription apps. The key is relevance — the offered product must feel like a natural extension of what the user already values, rather than an unrelated pitch.

The amount spent for each newly-acquired mobile app user over a given time period. Customer Acquisition Cost (CAC) for mobile apps refers to the cost that a business incurs to acquire a new user for their mobile application over a specific period of time. In other words, it is the amount of money spent to attract a user to download and install a mobile app on their device. Whether you are just embarking on your journey or navigating quite a while to create a successful mobile app, the Customer Acquisition Cost (CAC) must be at the forefront of your mind.

The LTV:CAC ratio measures the relationship between the lifetime value of a customer and the cost of acquiring that customer. It is one of the most important unit economics metrics for subscription app businesses. An LTV:CAC ratio of 3:1 or higher is generally considered healthy, meaning the revenue generated by a user over their lifetime is at least three times what it cost to acquire them. A ratio below 1:1 means the business is losing money on every customer acquired. This metric is critical for evaluating the sustainability of growth strategies — aggressive user acquisition spending only makes sense if LTV sufficiently exceeds CAC. For subscription apps, improving the LTV:CAC ratio can be achieved from both sides: increasing LTV through better retention, pricing optimization, and upselling; or decreasing CAC through more efficient ad spend, higher organic install share, and web-based checkout flows that avoid platform commissions. Investors scrutinize this ratio closely when evaluating subscription businesses, as it directly indicates whether the company can scale profitably.

Daily Active Users (DAU) measures the number of unique users who engage with your app within a 24-hour window. This metric is essential for understanding your app's daily engagement levels and is particularly important for apps where daily interaction drives success, such as social media, gaming, and messaging platforms. DAU helps product teams assess user engagement, track campaign effectiveness, and identify patterns in user behavior.

The process of utilizing a custom URL to direct users to a specific page within an app is known as mobile deep linking. Deep links are dedicated links that take you directly to an app instead of a website or a store. They can send you straight to a specific place within the app, instead of just opening it up. This technique helps guide users to explore deeper within the app, beyond the initial launch screen, ultimately improving user engagement and retention.

Deferred deep linking is a technique that allows a link to route a user to a specific in-app destination even when the app is not yet installed on their device. When a user clicks a deferred deep link, they are first directed to the App Store or Google Play to install the app. After installation and first launch, the app recognizes the original link context and automatically navigates the user to the intended content, offer, or screen — rather than dropping them at the generic home screen. This is especially valuable for web-to-app flows and paid acquisition campaigns where users discover an offer on a web landing page, click through to install the app, and need to land directly on the relevant paywall, trial offer, or personalized onboarding experience. Without deferred deep linking, the attribution context and user intent are lost during the install step, leading to higher drop-off and lower conversion rates. Implementing deferred deep linking typically requires integration with an attribution provider or deep linking service that persists the link parameters through the app store redirect.

Direct-to-Consumer (DTC) billing refers to the practice of processing subscription or purchase payments directly between the app developer and the end user, without routing the transaction through the Apple App Store or Google Play billing systems. DTC billing allows developers to collect payments via their own website, web checkout page, or third-party payment processor, thereby avoiding the 15–30% commission charged by app store platforms. This approach has gained significant traction following regulatory changes like the EU Digital Markets Act, court rulings in cases like Epic v. Apple, and Apple's own policy updates allowing developers to link out to external purchase options in certain regions. For subscription apps, DTC billing can dramatically improve unit economics — a $10/month subscription that nets $7 after Apple's commission nets $9.70 or more when processed via Stripe on a web checkout. However, DTC billing requires building and maintaining web payment infrastructure, managing subscription lifecycle events (renewals, cancellations, upgrades) outside of StoreKit or Google Play Billing, and carefully navigating the compliance requirements of each platform.

A downsell is a monetization strategy where a user who has declined an initial offer is presented with a lower-priced or reduced-scope alternative to capture revenue that would otherwise be lost entirely. In the context of mobile subscription apps, downselling commonly occurs on paywalls or web checkout pages: if a user dismisses the primary annual subscription offer, they might immediately see a follow-up screen offering a monthly plan at a lower commitment, a discounted trial period, or a feature-limited tier at a reduced price. The psychology behind downselling is that the user has already demonstrated interest by engaging with the offer flow — they simply weren't convinced at the original price point. By presenting a more accessible entry point, the app captures a subscriber who would have otherwise churned at the paywall. Downsells are particularly effective in web funnel environments where the developer controls the entire purchase flow and can dynamically serve different offers based on user behavior. When combined with upselling and cross-selling strategies, downsells form a comprehensive price discrimination framework that maximizes conversion across different willingness-to-pay segments.

Error rate is a crucial metric that measures the reliability and performance of a mobile application. A high error rate indicates that the app is more prone to crashes or malfunctions, which can lead to user frustration and prompt users to uninstall the app. Hence, monitoring the error rate of an app is essential to ensure that the app is running smoothly and providing a positive user experience.

Event-based attribution is a method of crediting marketing channels or campaigns based on specific post-install events that a user completes, rather than attributing value solely at the point of install. While traditional mobile attribution focuses on which ad or campaign drove the app install, event-based attribution goes deeper by tracking downstream actions like free trial starts, subscription purchases, in-app purchases, or reaching a specific engagement milestone. This approach is particularly valuable in the post-ATT landscape where install-level attribution data is limited. By shifting focus to post-install events, marketers can better evaluate which channels drive high-quality users who actually convert and generate revenue, rather than just volume of installs. Event-based attribution works in tandem with SKAdNetwork's conversion value framework, where developers can encode specific post-install events into the limited conversion value bits available. It also enables more sophisticated optimization of ad campaigns, since platforms like Meta and Google can optimize toward deeper funnel events when provided with conversion signals tied to revenue-generating actions.

Fingerprinting, also called probabilistic attribution, is a method of identifying and matching users across touchpoints using non-deterministic data signals such as IP address, device type, operating system version, screen resolution, language settings, and timestamp proximity. Unlike deterministic attribution methods that rely on unique identifiers like IDFA or GAID, fingerprinting creates a statistical probability that a particular ad click and subsequent app install belong to the same user. Before Apple's App Tracking Transparency framework, fingerprinting served as a fallback when device-level identifiers were unavailable. However, Apple has taken an increasingly strict stance against fingerprinting, explicitly prohibiting it in their developer guidelines and enforcing against it in App Store reviews. Despite these restrictions, probabilistic methods remain relevant in certain contexts — particularly in web-to-app flows where a user's web session attributes can be matched against app-side signals to maintain attribution continuity without relying on restricted mobile identifiers. The accuracy of fingerprinting varies widely depending on the signals available and the matching window, typically ranging from 60–80% compared to near-100% accuracy for deterministic methods.

First-party data is information collected directly by an app developer from their own users through interactions on owned channels — including the app itself, websites, web funnels, email communications, and customer support touchpoints. This data includes behavioral signals (screens viewed, features used, session duration), purchase history (subscriptions, transactions, plan changes), declared preferences (onboarding survey responses, settings), and device-level signals (OS, device model, app version). In the post-ATT privacy landscape, first-party data has become the most valuable data asset for mobile app businesses. Unlike third-party data, which is collected by external entities and is increasingly restricted by platform privacy policies, first-party data is consented, reliable, and privacy-compliant by nature. Subscription apps that build robust first-party data strategies can use this information to personalize onboarding experiences, optimize paywall presentations, build predictive LTV models, power targeted re-engagement campaigns, and create lookalike audiences for acquisition — all without depending on third-party cookies or mobile advertising identifiers that are being deprecated across the ecosystem.

Flutter is a freely available framework developed by Google that enables the creation of cross-platform applications that are natively compiled using a single codebase. Using Dart – a Flutter coding language, Flutter facilitates the development of applications for both Android and iOS devices.

Funnel analysis is the process of tracking and measuring how users progress through a defined sequence of steps toward a desired outcome, such as installing an app, starting a free trial, or completing a subscription purchase. Each step in the funnel represents a conversion point where some users proceed and others drop off. For mobile subscription apps, common funnel stages include: ad impression → ad click → landing page view → app install or web checkout → onboarding completion → paywall view → trial start → paid conversion. By measuring the conversion rate between each stage, product and growth teams can identify where the largest drop-offs occur and prioritize optimization efforts accordingly. Funnel analysis is essential for both in-app flows (onboarding to paywall to purchase) and web-to-app flows (ad click to landing page to web checkout to app activation). Advanced funnel analysis segments users by acquisition source, geography, device type, or cohort to identify which segments convert best and where each segment encounters friction.

Funnel drop-off rate measures the percentage of users who abandon a conversion process at each stage before reaching the final desired action. It is the inverse of stage-to-stage conversion rate. For example, if 1,000 users view a web landing page and only 300 click through to the checkout, the drop-off rate at that stage is 70%. Identifying stages with the highest drop-off rates reveals the biggest optimization opportunities. In web-to-app subscription flows, common high-drop-off points include: the transition from landing page to checkout (often caused by poor value proposition communication or unexpected pricing), the payment form itself (friction from too many fields or lack of trusted payment options), and the post-purchase app activation step (where users must download and open the app to access what they paid for). Reducing funnel drop-off by even a few percentage points at critical stages can have an outsized impact on overall conversion rates and revenue, since improvements compound across the funnel.

Google Play Billing is Google's required payment system for in-app purchases and subscriptions distributed through the Google Play Store. It handles transaction processing, receipt verification, subscription lifecycle management (renewals, cancellations, grace periods, holds), and revenue reporting. Google charges a commission of 15% on the first $1 million in annual revenue earned through the Play Store, and 30% on revenue above that threshold. For subscriptions specifically, Google reduced its commission to 15% for all subscription revenue starting in January 2022, recognizing the importance of recurring relationships. The Google Play Billing Library provides APIs for querying available products, launching purchase flows, acknowledging purchases, and handling subscription state changes. Like Apple's StoreKit, Google Play Billing abstracts the complexity of payment processing across regions, currencies, and payment methods. However, regulatory pressure — particularly in the EU, South Korea, and India — has led Google to allow alternative billing options in certain markets, enabling developers to process payments through third-party systems while still distributing their apps on the Play Store, sometimes with a reduced commission.

A grace period is a window of time after a subscription renewal payment fails during which the user retains full access to their subscription content or features while the platform attempts to retry the payment. Both Apple and Google offer grace period functionality. On iOS, developers can enable grace periods of 6 or 16 days; on Google Play, the grace period can be set to 3, 7, 14, or 30 days. The purpose of the grace period is to reduce involuntary churn — subscription cancellations caused by payment failures rather than deliberate user decisions. Common causes of payment failure include expired credit cards, insufficient funds, or bank-side authorization issues. By maintaining the user's access during the grace period, the app avoids abruptly cutting off a user who intends to remain subscribed, giving the billing system time to successfully retry the charge. Studies suggest that enabling grace periods can recover 10–30% of subscriptions that would otherwise be lost to involuntary churn. Developers should communicate payment issues to users during the grace period through in-app messaging or push notifications, encouraging them to update their payment method.

Gross revenue is the total amount of money generated from subscriptions and in-app purchases before any deductions. Net revenue is the amount remaining after subtracting platform commissions (Apple's or Google's 15–30% fee), refunds, chargebacks, and applicable taxes. For mobile subscription businesses, the distinction between gross and net revenue is critical for accurate financial planning and reporting. A subscription app generating $100,000 in gross monthly revenue might net only $70,000–$85,000 depending on its commission tier, refund rate, and revenue mix. When calculating unit economics like LTV and LTV:CAC ratio, using gross revenue inflates the apparent profitability of user acquisition. Investors and financial analysts expect to see net revenue figures when evaluating subscription businesses. Apps that route a portion of their subscriptions through web-based checkout (avoiding or reducing platform commissions) see a narrower gap between gross and net revenue on those transactions, which directly improves margins and makes previously unprofitable acquisition channels viable.

A hybrid app is a type of mobile application that combines elements of both native and web apps. It is built using web technologies like HTML, CSS, and JavaScript, but is wrapped in a native container that allows it to be installed from app stores and access device-specific features like push notifications, camera, and GPS.

Hybrid monetization is a revenue strategy that combines two or more monetization models within a single app — typically a mix of subscriptions, in-app purchases, and advertising. Rather than relying on a single revenue stream, hybrid monetization allows apps to capture value from different user segments based on their willingness and ability to pay. For example, a freemium app might generate subscription revenue from its most engaged users, display ads to free users who are unlikely to convert, and offer one-time in-app purchases for specific features or content. The rise of hybrid monetization reflects the reality that most apps have diverse user bases with varied preferences. A user who won't pay $9.99/month for a subscription might still watch a rewarded video ad to unlock premium features for a session. Implementing hybrid monetization requires careful balancing — too many ads can degrade the user experience and reduce subscription conversion, while overly aggressive paywalls might drive away users who would have generated meaningful ad revenue. The most successful hybrid models segment users dynamically and adjust the monetization approach shown to each user based on behavioral signals and predicted lifetime value.

IDFA, short for Identifier for Advertisers, is a distinct and unpredictable alphanumeric code that is assigned to each iOS device by Apple. Advertisers use this identifier to deliver targeted ads and measure the effectiveness of their advertising campaigns. With the changes to Apple's privacy policy, app developers are now required to explicitly ask for user permission to track their IDFA. Users can choose to opt out of IDFA tracking by turning on the "Limit Ad Tracking" (LAT) option in their device's settings.

The IDFV (Identifier for Vendors) is a 32-character code that serves the purpose of differentiating individual devices that interact with an app. It is used for identifying vendor apps and differentiating them from other apps present on the same device. The IDFV is deleted as soon as all the apps from the developer are uninstalled.

Impression-to-install rate (also called IPM — Installs Per Mille, or installs per thousand impressions) measures the percentage of ad impressions that ultimately result in an app install. It is calculated by dividing the number of installs by the number of ad impressions and multiplying by 100 (or by 1,000 for the IPM variant). This metric combines ad engagement efficiency (do people click?) with post-click conversion efficiency (do people install after clicking?), making it a holistic measure of creative and targeting quality. A high impression-to-install rate indicates that the ad creative resonates with the target audience and that the app store listing or landing page effectively converts interested users. Typical impression-to-install rates vary significantly by ad format and vertical, with video ads and rewarded formats generally outperforming static banners. Monitoring this rate across different creatives, audiences, and placements helps growth teams identify their most efficient combinations and detect creative fatigue early.

In-app events refer to activities that users perform on an app post-installation. These activities may consist of playing games, making purchases, adding items to shopping carts, or completing tutorials, among other things.

When a user is in your app, notifications in app can pop up to showcase new updates or features, greet the user to the platform, or provide guidance through instructions or training on how to use the app.

An In-app purchases SDK (Software Development Kit) is a set of tools, code libraries, and documentation provided by a developer platform, such as Apple or Google, that allows app developers to integrate the ability for users to make purchases within their app.

In-app subscriptions are a payment model in which users are charged on a recurring basis in exchange for access to premium content, exclusive features, or services. They are frequently used by developers as a way to monetize their apps by providing users with ad-free experiences or exclusive content.

Incremental lift testing (also called incrementality testing or hold-out testing) is a measurement methodology that determines the true incremental impact of a marketing campaign by comparing the behavior of a group exposed to ads against a control group that was not exposed. Unlike standard attribution, which can overcount conversions by crediting campaigns for users who would have converted organically, incrementality testing isolates the causal effect of advertising spend. In mobile app marketing, this typically involves withholding ads from a randomly selected subset of the target audience and measuring the difference in install rates, subscription conversions, or revenue between the exposed and holdout groups. The difference represents the true "lift" — the additional conversions directly caused by the campaign. In the post-ATT era, where traditional last-click attribution has become unreliable for iOS campaigns, incremental lift testing has gained importance as a privacy-safe way to measure campaign effectiveness. It answers the fundamental question: "Would these users have converted anyway without seeing my ad?"

An indie developer (short for "independent developer") is an individual or a small team that creates software applications, mobile apps, or video games without financial or creative backing from a major publisher, corporation, or studio.

An introductory offer is a special pricing incentive made available to new subscribers who have never previously subscribed to a particular plan. Both Apple and Google support introductory offers natively through their billing systems. The three main types are: free trials (the user pays nothing for a set period, then auto-renews at full price), pay-up-front (a one-time reduced payment covering an introductory period before standard pricing kicks in), and pay-as-you-go (a reduced recurring price for a set number of billing cycles). Introductory offers are one of the most powerful tools for improving trial-to-paid conversion rates, as they lower the barrier to entry for users who are interested but hesitant to commit at full price. The key challenge with introductory offers is balancing conversion uplift against revenue dilution — if users overwhelmingly choose the discounted option, the immediate revenue impact can be significant. Optimizing introductory offers involves A/B testing different trial lengths, discount levels, and offer types across different user segments, acquisition channels, and geographies to find the combination that maximizes long-term revenue per user.

In iOS, developers can enable users to purchase additional features or content within an app using in-app purchases, providing a way to monetize their apps beyond the initial purchase price or to offer a "freemium" model. Apple manages the payment process and deducts a commission, known as the "Apple tax", from the sales amount.

A landing page is a standalone web page designed with a single focused objective — typically to convert visitors into leads, trial users, or paying subscribers. Unlike general website pages with multiple navigation options, a landing page strips away distractions and guides the visitor toward one specific call-to-action (CTA). In mobile app marketing, landing pages serve several critical functions: they act as the destination for paid ad campaigns (receiving traffic from Facebook, Google, TikTok, and other ad platforms), they serve as the entry point for web-to-app subscription funnels where users can purchase subscriptions via web checkout before being directed to download the app, and they provide an SEO surface for capturing organic search traffic around topics relevant to the app's value proposition. For subscription apps using web funnel strategies, the landing page is where the conversion happens — it must communicate the app's value proposition, present pricing and plan options, build trust through social proof, and make the checkout process as frictionless as possible. High-performing landing pages in the mobile subscription space typically achieve 20–40% visitor-to-trial conversion rates when optimized through systematic A/B testing of headlines, imagery, pricing presentation, and CTA design.

LTV meaning, Lifetime Value (LTV), is a performance indicator used to evaluate the total earnings generated by a customer throughout their entire tenure of using a mobile application. Historical data on user retention rates is often used to estimate the expected duration of user engagement. Having knowledge of what is LTV and the average LTV of your customers is crucial for executing successful marketing strategies. LTV in marketing for mobile apps is normally used to optimize revenue streams such as subscriptions, in-app advertising, and in-app purchases by determining the amount of money that can be spent on user acquisition while still being profitable.

A lookback window (also called an attribution window) is the defined time period during which an ad click or impression can be credited for a subsequent app install or conversion event. If a user clicks an ad but doesn't install the app until after the lookback window has expired, the install is classified as organic rather than attributed to the campaign. Standard lookback windows vary by platform and ad network: click-through attribution windows are typically 7–30 days, while view-through (impression-based) attribution windows are usually 1–24 hours. The length of the lookback window significantly affects how marketing performance is measured. Shorter windows produce more conservative attribution (fewer attributed installs) but higher confidence that the ad actually influenced the decision. Longer windows capture more potential influence but increase the risk of over-crediting ads for installs that would have happened organically. In the SKAdNetwork framework, Apple uses fixed attribution windows — initially 24 hours for click-through and not supported for view-through — which is significantly more restrictive than the industry standard and has forced marketers to rethink how they measure campaign performance on iOS.

Media Mix Modeling (MMM) is a statistical analysis technique that measures the impact of various marketing channels and activities on business outcomes — typically installs, revenue, or subscriptions — using aggregated historical data rather than user-level tracking. MMM uses regression analysis to estimate how much each marketing channel (paid social, search, TV, influencer, organic) contributes to overall results, while controlling for external factors like seasonality, competitive activity, and macroeconomic conditions. In the mobile app industry, MMM has experienced a significant revival driven by the privacy changes introduced by ATT. As deterministic user-level attribution has become increasingly limited on iOS, MMM offers a privacy-compliant alternative that doesn't require any user-level identifiers or consent. It works with aggregated spend and performance data, making it immune to tracking restrictions. While MMM has historically been associated with large enterprises and offline media planning, modern implementations using Bayesian statistical methods and tools like Meta's Robyn or Google's Meridian have made it accessible to growth-stage app companies. The main limitation of MMM is its reliance on historical data variance — it needs sufficient changes in spend levels across channels over time to produce reliable estimates.

The mobile app onboarding process involves a series of steps that new users take to get started with an app. This process entails guiding users through the product, providing relevant information, and helping them set up their accounts. This is the first opportunity for users to understand the value of your product. By the end of the onboarding process, users should be familiar with the mobile user interface (UI), navigation patterns, and basic app functionality. A smooth app onboarding process can increase app usage as it reduces user uncertainty and frustration.

Mobile attribution is the process of connecting app installs and in-app actions to specific marketing campaigns, ads, or channels that drove them. It enables marketers to understand which advertising efforts deliver results, optimize ad spend across channels, and make data-driven decisions about user acquisition strategies.

A Mobile Measurement Partner (MMP) is a third-party analytics platform that provides independent attribution, analytics, and measurement services for mobile app marketing campaigns. MMPs track which ad clicks and impressions lead to app installs and post-install events, providing a unified view of marketing performance across multiple ad networks and channels. Major MMPs in the mobile ecosystem include AppsFlyer, Adjust, Branch, Singular, and Kochava. MMPs play a neutral intermediary role — since they are independent from both the advertiser and the ad networks, their attribution data is considered unbiased. Core MMP capabilities include last-touch attribution, multi-touch attribution, fraud detection, deep linking, audience segmentation, SKAdNetwork management, and cohort-based analytics. In the post-ATT landscape, MMPs have evolved to offer probabilistic modeling, predictive analytics, and aggregated measurement solutions that work within Apple's privacy constraints. For subscription apps, MMPs provide critical insights into which channels and campaigns deliver subscribers with the highest LTV, enabling marketers to shift budget toward the most profitable traffic sources.

Monthly Active Users (MAU) represents the number of unique users who engage with your app within a 30-day window. Unlike daily active users (DAU), MAU is typically used by travel, financial, or utility apps where users are expected to interact a few times a month rather than daily.

Monthly Recurring Revenue (MRR) is the predictable, normalized monthly revenue generated from all active subscriptions. MRR is calculated by summing the monthly-equivalent value of every active subscription — annual plans are divided by 12, weekly plans are multiplied by approximately 4.33, and monthly plans are counted at face value. MRR is the foundational financial metric for subscription app businesses because it provides a consistent, comparable measure of revenue trajectory regardless of billing cadence mix. MRR is typically broken down into component parts: New MRR (revenue from first-time subscribers), Expansion MRR (revenue from upgrades, upsells, or cross-sells), Contraction MRR (revenue lost from downgrades), Churned MRR (revenue lost from cancellations), and Reactivation MRR (revenue from previously churned subscribers who re-subscribe). Tracking these components separately reveals the underlying dynamics driving overall revenue growth or decline. A company with strong headline MRR growth but high churned MRR may be masking a retention problem with aggressive acquisition spending — an unsustainable pattern that component-level analysis makes visible.

A native mobile app refers to a type of smartphone application that is developed and programmed specifically for a particular operating system, such as iOS or Android, using a dedicated programming language such as Objective C for iOS or Java for Android.

Net Revenue Retention (NRR), also called Net Dollar Retention (NDR), measures the percentage of recurring revenue retained from existing customers over a given period, including the effects of upgrades, downgrades, and churn. An NRR of 100% means the business retains all of its existing revenue; above 100% means expansion from existing users exceeds losses from churn and downgrades. For subscription apps, NRR is a powerful indicator of product-market fit and monetization health. An app with 110% NRR is growing its revenue base by 10% from existing users alone, before any new customer acquisition — a strong signal that users find increasing value over time. NRR above 100% is often driven by users upgrading to higher-priced plans, purchasing add-ons, or re-subscribing after a lapse. Conversely, NRR below 100% indicates that the business must continuously acquire new subscribers just to maintain its current revenue level, putting pressure on user acquisition efficiency. Top-performing subscription businesses typically achieve NRR of 110–130%, and investors consider this metric one of the strongest predictors of long-term sustainable growth.

An offerwall is an in-app advertising format that presents users with a list of tasks or offers they can complete in exchange for virtual rewards, such as in-game currency, premium features, or other in-app benefits.

Mobile app marketers typically classify app downloads into two categories: those obtained through paid sources and those obtained organically. Organic installs occur when users come across the app through various non-paid channels, such as search engine optimization (SEO), app store optimization (ASO), or word-of-mouth recommendations.

Paid installs, also known as non-organic installs (NOI), occur when a user downloads and installs an app after being exposed to a marketing campaign. These campaigns can take various forms of advertising, such as social media ads, display ads, video ads, or search ads, and are part of user acquisition efforts on paid and owned media.

Payment recovery refers to the systems and strategies used to capture revenue from failed subscription renewal transactions before the subscription lapses entirely. Failed payments are the leading cause of involuntary churn — subscribers who don't intend to cancel but whose payment doesn't process successfully. Common causes include expired credit cards, insufficient funds, card limits, and bank-side fraud blocks. Payment recovery strategies operate at multiple levels: platform-level retry logic (Apple and Google automatically retry failed charges on optimized schedules), grace periods that maintain user access while retries occur, in-app messaging that alerts users to update their payment information, dunning emails that communicate payment issues and provide easy update links, and web-based payment update flows that allow users to fix billing issues outside the app. Effective payment recovery programs can reduce involuntary churn by 20–40%, representing significant revenue saved with minimal additional user acquisition cost. For apps processing subscriptions through web checkout, having direct control over the billing relationship enables more aggressive and customized recovery tactics compared to relying solely on App Store or Google Play retry mechanisms.

A paywall functions as a digital blockade that restricts users from accessing certain content or services until they have paid a fee or subscribed to a service. For mobile app developers, paywalls present an opportunity to showcase the value of their product and address any concerns that potential subscribers may have.

Paywall A/B testing is a research method that involves conducting a randomized controlled experiment to assess the effectiveness of mobile app paywalls.

Mobile app paywall optimization refers to the process of fine-tuning the design and user experience of an app's paywall to maximize revenue from paid subscriptions or in-app purchases. This involves analyzing user behavior and identifying the most effective paywall placement, messaging, pricing, and incentives.

A dashboard within App Analytics provided by Apple designed for iOS app developers to track iOS app performance. The Peer Group Benchmarks display percentile information regarding how an app performs in specific metrics relative to other comparable apps.

A platform fee (commonly called the "Apple tax" or "Google tax") is the commission that app store platforms charge on in-app purchases and subscriptions processed through their billing systems. Apple charges 30% on most transactions through the App Store, reduced to 15% for developers earning less than $1 million annually through the App Store Small Business Program, and 15% on all subscription renewals after the first year. Google Play charges 15% on subscription revenue and 15% on the first $1 million of non-subscription revenue, with 30% above that threshold. These platform fees have a profound impact on the unit economics of subscription apps. On a $9.99/month subscription, Apple's 30% first-year commission means the developer nets only $6.99 — and $8.49 after the rate drops to 15% in year two. This fee structure has driven significant industry interest in alternative billing mechanisms, including web-based checkout flows that process payments outside the app store ecosystem. Regulatory actions worldwide — including the EU Digital Markets Act, Japan's TPSA guidelines, and court rulings in multiple jurisdictions — are gradually expanding developers' ability to offer alternative payment options and communicate pricing outside the app, creating opportunities for meaningful margin improvement.

A postback (also called a server-to-server callback or S2S callback) is a server-side communication mechanism used to send conversion data from one system to another without relying on client-side tracking. In mobile attribution, postbacks are the primary method by which Mobile Measurement Partners (MMPs) communicate install and event data back to ad networks. When a user installs an app and the MMP attributes that install to a specific campaign, the MMP fires a postback to the relevant ad network containing the attribution details (campaign ID, ad group, creative, conversion timestamp, etc.). This enables the ad network to optimize its algorithms and allows the advertiser to measure performance. In the SKAdNetwork framework, Apple sends postbacks directly from the device to the ad network, bypassing the MMP entirely for initial attribution. Postbacks are also used in web-to-app flows to communicate web conversion events to advertising platforms — for example, when a user completes a subscription purchase on a web checkout page, a server-side postback can be sent to Meta or Google to feed their optimization algorithms with conversion signals.

Predictive LTV (pLTV) is the use of statistical models and machine learning to forecast the future lifetime value of a user or cohort based on their early behavior signals. Rather than waiting months or years to observe a user's actual LTV, predictive models estimate what a user will spend over their entire lifecycle using data available within the first hours, days, or weeks after acquisition. Common input signals include acquisition source, geographic location, device type, onboarding completion, early engagement patterns, initial purchase behavior, and session frequency. For subscription apps, predictive LTV models typically forecast metrics like probability of trial-to-paid conversion, expected subscription duration, likelihood of plan upgrade, and projected total revenue. Predictive LTV is critical for real-time user acquisition optimization — by estimating the long-term value of users from a particular campaign early, growth teams can dynamically adjust bids, budgets, and targeting without waiting for actual revenue to materialize. This is especially important in the post-ATT landscape where campaign-level feedback loops are slower and less granular. Advanced implementations use predictive LTV signals to personalize paywall offers, onboarding flows, and re-engagement messaging in real time.

Push notifications are short, clickable messages sent directly to a user's device by mobile apps or websites, even when the app isn't actively in use. They appear on lock screens, notification centers, and banners to deliver timely updates, promotions, reminders, and alerts. For mobile apps, push notifications are one of the most effective tools for driving user engagement, increasing retention, and re-engaging inactive users.

A reactivation campaign (also called a re-engagement or win-back campaign) is a marketing initiative specifically designed to bring back users who have previously churned, lapsed, or become inactive. Unlike retention efforts that target currently active users, reactivation campaigns focus on users who have already disengaged — whether they unsubscribed, stopped opening the app, or uninstalled it entirely. Effective reactivation campaigns leverage multiple channels including push notifications (for users who still have the app installed), email (for users who uninstalled but provided an email), paid retargeting ads, and SMS. The messaging typically highlights what's new since the user left, offers a special incentive to return (such as a discounted subscription rate or extended free trial), or triggers an emotional connection to the value the user previously experienced. For subscription apps, reactivated subscribers often have higher retention rates than first-time subscribers because they already understand the product's value proposition.

Return on Ad Spend (ROAS) measures the revenue generated for every dollar spent on advertising. It is calculated by dividing total revenue attributed to a campaign by the total ad spend on that campaign. A ROAS of 2.0 means the campaign generated $2 in revenue for every $1 spent. ROAS is the most widely used profitability metric in mobile user acquisition because it directly connects marketing investment to revenue outcomes. For subscription apps, ROAS calculations must account for the time lag between ad spend and revenue realization — a user acquired today may not generate their first payment for 7 days (if they start with a free trial) and may generate revenue over months or years of subscription renewals. This makes "Day 0 ROAS" (revenue from immediate purchases) an incomplete picture. Growth teams track ROAS at multiple horizons — Day 7, Day 30, Day 90, Day 365 — to understand the full return curve. Target ROAS thresholds depend heavily on a company's margin structure: apps routing payments through app store billing (with 15–30% commissions) need higher gross ROAS than apps processing through web checkout to achieve the same profitability.

Revenue recovery encompasses all strategies and systems designed to recapture revenue that would otherwise be lost due to failed payments, voluntary cancellation attempts, or expired subscriptions. It is a broader category than payment recovery alone, as it includes not just retrying failed transactions but also cancellation deflection flows (offering discounts, plan changes, or pauses when a user attempts to cancel), win-back offers for recently churned subscribers, and reactivation campaigns for lapsed users. For subscription apps, revenue recovery can represent 15–30% of total revenue that would have been lost without intervention. The most effective revenue recovery programs combine automated mechanisms (smart payment retry logic, grace periods, dunning emails) with personalized interventions (targeted offers based on cancellation reason, usage patterns, and predicted churn risk). Apps with direct billing relationships through web checkout have greater flexibility to implement sophisticated revenue recovery tactics, including real-time payment method updates, custom retry schedules, and personalized retention offers at the moment of cancellation.

Server-to-Server (S2S) integration refers to the direct communication between two backend systems without any client-side (browser or app) intermediary. In mobile app monetization and marketing, S2S integrations are used for real-time data exchange between a developer's backend and third-party services such as attribution providers, analytics platforms, payment processors, and ad networks. Common use cases include sending purchase events from a web checkout server to an MMP for attribution, forwarding subscription lifecycle events (renewals, cancellations, refunds) from a billing provider to an analytics platform, and transmitting conversion signals from a payment processor to advertising platforms for campaign optimization. S2S integrations are more reliable and privacy-compliant than client-side tracking methods because they don't depend on user-side factors like ad blockers, browser cookies, or SDK availability. For web-to-app flows, S2S architecture is particularly important — it enables the web payment system to communicate subscription status to the app's backend, which then provisions access for the user regardless of which platform or device they use.

SKAdNetwork (SKAN) is Apple's privacy-preserving attribution framework for measuring the effectiveness of advertising campaigns that drive app installs on iOS. Introduced as an alternative to IDFA-based tracking after ATT severely limited user-level tracking, SKAN provides aggregated, anonymized attribution data directly from Apple's servers — without revealing any information about individual users. Under SKAN, when a user clicks an ad and installs an app, Apple validates the install and sends an attribution postback to the ad network after a delay, containing limited information: the ad network ID, campaign ID, and a conversion value set by the developer. The conversion value (initially 6 bits allowing 64 possible values, expanded in SKAN 4.0 with coarse and fine values) is the developer's only mechanism for encoding post-install user behavior into the attribution signal. This means developers must carefully decide which events to encode — such as whether the user started a trial, made a purchase, or reached an engagement threshold — within a constrained time window. SKAN's design prioritizes user privacy through delayed, aggregated reporting with built-in noise, which makes campaign-level optimization significantly more challenging than traditional attribution methods.

Developers can use Apple's StoreKit framework to incorporate in-app purchases (IAPs) into their apps on iOS, macOS, watchOS, and tvOS. The framework facilitates secure payment processing on behalf of the app, connecting with the AppStore and requesting user authorization for payments.

The Google Play Developer API offers subscription purchase deferral, which allows developers to delay subscription purchases for a limited time period. This feature is beneficial for various reasons, such as offering users a free trial or allowing them to postpone payment due to financial challenges.

Subscription fatigue describes the growing consumer resistance to signing up for new recurring payment commitments, driven by the proliferation of subscription-based products and services across every category — from streaming and news to fitness, productivity, and food delivery. As the average consumer manages an increasing number of active subscriptions, each new subscription request faces higher scrutiny, longer decision times, and greater likelihood of rejection. For mobile app developers, subscription fatigue manifests as declining trial start rates, lower paywall conversion rates, and increased price sensitivity. Combating subscription fatigue requires clear value differentiation (why is this subscription worth adding to the user's existing portfolio?), flexible pricing options (monthly vs. annual, multiple tiers, usage-based components), low-commitment entry points (free trials, introductory offers, freemium features), and continuous delivery of perceived value to justify ongoing payments. Web funnel strategies can help address subscription fatigue by allowing more space and time to communicate value before the purchase decision, compared to the constrained paywall experience within an app.

Subscription revenue refers to the income generated from a recurring payment model, where users pay a regular fee, often on a monthly or yearly basis, to access premium features, content, or services within the app.

Third-party billing refers to the use of external payment processors — such as Stripe, Paddle, Braintree, or Adyen — to handle subscription and purchase transactions outside of Apple's App Store or Google Play's native billing systems. Third-party billing enables app developers to process payments on their own terms, typically through web-based checkout flows, and often at significantly lower processing fees (2–5% compared to 15–30% platform commissions). This approach has become increasingly viable as regulatory pressure and legal rulings in multiple jurisdictions have forced app store platforms to allow or accommodate alternative payment options. For developers implementing web-to-app subscription models, third-party billing is the technical backbone — it handles payment processing, subscription management, invoicing, tax calculation, PCI compliance, and often provides webhook-based events for real-time subscription status updates. The trade-off is added complexity: developers must build and maintain the web checkout experience, handle subscription lifecycle management outside the native app store frameworks, and ensure a seamless user experience as subscribers transition between the web payment flow and the app itself.

Trial conversion rate measures the percentage of users who start a free trial and subsequently convert into paying subscribers when the trial period ends. It is one of the most critical metrics for subscription apps that use free trials as their primary conversion mechanism. Trial conversion rates vary significantly by app category, trial length, and pricing — industry averages typically range from 40–70% for auto-renewing trials, depending on whether users must provide a payment method upfront. Higher trial conversion rates are generally associated with shorter trial periods (which create urgency), strong onboarding that drives engagement during the trial, effective activation of key features that demonstrate the product's value, and timely communication reminding users of the trial's benefits before it ends. Monitoring trial conversion rates by acquisition channel reveals which traffic sources bring users with the highest purchase intent, enabling growth teams to allocate budget toward the most profitable channels. Declining trial conversion rates over time may signal market saturation, product-market fit issues, or that the app is attracting increasingly lower-intent users through broader targeting.

The trial-to-paid funnel describes the complete user journey from initiating a free trial to becoming a paying subscriber, including all intermediate steps and decision points along the way. This funnel typically includes: trial start → onboarding/activation → feature engagement → value realization → renewal decision → paid conversion. Each stage has its own conversion rate and drop-off risks. The trial-to-paid funnel is distinct from broader acquisition funnels because the user has already committed to trying the product — the challenge is demonstrating enough value during the trial window to justify ongoing payment. Key optimization levers within the trial-to-paid funnel include: targeted onboarding that quickly guides users to their "aha moment," progressive feature revelation that gives users reasons to return throughout the trial, timely nudges and reminders about trial expiry, and strategic offers (discounts or plan suggestions) for users showing signs of disengagement. Apps with web-based subscription flows can extend the trial-to-paid funnel to include web touchpoints — such as email sequences, web-based engagement dashboards, and browser-based renewal reminders — that complement in-app communications.

An upsell is a sales and monetization technique where an existing user is encouraged to upgrade to a higher-value product, plan, or subscription tier. In mobile subscription apps, upselling typically involves persuading a user on a monthly plan to switch to an annual plan (often at a per-month discount), upgrading from a basic tier to a premium tier with more features, or offering an enhanced version of a specific feature the user already uses frequently. Upselling is one of the highest-leverage revenue growth strategies because it targets users who have already demonstrated willingness to pay — the friction is much lower than converting a free user to a first-time subscriber. Effective upselling requires precise timing (presenting the upgrade when the user encounters a limitation or reaches a milestone), clear value communication (showing exactly what additional value the higher tier provides), and frictionless execution (making the upgrade a one-tap action). For web-to-app subscription models, upselling can occur both within the app (in-context prompts when a user hits a feature gate) and on the web (email campaigns, web dashboard prompts, or renewal-time offers). When combined with downselling and cross-selling, upselling forms a comprehensive pricing optimization framework that captures maximum value from each user's willingness to pay.

User acquisition refers to the strategies and activities used to attract new users to a mobile app or platform. It encompasses paid advertising, organic discovery, and referral programs working together to drive installs and grow an engaged user base.

Voluntary churn occurs when a subscriber actively decides to cancel their subscription — they make a conscious choice to stop paying, typically because they no longer perceive sufficient value, found an alternative, or their needs changed. Involuntary churn occurs when a subscription lapses without the user's deliberate intent — most commonly due to a failed payment (expired credit card, insufficient funds, bank-side decline) that isn't resolved before the subscription expires. The distinction matters enormously because the two types of churn require completely different intervention strategies. Voluntary churn is addressed through product improvements, value communication, cancellation deflection flows (offering discounts, plan pauses, or downgrades when a user attempts to cancel), and win-back campaigns. Involuntary churn is addressed through payment recovery mechanisms — smart retry logic, grace periods, dunning communications, and frictionless payment update flows. For many subscription apps, involuntary churn accounts for 20–40% of total churn, representing a significant and often underaddressed revenue leak. Apps using web-based billing have more control over involuntary churn recovery because they own the billing relationship and can implement custom retry schedules, direct email communications, and web-based payment update pages without being constrained by app store billing system limitations.

A web funnel is a structured, multi-step web-based experience designed to guide users from initial awareness to a conversion action — typically a subscription purchase, trial start, or app download. In mobile app marketing, web funnels have become a critical acquisition and monetization strategy, particularly for subscription apps looking to process payments outside the App Store or Google Play to avoid platform commissions of 15–30%. A typical web funnel for a mobile subscription app follows a sequence like: ad click → landing page → value proposition/quiz/personalization flow → pricing/plan selection → web checkout → payment confirmation → app download prompt → in-app activation. By processing the subscription on the web before directing the user to the app, developers retain significantly more revenue per subscriber. Web funnels also offer advantages beyond commission savings: they provide a larger canvas for communicating value (compared to a constrained in-app paywall), enable more sophisticated A/B testing of pricing and messaging, allow for richer attribution data (since web tracking isn't subject to ATT restrictions in the same way), and support more flexible offer structures (downsells, upsells, bundles) that aren't possible within native app store billing. The main challenge of web funnels is the additional friction of requiring users to complete a purchase flow on the web and then separately download the app — making seamless handoff and activation critical to overall funnel performance.

Web landing page optimization is the systematic process of improving the conversion rate of a web page by testing and refining its design, copy, layout, imagery, social proof, pricing presentation, and call-to-action elements. For mobile subscription apps using web funnels, landing page optimization directly impacts the cost-effectiveness of every paid acquisition channel feeding traffic to that page. Key optimization areas include: headline and subheadline testing (communicating the core value proposition in seconds), hero imagery and video (demonstrating the product experience), social proof elements (ratings, testimonials, press mentions, user counts), pricing display format (how plans, discounts, and savings are presented), CTA button design (color, copy, placement, urgency signals), page load speed (every second of delay reduces conversion), mobile responsiveness (the majority of traffic arrives on mobile devices), and trust signals (security badges, money-back guarantees, privacy assurances). Best-in-class subscription app landing pages typically run continuous A/B and multivariate tests, iterating weekly on individual elements while tracking conversion rate, revenue per visitor, and bounce rate as primary metrics.

Web-to-App (Web2App) refers to the strategy and infrastructure that enables mobile app developers to acquire users and process subscription purchases through web-based flows before transitioning the user into the native mobile app experience. In a Web2App model, a user typically discovers the app through a paid advertisement or organic search, lands on a web page where they learn about the product's value proposition, completes a subscription purchase through a web-based checkout (processed by a third-party payment provider like Stripe), and is then directed to download and activate the app with their subscription already provisioned. The Web2App model has gained significant adoption among subscription apps for several reasons: it allows developers to avoid the 15–30% App Store and Google Play commissions by processing payments outside the native billing systems; it provides richer attribution data since web-based tracking isn't subject to the same ATT restrictions that limit in-app attribution on iOS; it offers a larger canvas for communicating value and presenting offers compared to in-app paywalls; and it enables more flexible pricing, offer, and discount strategies that aren't constrained by app store billing rules. The primary technical challenges of Web2App include maintaining a seamless user experience across the web-to-app transition, reliably syncing subscription entitlements between the web billing system and the app backend, handling edge cases (user doesn't download the app, switches devices, etc.), and solving post-iOS 14.5 attribution challenges that affect the ability to connect web conversion events to the advertising campaigns that drove them.

Weekly Active Users (WAU) measures the number of unique users who engage with your app within a 7-day window. WAU is particularly valuable for apps where daily usage isn't expected but weekly interaction is, such as business tools, productivity apps, and analytics platforms. This metric bridges the gap between daily and monthly active users, helping you understand weekly engagement patterns.

A win-back campaign is a targeted marketing initiative designed to re-engage and resubscribe users who have previously cancelled or allowed their subscription to lapse. Unlike general reactivation campaigns that target any inactive user, win-back campaigns specifically focus on former paying subscribers — users who previously saw enough value to pay but chose to leave. Win-back campaigns leverage the unique advantage that these users already understand the product, have already provided their payment information (in many cases), and demonstrated willingness to pay at some point. Effective win-back strategies include: personalized email sequences highlighting new features or content added since the user left, limited-time resubscription offers at a discounted rate, Apple and Google's native promotional offers for lapsed subscribers (which can be targeted at specific user segments), push notification re-engagement for users who still have the app installed, and paid retargeting campaigns on social and display networks. Both Apple (through Subscription Offer Codes and promotional offers) and Google (through Resubscribe offers in Play Billing) provide built-in mechanisms for offering special pricing to lapsed subscribers, making it easier to implement win-back offers that feel integrated with the platform experience.