Glossary
ASO glossary for App Store screenshots
A comprehensive reference of App Store Optimization terms every app marketer and designer should know. Each definition explains what the concept means, why it matters, and how it connects to screenshot design and conversion optimization on iOS and Google Play.
Core ASO terms
ASO (App Store Optimization)
App Store Optimization is the practice of improving an app's visibility, search ranking, and conversion rate within the Apple App Store and Google Play Store. ASO encompasses keyword strategy, metadata optimization, visual asset design, ratings management, and localization. For screenshot designers, ASO determines the strategic context: which benefits to highlight, which keywords to reinforce in caption text, and how to sequence frames for maximum conversion. A well-optimized listing combines strong metadata with compelling visuals — screenshots are the visual half of that equation.
Conversion rate (CVR)
Conversion rate is the percentage of users who visit your app's store listing and then install the app. It is one of the most important ASO metrics because both Apple and Google use it as a ranking signal — apps that convert better tend to rank higher in search results, creating a compounding growth loop. Screenshots are the single biggest lever for improving CVR because they are the first visual element most users evaluate. Even a small improvement in CVR — say from 25% to 30% — can translate into thousands of additional installs per month without any increase in traffic.
Impression
An impression is recorded each time your app appears in a store search result, browse listing, featured placement, or other discovery surface. Impressions represent the top of your conversion funnel — they measure raw visibility before any user engagement occurs. Tracking impression volume by keyword and by source (search vs. browse) helps you understand where your traffic originates. A high impression count with a low install rate indicates a conversion problem, which is often solvable through better screenshot design and metadata alignment.
Tap-through rate (TTR)
Tap-through rate is the percentage of users who see your app in search results or browse listings and then tap to open your full store listing page. TTR is the intermediate step between impression and install and is heavily influenced by your app icon, title, subtitle, and the first visible screenshots. On iOS, the first two to three screenshots are displayed inline in search results, making them a primary driver of TTR. A low TTR relative to competitors in your category typically signals that your visual first impression needs improvement.
Install rate
Install rate is the percentage of users who view your full store listing page and then proceed to download the app. Unlike the broader impression-to-install metric, install rate isolates the conversion performance of your listing page itself. This makes it the most direct measure of how well your screenshots, description, ratings, and overall listing work together. Improving install rate through better screenshots is one of the most cost-effective growth levers available because it multiplies the value of every visitor your listing already receives.
Keyword density
Keyword density refers to the frequency and prominence with which target keywords appear across your app listing metadata, including the title, subtitle, keyword field (iOS), and description. While keyword density in traditional SEO can lead to penalty for "stuffing," ASO requires a more nuanced balance: your primary keyword should appear in the title, secondary keywords in the subtitle, and supporting terms in the description. Screenshot caption text should reinforce these same keywords to create message consistency, though the captions themselves are not indexed for search by Apple or Google.
Keyword difficulty
Keyword difficulty is a score that estimates how hard it will be to rank on the first page of search results for a given keyword. High-difficulty keywords are typically short, generic terms dominated by well-established apps with large install bases and strong ratings. Lower-difficulty long-tail keywords are often more valuable for newer apps because they attract higher-intent users with less competition. Understanding keyword difficulty helps you choose which benefits to emphasize in your screenshot captions — aligning your visual messaging with the keywords you can realistically win.
Organic installs
Organic installs are downloads that come from users who discover your app through store search, browse, featured placements, or top charts without being driven by paid advertising. Organic installs are the primary goal of ASO because they compound over time and carry no per-install acquisition cost. Improving your screenshots directly increases organic conversion — every visitor who arrives through search or browse is more likely to install when your visual assets clearly communicate your app's value. A strong organic install base also signals quality to the store algorithms, improving your ranking further.
Paid vs. organic mix
The paid vs. organic mix describes the proportion of your total installs that come from paid acquisition channels (such as Apple Search Ads, Google Ads, or social media campaigns) versus organic discovery within the store. A healthy app typically derives 60-80% of installs from organic sources, with paid campaigns used to accelerate growth and boost visibility. Screenshots play a dual role: they must convert organic traffic that arrives with high intent, and they must also convert paid traffic that may be less familiar with your brand. Optimizing screenshots improves both channels simultaneously.
Screenshot-specific terms
Screenshot storytelling
Screenshot storytelling is the practice of sequencing your screenshot set to communicate a narrative arc rather than presenting a random collection of features. A well-structured story typically opens with the primary outcome or value proposition, follows with supporting features ordered by impact, and closes with social proof or a call to action. This narrative structure mirrors how users naturally evaluate products — they want to know the benefit first, then understand how it works, then see evidence that others trust it. Apps that tell a coherent story through their screenshots consistently outperform those that treat each frame as an isolated feature callout.
Hero frame
The hero frame is the first screenshot in your gallery and the single most important visual asset in your entire store listing. Because it appears in search results and is the first thing users see when they open your listing, the hero frame must instantly communicate your app's primary value proposition. An effective hero frame combines a concise, benefit-driven headline with a product screen that demonstrates the core experience. Data shows that most install decisions are made based on the hero frame alone, with fewer than 10% of users scrolling past the third screenshot. Invest your strongest design and testing effort here.
Feature frame
A feature frame is a screenshot dedicated to showcasing a single, specific capability of your app. Feature frames form the middle section of your screenshot sequence, typically occupying positions two through six. Each frame should present one distinct benefit with a clear headline, a relevant product screen, and minimal supporting elements. The key to effective feature frames is prioritization: order them by user impact, with the most compelling differentiators appearing earliest. Avoid the common mistake of trying to show every feature — instead, select the four to five capabilities that matter most to your target users.
Social proof frame
A social proof frame is a screenshot dedicated to showcasing trust signals such as user ratings, download milestones, press quotes, awards, or notable customer logos. Placed toward the end of the screenshot gallery, it serves as the closing argument in your storytelling sequence — after showing the value and demonstrating features, you provide evidence that others have validated the product. Social proof is particularly effective for newer apps competing against established players, as it reduces perceived risk for the user. Common formats include a clean layout with a star rating, a quote, and a download count or "Featured by Apple" badge.
Device framing
Device framing is the visual technique of presenting your app's product screens within a realistic device mockup — such as an iPhone, Pixel phone, or iPad — rather than showing raw screenshots at full bleed. The device frame provides visual context, helping users immediately understand what the app looks like on their actual hardware. Consistent framing across all screenshots (same device model, angle, shadow, and color) reinforces brand consistency and makes the overall set feel polished. Some top apps skip device frames entirely for a cleaner look, but for most listings, framing adds professionalism and visual grounding.
Safe area
The safe area is the region within a screenshot where content will not be clipped, obscured, or overlapped by device hardware elements such as notches, Dynamic Island, rounded display corners, or status bar overlays. When designing screenshots with device frames, critical elements like headline text and key UI must stay within the safe area to remain fully visible. On iOS, the safe area insets vary by device generation. On Google Play, rounded corners on modern Android devices can clip content placed at the extreme edges. Always test your final exports on-device or in a simulator to verify that nothing important is cut off.
Visual hierarchy
Visual hierarchy is the arrangement of design elements so that the viewer's eye naturally flows from the most important information to the least important. In app store screenshots, this typically means a bold headline at the top, a device-framed product screen in the center, and optional supporting text or callouts below. Size, color contrast, weight, and spacing all contribute to hierarchy. A screenshot with poor visual hierarchy looks cluttered and forces the user to figure out where to look first — which, at mobile browsing speed, usually means they move on without processing your message.
Screenshot sequence
The screenshot sequence is the specific order in which your screenshots are arranged in your store gallery. The sequence determines the narrative flow and directly impacts conversion because users experience your screenshots from left to right (or right to left in RTL locales). A proven sequence pattern is: hero frame with primary value proposition, two to three feature frames ordered by impact, a social proof frame, and a closing frame with a call to action. Reordering your existing screenshots is one of the easiest and most impactful A/B tests you can run — changing the sequence alone can move conversion rates significantly without any new design work.
Above the fold (App Store context)
In the App Store context, "above the fold" refers to the content visible on a store listing before the user scrolls down. On iOS, this includes the app icon, title, subtitle, ratings, and the first two to three screenshots (in portrait orientation). On Google Play, the feature graphic sits above the fold, followed by the app's metadata. Everything above the fold receives disproportionate attention because many users make install decisions without scrolling further. Optimizing your above-the-fold elements — especially the hero screenshot and app icon — is the highest-leverage ASO activity you can perform.
First impression frame
The first impression frame refers to whichever screenshot or screenshots are visible to the user before any interaction occurs. In iOS search results, this is the first two to three portrait screenshots displayed inline. On Google Play, it is the feature graphic or the first screenshot visible beneath it. The first impression frame concept emphasizes that users form an opinion about your app within seconds of seeing your listing, and most of that judgment is visual. Your first impression frame must be self-contained — it should communicate a clear benefit without requiring the user to swipe or tap for more context.
Localization terms
Text expansion
Text expansion refers to the increase in character count and visual length when English text is translated into other languages. German, French, Portuguese, and Finnish are common examples where translated text can be 20-35% longer than the English source. For screenshot design, this is a critical layout consideration: a headline that fits perfectly in English may overflow or require a smaller font size in German. Designers must build flexible layouts with enough whitespace and padding to accommodate longer strings without breaking the visual hierarchy or requiring per-locale layout adjustments.
RTL (Right-to-Left)
RTL refers to languages that are read and written from right to left, such as Arabic, Hebrew, Persian, and Urdu. Supporting RTL locales in your screenshots requires more than just translating text — the entire layout must be mirrored. Text alignment flips from left to right, UI elements that imply direction (arrows, progress indicators) must be reversed, and the visual reading flow of each frame changes fundamentally. Many apps skip RTL localization because of the design effort involved, but the Middle East and North Africa represent significant markets where properly mirrored screenshots can dramatically improve conversion rates.
Locale
A locale is a specific combination of language and region that defines how content should be presented to users in a particular market. For example, en-US (English, United States) and en-GB (English, United Kingdom) are different locales despite sharing the same language. Locales affect date formats, currency symbols, spelling conventions, and cultural references. The App Store supports approximately 40 locales, while Google Play supports over 75. Each locale can have its own set of screenshots, meaning a thorough localization strategy can require managing dozens of distinct creative sets.
Localized screenshots
Localized screenshots are App Store or Google Play screenshots that have been adapted for different languages, regions, or cultural contexts. Localization goes beyond translation — it includes adjusting date formats, currency symbols, imagery, and even the benefit messaging to resonate with each target market. Studies consistently show that localized screenshots improve conversion rates by 20-30% in non-English markets. For screenshot designers, localization introduces practical challenges like text expansion, right-to-left layout mirroring, and maintaining visual quality across dozens of locale-specific exports.
Cultural adaptation
Cultural adaptation is the process of modifying screenshot content to resonate with the values, aesthetics, and expectations of a specific cultural market. This goes beyond language translation to include changes in color choices (colors carry different meanings across cultures), imagery (people, gestures, clothing), sample data (local currencies, local names), and even benefit messaging (features that are a priority in one market may be irrelevant in another). For example, screenshots targeting Japan may benefit from more detailed, information-dense layouts, while Scandinavian markets often respond better to minimalist designs. Effective cultural adaptation requires market research and, ideally, review by native speakers.
Market tier
Market tiers are groupings of countries based on their revenue potential, user acquisition cost, and strategic importance for app monetization. Tier 1 markets (US, UK, Canada, Australia, Germany, Japan) typically have the highest willingness to pay and strongest in-app purchase revenue. Tier 2 and Tier 3 markets offer higher volume at lower revenue per user. Understanding market tiers helps prioritize which locales to target with localized screenshots first. Localizing screenshots for your top five Tier 1 markets usually delivers the highest ROI, while broader localization to Tier 2 markets is a scale play that tools like PerfectDeck can automate.
Translation vs. localization
Translation is the act of converting text from one language to another while preserving the original meaning. Localization is the broader process of adapting an entire experience — including visuals, formats, cultural references, and user expectations — for a specific market. In the context of app store screenshots, translation means swapping English headlines for their equivalents in other languages, while localization means also adjusting the layout for text expansion, changing sample data to reflect local conventions, mirroring for RTL scripts, and potentially reordering features to match local priorities. Translation is a subset of localization, and treating it as the whole job is a common mistake that leaves conversion gains on the table.
Pseudo-localization
Pseudo-localization is a testing technique where placeholder text is generated to simulate the visual characteristics of translated content without performing actual translation. Pseudo-localized strings typically add accented characters, extend text length by 30-40%, and include bracket markers to identify hardcoded strings. For screenshot design, pseudo-localization is invaluable because it reveals layout breakpoints — headlines that overflow, text boxes that clip, and font sizes that become unreadable — before you invest in real translations. Running a pseudo-localization pass early in the design process saves significant rework and ensures your layouts will hold up across all target locales.
Testing and optimization terms
A/B testing (App Store context)
A/B testing in the context of ASO means running controlled experiments where a portion of store visitors see a variant of your listing (different screenshots, icon, or description) while the rest see the original. Google Play Console offers native store listing experiments, and Apple provides product page optimization (PPO) for the same purpose. For screenshots, common tests include headline copy variations, frame ordering, background color, and device framing style. The key to valid results is testing one variable at a time and running each experiment for at least seven days to reach statistical significance. Even modest conversion lifts compound into substantial install gains over time.
Product Page Optimization (PPO)
Product Page Optimization is Apple's native A/B testing framework for App Store listings, introduced with iOS 15. PPO allows developers to create up to three treatment variants of their product page, each with different screenshots, app icons, or preview videos. Apple then splits traffic between the original and the treatments, measuring conversion rate differences. PPO is one of the most important tools for screenshot optimization on iOS because it provides real-world data on which visual approaches convert better. Tests typically need seven to fourteen days of traffic to produce statistically reliable results, and winning treatments can be applied permanently with a single tap.
Store listing experiments
Store listing experiments are Google Play Console's built-in A/B testing feature that lets you test different versions of your store listing elements — including screenshots, icon, short description, and feature graphic — against each other with live traffic. You can run both global experiments (affecting all locales) and localized experiments (targeting a specific language). Google's system automatically calculates statistical significance and recommends when to apply a winner. For screenshots, store listing experiments are essential for validating design decisions with real data rather than relying on intuition. The most impactful first test is usually the hero screenshot or the overall frame sequence order.
Conversion lift
Conversion lift is the measurable increase in conversion rate produced by a specific change to your store listing, expressed as a percentage improvement over the baseline. For example, if your original screenshots convert at 25% and a new variant converts at 28%, the conversion lift is 12%. Conversion lift is the primary success metric for screenshot A/B tests and is directly tied to business impact — a 10% lift on a listing that receives 100,000 monthly visitors translates to 10,000 additional installs per month. Tracking cumulative conversion lift across multiple rounds of testing helps quantify the total ROI of your screenshot optimization efforts.
Statistical significance
Statistical significance is a measure of confidence that the difference in performance between two test variants is real and not the result of random chance. In ASO testing, a result is typically considered significant at the 90% or 95% confidence level, meaning there is only a 5-10% probability that the observed difference is due to noise. Ending a test too early — before reaching significance — is one of the most common mistakes in screenshot optimization because small sample sizes produce unreliable results. Both Apple PPO and Google store listing experiments provide built-in significance indicators, but a general rule is to run tests for at least seven days with sufficient traffic volume.
Control variant
The control variant is the original, unchanged version of your store listing that serves as the baseline in an A/B test. All treatment variants are compared against the control to determine whether changes produce a statistically significant improvement or regression. Maintaining a clean control is essential for valid testing — if you change your control mid-test (for example, by updating your app description while testing screenshots), the results become unreliable because you cannot isolate which change caused the observed effect. After a winning variant is identified, it becomes the new control for subsequent tests, enabling continuous iterative improvement.
Metrics and analytics
Conversion velocity
Conversion velocity is the rate at which listing views turn into installs over a given time period. Unlike conversion rate, which is a static percentage, conversion velocity captures momentum — a sudden spike in installs relative to views signals to the store algorithms that your app is resonating with users. Both Apple and Google factor velocity into their ranking algorithms, meaning apps with accelerating install rates tend to climb charts and gain additional organic visibility. Improving your screenshots is one of the fastest ways to boost conversion velocity because the change takes effect immediately across all traffic without requiring new user acquisition spend.
Browse vs. search traffic
Browse traffic consists of users who discover your app through editorial features, top charts, category listings, or "similar apps" recommendations, while search traffic comes from users who type a specific query into the store search bar. These two traffic sources have fundamentally different intent levels: search users already know what they want, while browse users are exploring. Your screenshots must serve both audiences. For search traffic, screenshots should reinforce the keyword match and quickly confirm relevance. For browse traffic, screenshots need to capture attention and communicate your app's unique value without prior context. App Store Connect and Google Play Console both report the split between these sources.
Re-engagement rate
Re-engagement rate measures the percentage of users who return to your app after a period of inactivity. While re-engagement is primarily driven by product quality and push notification strategy, screenshots play an indirect but important role. When your screenshots accurately represent the in-app experience, users arrive with correct expectations, leading to higher satisfaction and stronger retention. Misleading screenshots may boost initial install rates but will increase churn and reduce re-engagement because the product does not match the promise. Aligning your screenshots with the real user experience is a long-term investment in re-engagement and lifetime value.
Retention impact
Retention impact refers to the downstream effect that your store listing — and specifically your screenshots — has on user retention metrics like Day 1, Day 7, and Day 30 retention. Screenshots that set accurate expectations attract users whose needs genuinely match your app's capabilities, resulting in higher retention. Conversely, screenshots that over-promise or misrepresent features attract low-quality installs that uninstall quickly, dragging down retention rates and negatively affecting your store ranking. When evaluating screenshot changes, consider not just the immediate conversion lift but also whether the new assets attract users who will stick around and generate long-term value.
Funnel drop-off
Funnel drop-off is the percentage of users lost at each stage of the conversion funnel, from impression to listing page view to install. Analyzing where the biggest drop-off occurs tells you which part of your listing needs the most attention. A high drop-off between impression and page view suggests your icon, title, or first visible screenshot is not compelling enough in search results. A high drop-off between page view and install indicates that users open your listing but are not convinced by what they see — typically pointing to weak screenshots, low ratings, or a confusing description. Mapping your funnel drop-off rates helps you prioritize optimization efforts for maximum impact.
Create ASO-ready screenshots with PerfectDeck
PerfectDeck helps you apply every concept in this glossary to your screenshot workflow. Generate on-brand, localized App Store visuals with AI — designed for conversion from the first frame, optimized for every locale, and ready to publish in minutes.