App Store optimisation (ASO) – how can you increase mobile app visibility?

ASO, that is App Store Optimization, supports an app in building visibility in the App Store and Google Play and in more effectively turning product page visits into installs. In practice, this is not limited to the description itself, but to tailoring the whole listing to the way users search for apps and make download decisions. Well-executed ASO organises metadata, strengthens the message on the screenshots and reduces the gap between the marketing promise and the product’s actual performance. The most important thing is that ASO works best when the listing, product and user reviews are consistent with one another. This also matters because the App Store and Google Play operate differently, so one version of the description and creatives cannot be effectively transferred to both stores. In the following sections, you will find what really affects app visibility and where to start with optimisation.

What is App Store Optimization (ASO) and why is it important?

App Store Optimization (ASO) is the process of increasing app visibility in mobile stores and raising the number of installs generated from visits to the product page. It covers both how easily a user finds the app and whether they actually decide to download it after landing on the listing. It combines work on metadata, visual creatives and quality signals such as ratings, reviews or app stability.

In practice, ASO covers two areas. The first is discoverability, meaning visibility in search results and within the store. The second is conversion on listing, meaning how effective the app page itself is at persuading the user to install.

ASO matters because even a good app will not grow organically if users cannot find it or do not understand its value within a few seconds. Mobile stores are crowded, and the decision to install is usually made very quickly. If an app has few impressions, the problem is visibility; if it has listing visits but few installs, the problem is conversion.

This is also not a one-off action. Store algorithms change, demand is seasonal, app features evolve and the language users use changes too. ASO should be run as an iterative process, not as a one-off writing of the description.

It is also important that the App Store and Google Play differ in listing structure and in the way they index text. This affects the keyword strategy, the structure of metadata and optimisation priorities. Effective ASO requires a separate strategy for each store, even if the app is the same.

1. 01Visibility (Discoverability)Making the app easier to find
2. 02Conversion on the listingPersuading users to install
3. 03Optimisation elementsMetadata, creatives, ratings
4. 04The importance of ASOOrganic app growth

Key to organic success – optimising visibility and encouraging downloads.

Key elements of app listing optimisation

App listing optimisation is made up of four pillars: metadata, visual assets, quality signals and localisation. Each of these areas supports a different moment in the user journey: from finding the app, through clicking the result, to quickly understanding the value and deciding to install. A well-crafted listing does not stop at selecting keywords, but directly and without delay shows why the app may be useful.

• app title, subtitle or short description and other text fields
• long description and keyword fields where the store makes them available
• icon, screenshots, graphic captions and any preview video
• category, promotional texts and consistency of the message with the app’s actual function
• ratings, reviews, performance stability and the quality of the first experience after installation
• language localisations matched to specific countries and search habits

Metadata is the main factor in whether the app appears for relevant queries and whether the user immediately understands what it is for. The title and short text fields should both answer the user’s intent and clearly communicate the benefit. Overly aggressive keyword stuffing usually reduces readability and rarely translates into better conversion.

Visual creatives are crucial at the stage after landing on the listing. The icon sets the first impression, and the first screenshots should show the problem, the way it is solved and the most important use case within a few seconds. The icon, the first screenshot and the first message have the greatest impact on whether the user will consider installing at all.

Quality signals are often overlooked, although in practice they strongly affect ASO results. Low ratings, recurring complaints about bugs, confusing onboarding or a mismatch between the promise on the listing and the app’s real performance can weaken the effect even of very well written metadata. If the listing promises more than the product delivers, both conversion and ratings fall.

Localisation is much more than translation alone. Users in different countries enter different phrases, react differently to messages and may need different usage examples on the screenshots. That is why an effective listing is worth updating after product changes, when entering a new market and after every release that alters the app’s core value.

How to carry out an ASO audit and keyword analysis effectively?

A good ASO audit starts by determining whether the problem concerns visibility in the store, conversion on the product page, or the quality of the post-install experience. This distinction matters, because each of these areas requires a different set of actions. When an app records few impressions in search results, the keyword matching and metadata need to be improved. If users open the listing but rarely install, the cause most often lies in the icon, screenshots, the first message, or a mismatch between the promise and the product.

The audit starts by collecting data from both stores, product analytics and the history of changes in the app. Without this, it is easy to draw inaccurate conclusions, for example to assign a drop in installs to the description when the real problem results from an outage, poorer ratings or the introduction of a new paywall. A good audit does not stop at assessing the copy, but covers the whole chain: the user query, the listing, the installation and the first in-app experiences.

• current metadata in the App Store and Google Play for all languages and markets,
• data from store consoles: impressions, product page views, install rate, traffic sources,
• ratings, reviews and the most common reasons for negative feedback,
• the update history, changes in features, pricing model and onboarding,
• a list of the main competitors visible for the same user intent.

Keyword analysis is not about gathering the largest possible number of phrases, but about identifying those that match real user intent. In practice, you need to connect phrases with problems, use cases, features and the language used by the audience, not the product team. The best keyword is not always the one with the highest volume, but the one that is relevant, understandable and has a chance of leading to an install.

It is worth grouping phrases into clusters, because users reach an app through different paths. Some enter the category name, others the problem they want to solve, and still others a specific feature or an alternative to a well-known app. This division makes it easier to decide which phrases should go into the title, which into the short description, and which should be left for further testing and localisation.

Competitor analysis is needed in order to check not only which phrases competitors appear for, but also how they frame the value proposition. Often the difference does not lie in the words themselves, but in what the app communicates in the first few seconds of contact with the listing. If the competition shows a concrete outcome of use, and your product page talks vaguely about an “innovative solution”, you will lose even with similar visibility.

At the end of the audit, you need to set implementation priorities. First, you change the elements that have the biggest impact on the result and are easiest to verify in the data. It is not worth improving everything at once, because then it is hard to determine what actually worked and what merely happened to coincide with another change.

1. 01Collect input dataStores, analytics, change history
2. 02Diagnose the problem areaVisibility, Conversion or Quality?
3. 03Implement dedicated actionsOptimisation tailored to the diagnosis

An effective audit requires distinguishing visibility from conversion, which allows for precise corrective action.

Optimisation of metadata and visual assets in practice

Optimisation of metadata and visual assets in practice means assigning each listing element one clearly defined role: improving indexing, increasing product page views or raising the install rate. This matters because the title, short description, icon and screenshots do not work in the same way. Some elements make it easier to find the app, while others help convince the user to download it. The best listings combine these functions without diluting the message.

Metadata should be built around the highest-priority keywords and the key benefit for the user. The title and the most important fields should contain the wording people actually use in the store search. At the same time, the whole thing must sound natural, because cramming in keywords reduces readability and often harms conversion. If the user does not understand within 2-3 seconds what the app is for, visibility alone will not be enough.

A long description makes sense when it organises the arguments, clears up doubts and helps the user make a decision, rather than simply repeating keywords. It is worth clearly showing the main use cases, important features and limitations, in a simple and concrete way. This is especially important for subscription apps, specialist apps or those that are easy to misread based on the name alone.

The icon and first screenshots usually have the biggest impact on the decision to open and install. The first screenshot should not tell the whole product story, only show the main use case and the promised benefit straight away. The next graphics develop the message: they present features, ease of use, differences versus alternatives and any proof of usefulness. The first visual assets should sell the result for the user, not the interface itself.

In practice, the most common mistake is designing screenshots like a presentation for an investor or for the internal team. A store user does not need to see the product’s full architecture. They want to know whether the app solves their problem, how quickly it will do so and whether it is trustworthy. That is why the messages on the graphics should be short, factual and focused on one use scenario.

A preview video can help, but only when it quickly shows value and does not blur the message. In many categories, a very clear sequence of screenshots works better than a video that starts too slowly or highlights less important details. The best decision is based on tests, not on the assumption that video always improves listing performance.

Localisation requires more than translating the text. The phrases entered by users, use cases and the way benefits are presented differ between countries. The same applies to screenshots, captions and the order of arguments. Effective localisation means adapting the message to local intent, not copying one template across all markets.

After implementing changes, it is worth looking not only at keyword positions, but also at product page visits, install rate, ratings and user reactions after the update. It happens that better visibility does not translate into more installs because the new message attracts less relevant traffic. That is why listing optimisation is a cyclical process: change, measurement, adjustment and re-matching to the product and the market.

The role of localisation and content adaptation in ASO

Localisation and content adaptation increase the effectiveness of ASO because users search for apps using local phrases and judge the offer through the filter of their own language, habits and expectations. This affects both visibility in results and the decision to install after visiting the product page. Good localisation means adapting to user intent, not literal translation. The same product may require different keywords, a different screenshot layout and a different way of presenting benefits depending on the country.

In practice, localisation should cover not only the title, subtitle and description, but also screenshot captions, the order of messages, use cases and the language of benefits. A user in one country may react more strongly to time savings, while in another they may respond more to simplicity or security. That is why it is better not to replicate one listing across all markets, limiting yourself solely to changing the language.

Well-executed adaptation starts with selecting markets that make business sense and can be supported operationally. It is worth checking whether the app is linguistically ready and whether onboarding, support, payments and in-product messages do not stop at English. First localise the markets you can realistically support after installation. Otherwise, it is easy to end up with more disappointed users, poor ratings and quick uninstalls.

After localisation has been implemented, the results need to be analysed separately for each market. In one country you may have a good level of impressions but weak listing conversion, which usually suggests a problem with the creatives or an ill-fitting promise. In another, conversion may be good but visibility low, which points to the need to refine the phrases and metadata. In ASO, you do not localise “for the sake of it”, but in order to improve specific metrics in a specific market.

1. 01Local phrasesSearching in your own language.
2. 02Understanding intentAdaptation, not translation.
3. 03Comprehensive adaptationKeywords, screenshots, benefits.
4. 04Higher conversionBetter visibility and installs.

Good localisation means adapting to user intent, not literal translation.

The most common mistakes and limitations in the ASO process

The most common mistakes in ASO come from treating it as a one-off app description, rather than as a process based on data, tests and iterations in the product. The result is misguided decisions, because the source of the problem is often not the metadata, but the quality of onboarding, app stability or the promise from the listing that does not match reality. ASO works worst when it is meant to cover up product problems instead of exposing and correcting them.

• Lack of a separate strategy for the App Store and Google Play, despite the fact that both stores differ in metadata fields and indexing methods.
• Changing many elements at once without a hypothesis, which makes it hard to determine what actually improved or worsened the result.
• Stuffing texts with keywords at the expense of readability and a clear message about the app’s value.
• Overly generic screenshots and opening message that do not show the main use case or a specific benefit.
• No update to the listing after a release, a change to the payment model or the addition of a new feature.
• Ignoring user reviews and ratings, even though this is often where the real causes of the decline in conversion and retention can be seen.

The second group of challenges is measurement limitations. Today it is not possible to base the entire assessment on a single data source, because stores, product analytics and attribution systems show different slices of reality. On top of that, results can change under the influence of seasonality, branded traffic, paid campaigns, store algorithm changes and the current quality of the app itself.

This means that a single increase or drop after implementation does not always give a clear answer. If the icon, first screen, description and onboarding were changed at the same time, the result will be difficult to interpret and not very reliable. The safest approach is to test a small number of elements at once and assess the trend, not a single reading after publication.

It is also worth being careful with marketing promises that the product does not deliver. A listing may improve the number of visits or installs in the short term, but if after installation the user lands on a different feature set, an aggressive paywall or low stability, negative reviews and a drop in results will quickly appear. In practice, ASO should be synchronised with the product roadmap, support and release plan, because only then does the effect last longer than one change cycle.

How to measure the effectiveness of ASO activities and what to analyse?

The effectiveness of activities in ASO is assessed through changes in app visibility, visits to the listing and installs after entering the product page. The key is to separate two areas: whether users can find the app at all and whether they want to install it after landing on the page. If you do not separate the visibility problem from the conversion problem, it is easy to improve the wrong element and see no effect. In practice, there is no single metric that shows the full picture. You need to monitor a set of metrics and interpret them in the context of the store, the market and product changes.

The foundation is data from App Store Connect, Google Play Console and product analytics. Store consoles usually show impressions, traffic sources, visits to the app page, installation rate, as well as ratings and reviews. Product analytics complements this picture with what happens after installation: activation, onboarding, retention, uninstalls or technical issues. ASO does not end with installation, because poor product quality quickly lowers ratings, and that affects both conversion and visibility.

• Visibility: the number of impressions in search results and store sections, positions for important keywords, and the share of branded and non-branded traffic.
• Interest in the listing: CTR from search results or store sections to the app page.
• Conversion: installation rate after entering the listing, compared across countries, platforms and creative variants.
• Quality signals: average rating, growth dynamics of reviews, the most frequently mentioned sources of negative feedback, crash rate, payment issues and onboarding problems.
• Quality of the acquired user: activation after installation, retention, uninstalls and how well the acquired traffic matches the promise made in the listing.

Interpreting results depends primarily on which stage of the funnel shows a decline. If the app has few impressions, the cause is usually keywords, metadata, category or poor alignment with user intent. When impressions are there but few people move to the page, it is worth looking at the icon, title, subtitle or short description. If listing visits are high but installs are low, the screenshots, first message, ratings, consistency of the promise and the product’s real appeal usually make the difference.

Data is best reviewed separately for App Store and Google Play, because both stores work differently. They differ in metadata fields, indexing logic and the layout of elements visible even before entering the page. As a result, the same increase or drop does not have to stem from the same cause on both platforms. Applying one interpretation to two stores often ends in poor decisions.

The split by country, language and traffic source is also important. Branded traffic usually converts better than traffic from generic keywords, so a rise in installs does not always mean an improvement in ASO. If an ad campaign launched at the same time, a press article was published or the app received an important release, the store results will overlap with other factors. That is why you should assess ASO changes in trend and over a comparable time window, not on the basis of a single reading from a few days.

In practice, it is best to compare results before and after changing one specific element. If you change the title, icon, screenshots and description at the same time, it will be hard to determine what actually worked. More effective are single hypotheses: a new icon for CTR, new first screenshots for conversion, a new keyword strategy for visibility. Where the store allows experiments, it is worth comparing the control variant with the alternative version, and then assessing the result based on differences in user behaviour.

Beyond the numbers, it is worth regularly reviewing review content. User comments quickly reveal whether the listing promises something the app does not deliver, whether the onboarding is misleading, whether the paywall appears too early or whether localisation is missing. These are operational signals, not merely reputational ones. Often it is reviews that explain why good visibility does not translate into steady growth in installs and retention.

The most practical working model assumes a regular review after every major change in the product or on the market. The launch of a new feature, a pricing adjustment, an interface redesign, entry into a new country or a seasonal increase in demand should trigger a re-analysis of the metrics and an update of the listing. In this approach, ASO works as a data-driven process, rather than a one-off adjustment to the description. This working rhythm usually gives the best chance of a lasting improvement in visibility and conversion.