It is important to collect and analyze real-time data about your app’s ranking and conversion patterns in the App Store and Google Play, understand how seasonal factors affect downloads, and understand the development trends of keywords that drive your app’s growth.
It can be tricky to optimize your keywords and content that is high in search AI for humans and Google Play. However, app store optimization experts know that only a few users have read the detailed description of the app. Therefore, it is wise to conduct keyword research and actively used the results to adapt the description of your mobile application to the requirements of search engine.
Optimize content for your App Store and Google Play listings
Optimizing all aspects of your application’s details can help your application gain more keyword coverage and achieve higher rankings on the most important keywords. This includes optimizing keyword packs, app titles and subtitles, short and long descriptions, and promotional content associated with your app.
Use machine learning to understand App Store and Google Play algorithms
ASO keyword optimization requires accurate data. We have aggregated billions of data points from the App Store and Google Play, combined with our machine learning technology to analyze search volume, trends and other factors which are important to ASO. Through continuous A/B testing, we will work with you to optimize the ideas presented in the app store and increase the conversion rate.
What is the Google Play Store search algorithm?
Many people believe that the search algorithms of Google Play Store and Apple App Store are exactly the same. In fact, our large amount of experimental data proves that the search algorithms of Google and Apple are completely different, and they need different ASO strategies. For starters, the Google Play search algorithm is more complex and unpredictable. Here we study the search algorithm of Google Play Store together to improve your application store optimization strategy.
AI and machine learning in Google Play search
The visibility of your app in the Google Play store depends on how well Google AI tools understand information about the mobile app. In addition, Google’s machine learning model memorizes and recognizes the activities of specific users and provides personalized Google Play search results. You may have encountered this situation: After searching for a piece of clothing, you will see advertisements related to this piece of clothing on the entire desktop. A very similar algorithm is responsible for the visibility of your app in the Google Play store.
When you perform an App Store search, its algorithm checks that the mobile apps in it have related keywords in their descriptions, and word segmentation technology evaluates the ASO weight of these words. Then, the Apple App Store forms a list of apps that fit your search criteria.
Google did the same, but something magical happened. Its AI will check your previous activities, such as search queries, application downloads, etc., and determines your preference based on your historical track, and adjust the list accordingly. Every search result we get on our Android device is unique. Google reset is consistent with our search history.
How to improve your app’s ranking in product listings?
In short, all you have to do is make your application description easy to understand by the Google Play search algorithm. This is more than just filling short and detailed descriptions of the app with popular and relevant keywords. You also need to make your replacement description relevant to the general purpose of the mobile application.
For example, just using the words "mini truck", "transportation", "application" and "moving" in the entire metadata is not a good strategy for Google Play store optimization. In the detailed description of the application, such as "book a minivan in London", "book a minivan or London moving service", and "a minivan booking application to move in London" are more reasonable for search engines.
The Google Play Store uses machine learning to implement its search algorithm to interpret the full meaning, function, possibility, service location, etc. of your Android application. What you have to do is tell Google what kind of service your mobile app offers, has a great user experience, and is completely relevant to the target audience (or intended target, their search history).
Can I see what Google thinks about the detailed description of my app?
Google's machine learning technology can complete text analysis, classify information, use word segmentation technology to split and interpret semantics, and select important words and word blocks from it. ASO practitioners use Cloud NL to check detailed descriptions of Android apps-to ensures that Google understands them.
Therefore, after you have prepared the complete description of the mobile application, paste it into Cloud NL and check the category results. Try to get the highest score -0.99 points.
How to describe my Android application correctly?
Cloud NL extracts words and sentences from the text. It classifies them and calculates the significance score of the entire text. Saliency refers to the nature of words to text. Therefore, taxis, booked taxis, your location, the same highly relevant keywords that you use in the app name, app title, change description, and change description even in the screenshot should be displayed in Cloud NL Very high visibility.
To gain visibility of related keywords in the description, please write appropriate sentences. Don’t use the same keywords to fill the description. Instead, use different keywords to express clearly which user needs the application can meet.
This is to find the best choice for your application. Some application developers don't care about turning the description into anyone to improve search rankings. Others would rather sacrifice the "substitution of search algorithms" to make app users sound clear. A/B testing helps you find your way.
A/B testing and testing focus
In the process of A/B testing, we mainly focus on testing your icon, screenshot, title and description to achieve the best conversion rate.
Through the A/B test of this series of important parameters, it is ensured that the quantitative data can draw correct conclusions. Use traffic from various channels and audience segments to understand what users really think when they see your app. Understand the "why". Why did the user choose to click, or why choose to continue to move?
Why do A/B testing?
With A/B testing, you can try to use different product details in the App Store and Google Play. This allows data-driven decision-making and limits costly errors caused by emotional decision-making. Through a series of test data, you can statistically determine how different creative assets in the store list increase the conversion rate of the application. This data can also help you accurately measure the impact of new creatives and messaging.
It’s important to always test creative assets and metadata in the store list. According to statistics, the conversion rate of frequently tested developers is 50% higher than that of competitors. This is why top companies including Kabam, Sephora and Microsoft are constantly conducting A/B testing and updating the assets in their store listings. A/B testing is essential for conversion rate optimization and overall App Store optimization.
A/B tests your current application-do more, convert more!
Your icon, screenshot, video, title and overall metadata are the key factors affecting downloads. The user only needs to give each application a short time window (about six seconds), and then switch to another application. Different experiences of A/B testing can help convert more users to browse through the App Store and Google Play.
In addition to improving creatives, it’s key to understanding which marketing channels are most effective for your app. A/B test creatives in paid channels to understand which variants provide higher conversion rates, more user engagement will help reduce CPI and increase return on investment.
Easy A/B testing technology
Each store has a completely different user experience, which affects user behavior and conversion metrics. We will evaluate the conversion of each channel and landing page experience separately, and execute in the best test environment to produce reliable results.
Conversion optimization and A/B testing require creative assets. Our creative services team will build all product listing assets for testing, which may include (but is not limited to) A/B testing in the following areas:
Attribution analysis and reporting for ASO and mobile marketing
Accurate measurement to understand your entire organic (ASO) and paid channel user acquisition channels. By studying the conversion benchmarks of natural search and paid traffic sources, the growth of downloads and user engagement, including external factors that may affect the results. The effect of mobile marketing of the application is continuously optimized.
How to analyze the influence of various factors on the results of your mobile marketing?
Measuring App Store optimization activities (and even paying user acquisitions) is not always simple, just like looking at the number of installs or actions on a particular channel. It is important to understand changes in seasonal demand, how different sources of external traffic affect organic traffic, and accurately measure ROIS (return on investment).
Take time to understand how to filter the influence of various traffic sources from broadcasts and large-scale online media resources. It is necessary to clarify the influence between ASO or paid user acquisition and traffic and installs. This may be caused by broader marketing or by popularity.
Gradually establish an effective ASO and paid user acquisition plan. Use the knowledge of ASO to maximize the visibility and conversion rate of the store, and combine it with the knowledge of the paying user acquisition channels to have the greatest impact inside and outside each store. The result is tremendous growth and return on investment.