There are many ASO services in the world that solve various tasks related to search engine optimization in mobile app stores. They all have their advantages and disadvantages, one of the main disadvantages is closed data analysis algorithms, ASO specialist does not have access to raw data, most services do not know how the popularity of keywords is formed, there is no way to check the correctness of the algorithm. We create open source ASO automation software so that each user has full access to all data and algorithms, can offer their own functions or add their own code.
You can create a set of keywords and track the position of your app in Google Play search
The tool can analyze suggestions in the store, find derived keywords and calculate their popularity
Analyze by which keys your competitors are indexed, analyze their positions and the quality of ASO
📌Monitoring of app positions in search
📌Checking the indexing of the app
📌Collection of semantic core for different countries
📌Search and research of competitors
📌Analysis of similar apps
📌Monitoring of popular keywords
📌Creation and automation of ASO
📌Research of competitors
📌Automation of data analysis
📌Opportunity to join the development
📌Analysis of market leaders
📌Tracking of installs
📌Search and analysis of the niche
One of the most effective ways to collect the semantic core for your app is to analyze search suggestions in the app store. The more users write a keyword, the higher it appears in the suggestions.
To use the suggestion flag in Asolytics, use the --kay switch and specify the keyword as a parameter. The algorithm will recursively check all search suggestions and find all derived keywords that contain the original keyword. Based on their order and depth of recursion, the relative popularity of the found keywords will be determined.
Use the --gl and --hl keys to specify the country and language.
The number of derived suggestions is one of the criteria for determining the popularity of a keyword. The popularity of a keyword is always directly proportional to the number of derived suggests, so the more suggests are found, the more often users use this keyword in search, and the more traffic it can bring.
To determine the most popular keywords on Google Play, use the --trends option. To specify the country and language, use the --gl and --hl options. The table will display trending search queries and their relative popularity. The algorithm sequentially substitutes letters of the alphabet and collects the most popular suggestions.
You can get a lot of additional information about your competitors on Google Play by using the --average option with the package ID of the app you want to analyze. Asolytics automates the analysis of public information sources.
You will get the following data:
The software allows you to track the position of the application in Google Play search by specified keywords. To start this function, use the --tracker option. Keywords are passed as a parameter, separated by semicolons (for example, "workout at home; fitness; fitness plan"). Alternatively, the keywords can be loaded from a file using the --file option, with the path to the keyword file passed as the --tracker parameter. As the --id parameter, pass the bundleID of the program whose positions you want to track To specify the country and language, use the --gl and --hl options.
If you use a keyword file, make sure that each keyword in the file starts on a new line
You can extract keywords used in the metadata of any app. To do this, you need to use the --extract option and pass the bundleID of the application you want to analyze as a parameter. Asolytics uses artificial intelligence to recognize keywords in:
The table will display the position of the app in Google Play search for all found keywords. To specify the country and language, use the --gl and --hl options
The bottom of the table shows the indexing coefficient of metadata, the higher it is, the more traffic this app receives
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