ASA advertising in the last 7 days / Advertising on Google in the last 7 days

The number of unique devices launching the app each week (multiple launches from the same device within a calendar week are counted as only one).

Keywords advertised in the last 7 days

The average number of times each active user launches the app per week during the selected dates.

The number of unique devices launching the app each day (multiple launches from the same device within the same day are only recorded as one).

Daily revenue / Daily active users

Supports viewing the percentage of keyword ad impressions on Google Play for User Account Control (UAC) ads.

The keywords appear twice or more in the statistical application description

The number of unique devices launching the app each month (multiple launches from the same device within a calendar month are only recorded as one).

This score is based on a comprehensive analysis of the app's store performance, downloads/revenue, and user usage data, used to measure the app's influence in the current country/region. The maximum score is 100.

The average number of times each active user launches the app per month within the selected dates.

The 7-day active user retention rate is the percentage of users who were active on a selected date and still launched the app N days later, out of the total number of active users at that time. For example, if an app had 100 active users on January 1st, and 50 of them launched the app on January 8th, then the 7-day active user retention rate for January 1st is 50%.

Weekly cumulative revenue / Weekly active users

Taking into account the popularity and bid share of each bidding keyword, the value is set between 0 and 100.

Application status: online, unavailable, pre-order, etc.

Keyword difficulty is categorized into S, A, B, C, D, and E, indicating the level of competition for a keyword. Higher difficulty levels indicate more intense competition. Ranking in the top ten is considered when evaluating highly competitive keywords.

Monthly cumulative revenue / Monthly active users

Taking into account the popularity and bid share of each bidding keyword, the value is set between 0 and 100.

The number of unique devices that launch the app within the selected period (multiple launches from the same device within the selected period are recorded as only one).

The percentage of devices with a particular app installed out of the total number of devices with the app within the selected date range.

The active dormancy rate is the percentage of users who were active on a selected date but did not launch the app after N days. For example, if an app had 100 active users on January 1st, and 50 of them did not launch the app by January 8th, then the 7-day active dormancy rate for January 1st is 50%.

This displays the percentage of active users out of total active users for a specific app across different cumulative active days in a given month. Active days are categorized as follows: 1-3 days, 4-10 days, and ≥11 days (viewable by month).

The average number of times each active user launches the app per day during the selected dates.

Keyword search result change rate refers to the average number of changes in the top ten search results for each keyword.

The average number of times each active user launched the app within the selected dates. For example: average daily launches per user / average weekly launches per user / average monthly launches per user.

Average usage time of the app per active user within the selected dates

The probability of the following applications appearing in keyword search results within 7 days.

In iOS 14, search results for certain keywords will be automatically corrected to show results for other words. For example, entering "wechit" will automatically correct and display search results for "wechat". "Wechit" is referred to as the corrected word, and "wechat" as the corrected word.

You can switch between chart mode, list mode, and overseas mode according to your own usage needs.

The spending power distribution of users of this app was analyzed. A model was built and scored based on data such as app installation and activity levels, device brand and model, and frequent user locations. A score of 80 or above indicates high spending power, 40-80 indicates medium spending power, and below 40 indicates low spending power.

App information changes/additions

Keyword search result change rate refers to the average number of changes in the top ten search results for each keyword.

The number of unique devices that launched a specific app within the selected date range; [Multiple launches by the same device within that day will only be recorded as one active user].

Average daily active users of all game apps

The number of devices downloading the app for the first time does not include updates and re-downloads.

The probability of the following applications appearing in keyword search results within 7 days.

Statistics on the number of apps added/removed/online in each category of the App Store

Recent revenue fluctuations over X days represent the change in total downloads compared to the same number of days in the previous period. For example, revenue fluctuations over the last 7 days (T-3) represent the change in total revenue from August 8, 2023 to August 14, 2023 compared to the change in total downloads from August 1, 2023 to August 7, 2023.

Keywords appearing two or more times in the statistical application description

Characteristics of user devices that used the app within the selected dates, including network operator, operating system, brand, distribution rate, price, and launch date.

Pre-registration can attract and retain core high-value users earlier, resulting in higher first-day and first-week downloads. It can also help games climb to the top of the app store download charts faster and has an advantage in search rankings.

Statistics on the number of apps listed/removed/online in each category on Google Play

This keyword represents the estimated number of installs for the application.

Only the actual number of days installed is counted. Uninstallation and reinstallation are not included in the count.

This data comes from official App Store data. It represents the number of apps appearing in the search results when searching for this keyword on the App Store.

This data comes from official App Store data. It represents the number of apps appearing in the search results when searching for this keyword on the App Store.

The percentage of devices with a particular app installed on the market out of the total number of devices on the selected date range.

App attention on the mobile internet

The estimated number of impressions this keyword will bring to the application.

Within the selected date range, this represents the percentage of new users who launched the app on a given day and continued to use it for N days thereafter, out of the total number of new users on the selected date range. Examples include: 1-day retention, 7-day retention, 14-day retention, 30-day retention, etc.

In-app purchases are indicated by a $ symbol.

The trending keywords for iOS 11 and iOS 12 are the same; the blue keywords are those displayed on the App Store page.

This refers to the average number of changes in the top ten search results for each keyword.

Keyword opportunity score comprehensively considers keyword search index and ASO difficulty, with a value ranging from 0 to 100. The higher the opportunity score, the easier it is to obtain higher search rankings and search downloads.

App store chart types, such as free charts, paid charts, and top-grossing charts.

Total usage time of all active users within the selected date period

TapTap officially removed the "New Products Chart" on March 22, 2023. (The last update of DianDian Data was on March 21 at 03:29.)

Selected date range, current keyword ranking of newly added applications

The new installation dormancy rate is the percentage of users who installed the app on a selected date but did not launch it after N days, out of all new installations at that time. For example, if an app had 100 new installations on January 1st, and 50 of those users did not launch the app by January 8th, then the 7-day new installation dormancy rate for January 1st is 50%.

Cumulative revenue/cumulative downloads over the most recent N days (including the current day), for example: 7-day RPD/30-day RPD/60-day RPD/90-day RPD/180-day RPD/365-day RPD

One-star, two-star, three-star reviews

The new installation/uninstall rate is the percentage of users who newly installed the app on a selected date and then uninstalled it N days later, out of all new installations at that time. For example, if an app had 100 new installations on January 1st, and 50 of those users uninstalled it by January 8th, then the 7-day new installation/uninstall rate for January 1st is 50%.

The new installation churn rate is the percentage of users who installed the app on a selected date but did not launch or uninstall it on the same day.

Within the statistical period, this is the ratio of the number of overlapping devices to the number of active devices for the selected application. Taking the overlap between A and B as an example, the overlap rate of A = the number of overlapping devices between A and B / the number of active devices of A, i.e., A∩B/A; the exclusivity rate of A = the number of active devices of A - the number of overlapping devices between A and B / the number of active devices of A, i.e., (AA∩B)/A.

Reviews are displayed directly on the Google Play app details page. Other reviews can only be viewed by clicking "View all reviews" on Google Play.

Four-star and five-star reviews

The "popularity" of keywords in the App Store comes from the official App Store and directly reflects the search popularity of that keyword within the App Store. Here is a detailed explanation of keyword popularity: I. Definition and Source: Popularity data is provided by the App Store and represents the search popularity of a keyword within a specific time period. The level of popularity directly reflects the frequency and level of user search for that keyword. II. Popularity Levels: According to reference article 1, popularity is typically distributed from 0 to 100, where 0 represents the lowest and 100 represents the highest. When the popularity is between 0 and 5, the keyword is almost impossible for users to find in the App Store and can therefore be largely ignored. Keywords with a popularity between 6 and 29 are occasionally searched by some users with specific needs, but the volume is small. If highly relevant to the product, these keywords can be selected appropriately. Keywords with a popularity between 30 and 69 are frequently searched by users in the App Store, and keywords in this range are worth paying attention to. Keywords with a popularity between 70 and 100 are considered popular and are frequently searched by users. However, most of these keywords also have relatively high competition. III. Relationship with Search Volume: Generally speaking, the higher the popularity of a keyword, the more times that word is searched in the App Store every day. High-popularity keywords often mean higher exposure and more potential users.

Keywords with a search index greater than 4605

Profit models include in-app purchases and advertising.

The list of apps whose rankings have dropped the fastest for the selected date range.

Keywords that have entered the top 100 at least once in the past 3 months

The list of apps with the fastest-rising rankings for the current keywords within the selected date range.

Cumulative revenue/cumulative downloads over the past N days (including the current day), for example: 7-day RPD/30-day RPD/60-day RPD/90-day RPD/180-day RPD/365-day RPD

Recent download fluctuations over X days represent the change in total downloads compared to the same number of days in the previous period. For example, the recent 7-day (T-3) download fluctuations represent the change in total downloads from August 8th to August 14th, 2023 compared to the total downloads from August 1st to August 7th, 2023.

Net revenue from in-app purchases in app stores

The estimated sales figures for apps on the App Store are calculated by DianDian Data using a data model and are for reference only.

Selected date range, suggested terms in the App Store search dropdown for the current keyword.

Cumulative revenue/cumulative downloads since launch

App ranking in the current real-time ranking list

The ranking snapshot only shows valid changes; changes caused by the removal of a single app are not displayed here. For complete change data, please click "Weekly Ranking Update Monitoring" and select the "All Changes" button.

This displays the percentage of active users of a specific app across different launch intervals within a given month. Launch interval segments: first launch, 0-24 hours, 1 day, 2 days, 3 days, 4 days, 5 days, 6 days, 7-14 days, ≥15 days (can be viewed by month).

Within the selected date period, this displays the percentage of active users of a particular app across different launch count segments: 1-3 launches, 4-6 launches, 7-9 launches, 10-14 launches, and ≥15 launches (viewable by daily, weekly, and monthly dimensions).

Comparison of ranking changes from the previous day

Within the selected date period, the average percentage of app launches per hour within a 24-hour period. Percentage of launches per hour = Number of launches per hour / Total number of launches.

The App Store's "Search Index" is a quantitative metric used to measure the popularity or search frequency of specific keywords or apps in the App Store's search function. This index helps developers, marketers, and other stakeholders understand how users discover and search for apps, and which keywords or phrases are more effective at attracting target users. Prior to February 6, 2020, the App Store officially provided keyword search indexes; this data was typically collected and calculated directly by the App Store and was considered highly authoritative. However, since then, the App Store no longer provides such data, possibly due to privacy policies, market competition, or other reasons. Since then, third-party data providers (such as "DianDian Data") have begun calculating search indices through other methods. These calculations are typically based on multi-dimensional data such as web traffic, downloads, and related keywords. Specifically, third-party calculated search indices may consider the following factors: Web Traffic: By analyzing user search behavior in the App Store, such as clicks and views of search keywords, the search popularity of a keyword can be estimated. Downloads: Observing the download volume of apps related to a specific keyword can indirectly reflect the search effectiveness of that keyword. If a keyword is associated with a large number of downloads, its search index is likely to be relatively high. Related keywords: App stores typically provide related keywords based on users' search history and habits.

This data comes from official App Store data. It represents the number of apps appearing in the search results when searching for this keyword on the App Store.

The average duration of each session within the selected period (viewable by day, week, and month; only available in China).

Estimated number of searches for this keyword

Story keyword coverage statistics for the current application

Total number of app launches per month by all active users within the selected dates

Total number of app launches per week by all active users within the selected dates

Compared to yesterday, the total number of keywords covered has increased/decreased.

Monitoring the ranking trends of the top 10 applications for the selected date range.

Time Period Percentage = Number of Startups in Each Time Period / Total Number of Startups

Note: Download statistics are sourced from publicly available data from various app stores. Different app stores have different update cycles and may experience a decrease in downloads. Some app store download data is also inaccurate; therefore, this statistical data is for reference only.

TapTap officially removed the "Hot Games Ranking" on March 22, 2023. (The last update of DianDian Data was on March 21 at 22:45.)

Total number of app launches per day by all active users within the selected date period

The total number of times the app was launched within the selected dates. For example: daily launches / weekly launches / monthly launches.

Compared to yesterday's top 10 keywords, there has been an increase/decrease.

Compared to yesterday's top 3 ranked keywords, there has been an increase/decrease.

Total usage time of all active users within the selected date range. For example: daily usage time / weekly usage time / monthly usage time.

Editor's Note N's keywords are additional trending search terms for iOS 16.

Number of devices with the app installed (Note: This does not include devices where the app has been uninstalled).

Selected date range, current keyword ranking list of applications.

Within the selected date range, the percentage of active users of a certain app across different usage durations relative to the total number of active users on that day. Usage duration segments: 0-3s, 4-10s, 11-30s, 30-60s, 1-3min, 3-10min, 10-30min, >30min

Within a selected month, the distribution of active devices for a certain APP by gender, region (city level, province, area), age group, etc.

The retention rate is the percentage of new users who still launch the app N days later within the selected date range. For example, if 100 new users install an app for the first time on January 1st, and 50 of them launch the app on January 8th, then the 7-day retention rate for January 1st is 50%.

During the statistical period, the proportion of devices with users who were inactive or uninstalled that newly installed other apps out of all devices with apps installed across the entire network.

Taking into account the popularity and display share of each keyword, the value is set between 0 and 100.