The Publisher Leaderboard ranks top app publishers by Estimated Publisher Worth, which aggregates the Estimated App Worth of all apps in a publisher's portfolio. Unlike other charts ranking by single metrics like downloads or revenue, this leaderboard uses a proprietary algorithm considering user estimates, user activity, international reach, and a secret sauce. The leaderboard is accessible via the main menu's Rankings dropdown.
It displays each publisher's Estimated Worth and icons for their top five most successful apps, which can be hovered for details or clicked to visit App Profile Pages. Clicking a publisher leads to their Publisher Profile Page. This tool helps users research successful publishers in their category to learn effective strategies for improving their apps and increasing downloads.
This guide explains how to use Sensor Tower's Keyword Rankings feature for App Store Optimization. It covers adding apps, tracking keywords, interpreting ranking data, and managing keywords to improve app visibility.
App categorization, though less crucial than keywords or icons, aids discoverability. Choose relevant categories, favor less competitive ones using leaderboards. Always align with Apple's definitions to avoid rejection.
This post analyzes pricing strategies for paid iOS apps in the top 50 of each App Store category, breaking down prices into 14 tiers. Categories like Education, Business, and Medical show diverse pricing, while Finance and Social Networking are dominated by free apps. Most expensive apps are in Medical, Navigation, and Travel. The data helps developers understand effective pricing for their category.
Sensor Tower adds Android features. View Google Play Top Charts and app profiles. Beta Android ASO modules track keyword ranks. Example shows Clash of Clans data. Company works on improvements.
Japan's finance app category is outperforming, with H1 2026 installs up 8% YoY and sessions up 40%—nearly 5x the install growth and well ahead of global figures (5% and 29%). Stock trading is the standout subvertical: installs +90% YoY and average session length climbing to 11.7 minutes, driven by NISA reforms and a retail investor resurgence. Retention is improving across the full 30-day curve (D1 17% to 19%, D30 7% to 8%). For ad ops teams, the takeaway is clear: prioritize measurement depth, re-engagement, and channel-level quality over top-of-funnel volume alone.
Adjust has expanded store detection and verification across multiple app storefronts, making Store Type the primary dimension for identifying where an install originated rather than relying on platform or OS alone. For ad ops teams, this means campaign performance can now be analyzed at the store level across Huawei AppGallery, Xiaomi GetApps, Samsung Galaxy Store, Vivo Appstore, and Google Play variants, with independent verification of install origin. Newly detected stores are flagged in AppView with a direct route to configuration, and store-level data flows automatically into reporting, raw data, callbacks, and CSV exports, plus Conversion Rules via Store Rule conditions.
The Review Analysis module mines app reviews for keywords, highlighting trends and sentiment. It helps find new, relevant keywords easily, such as 'elixir', with low competition and high traffic. Testing is crucial to optimize keyword lists for better visibility and downloads.
iOS push notifications boost user retention. Implement via services like AppsFire, PushWoosh, or Urban Airship. Start with one notification, gauge response, then add more. Tailor to app type: games can notify events; utility apps can welcome and remind.
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