Summary
We are excited to launch Store Intelligence, complementing our ASO platform. It provides estimated download and revenue data for apps across Apple and Google stores. Use the Store Summary to analyze trends and detect algorithm changes.
The Publishers module helps uncover hidden competitors. Compare individual apps to evaluate promotion effectiveness. Our estimates are validated against customer data and offered as a separate Enterprise product with API and CSV exports.
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AdjustMeasure installs across more app stores | Adjust
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.
AppsFlyerOmnichannel Analytics Explained
Omnichannel analytics unifies customer behavior and campaign performance across mobile, web, CTV, and AI search into one identity, one attribution model, and one ROAS number. The core problem: a single customer seen on three surfaces becomes three users, inflating performance and corrupting attribution, LTV, and retention. Stitching channel reports into one dashboard is not unification—each channel keeps its own attribution logic, so conversions get double-counted and upper-funnel spend looks unproductive. For ad ops leaders, the takeaway is that identity resolution (deterministic plus probabilistic, privacy-safe) must happen at the data layer before any dashboard exists. Platform choice hinges on surface coverage, identity resolution, compliance, incrementality testing, and migration support.
AdjustJapan’s finance app growth in 2026 | Adjust
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.
AppsFlyerWeb Gaming: The untapped path to lower CPI and boost ROAS
Mobile CPI and app store fees are eroding ROAS, making web gaming a viable acquisition channel. Full Unity-to-HTML5 ports now deliver 30-50% lower CAC and avoid 15-30% store revenue cuts via web payments. Measurement parity is here: AppsFlyer enables independent attribution, conversion signals, and unified reporting. Retention can improve; one strategy title jumped from 6-7 minutes mobile to 70+ minutes web. Best fit: deep RPG, strategy, puzzle, story games, not hypercasual. Action: audit catalog, pilot web ports, link accounts cross-platform, and use owned media to drive high-intent web users.
AppsFlyerCracking the 2026 Holiday Season: A Data-Backed Playbook for Marketing Leaders
Q4 2026 planning should treat peak shopping as a compressed event, not a week. Black Friday/Cyber Monday purchase lift runs 2–3x install lift, so ad ops must schedule by daypart and hour. Singles Day is not global: Brazil, UAE and Spain show real lift, while US/France barely react. CPI spikes hardest in supposedly cheap markets—Spain’s CPI rose nearly 50%. Remarketing already drives 65–92% of non-organic spend and rises during peak. Deep linking is critical: deep-linked users are ~2x more likely to purchase and spend nearly 3x more. Benchmark market CPI, shift budget to remarketing, and connect every entry point.
AppsFlyerCreative optimization: Why your best video ad fails as a static image
AppsFlyer’s 2026 creative data shows video and static image ads reward opposite creative qualities, so ad ops teams should plan, budget, and test them separately. Video spend is concentrating: gaming’s top 2% of video creatives captured 60.7% of spend, up from 53.5%, while image spend spread out. Top spenders are testing far more variations, widening the testing gap. Action/Strategy and Puzzle/Lifestyle show format-specific tone and social-proof reversals; Finance is the exception. Teams should use AI-assisted variation, analyze video winners deeply, keep broad image testing, and measure performance at attribute level.
MintegralWhy In-App, not MFA, is the Advertising Solution Made for Advertisers
MFA sites exploit programmatic buying by attracting low-intent clicks and inflating viewability/CPM metrics, so spend can look successful while delivering little brand impact. The article argues in-app advertising is a stronger advertiser-controlled environment: app downloads create intent-bearing friction; in-app video/display viewability outperforms mobile web (77.4%/72.5% vs 71.4%/63.6%, per DoubleVerify 2022); brand unsuitability is lower (4.4% vs 9.7%); and ads.txt/approved-publisher controls plus vetted apps reduce fraud. Decision-makers should treat MFA as a measurement and supply-path risk, not just a brand-safety issue, and reallocate a meaningful budget share to verified in-app inventory.
AdjustIntroducing the Device Usage dashboard | Adjust
Adjust's Device Usage dashboard in Datascape gives ad ops teams a prebuilt view of how active users are distributed across app versions, OS versions, SDK versions, and iOS ATT status, plus dimensions like device type, country, language, and date. The core insight is that release impact can lag because users update over days or weeks; segmenting DAU by version explains flat or shifting metrics. Teams can track SDK and app-version adoption, compare OS behavior, identify stale versions, and add device/country context to performance analysis. Actionable takeaway: use the dashboard before and after releases or SDK rollouts to validate adoption, isolate version-specific issues, and contextualize attribution and engagement trends.
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