Send us Message

Marketing

Awesome Image Awesome Image
10.03.2026

OEM as a First-Session Accelerator: Why On-Device Traffic Changes Time-to-Value

Mobile user acquisition is evolving fast. As performance marketers seek ways to improve return on ad spend, OEM traffic has emerged as a powerful first-session accelerator. Unlike traditional install channels, mobile inventory from device manufacturers such as Xiaomi, Samsung, Huawei and others reaches users before they even enter an app store or browsing session. This early exposure changes how we think about key metrics like time-to-value and highlights why focusing on first meaningful actions in the session is becoming critical for growth in 2026. Why OEM Traffic Reshapes the Time-to-Value Metric Historically, mobile marketers have used cost per install (CPI) as the primary measure of acquisition efficiency. That made sense in an era when installs were hard won and the focus was simply on getting users to download an app. But OEM traffic works differently. OEM inventory reaches users at native, on-device discovery points such as setup flows, preloads, smart folders and other system-level placements, long before they might see an ad on social or search. Because these placements appear inside the phone’s own interface, they often connect with users early in their device journey. This early exposure means users are more likely to open the app right after install, which in turn affects how quickly they reach the first meaningful action. In this context, time-to-value becomes a more important metric than CPI alone. Instead of simply measuring how much it costs to get an install, UA teams now focus on how long it takes new users to complete that first valuable event — whether it is first app open, tutorial completion, signup, trial start or verification (KYC) process. These actions reflect true user engagement and are better indicators of future spending, retention, and lifetime value. Not Just Installs: The Shift to Meaningful Actions When OEM traffic accelerates time-to-value, what it really means is that users who come through on-device placements often trigger key events sooner than users acquired through feed-based or search ads. For example, a ride-hailing app that optimizes toward first ride bookings sees strong evidence of this shift in UX-driven metrics. In a case study with a mobility app, the UA team pivoted away from optimizing installs and instead focused on CPA — cost per first ride event. After activating OEM native placements inside device search bars, smart folders and browser suggestions, they saw a 2.5x increase in first-ride completions and a much faster conversion pipeline from install to revenue generation.  This illustrates a broader trend: OEM traffic tends to deliver users who engage with the app faster, because they encounter the app in an integrated environment rather than as a distant link in a social or feed ad. Reaching users earlier in their device journey reduces friction between install and value, which shrinks time-to-value and improves downstream metrics like Day-0 and Day-1 events. How OEM Traffic Impacts D0/D1 Events, Trial Start and KYC Completion Metrics like first open, onboarding events, trial start and KYC completion are essential for many app verticals — especially fintech, subscription services and consumer platforms. OEM traffic can influence these early session events in several ways: Early Exposure Increases Engagement Likelihood When users discover an app through system-native placements — such as recommendations during setup or app folders — they often open the app sooner. That reduces delays between install and first open, which helps trigger Day-0 events sooner and improves Day-1 activity. This faster progression has a direct effect on long-term retention, because users who complete critical first steps early in their journey are more likely to stick around. Native Discovery Reduces Onboarding Friction OEM placements don’t interrupt users with external redirects. Instead, they place your app in a context that feels trusted and seamless. That native context has been shown to improve first session engagement and reduce drop-off during initial onboarding, which is essential for completing trial starts or identity verification (KYC) sequences that are common in finance and subscription apps. Shift to Event-Based Optimization Improves Value Signals Unlike campaigns that optimize purely for CPI, OEM advertising programs increasingly let marketers optimize toward events that matter — such as first purchase, tutorial completion or signup verification. As one industry analysis notes, this shift from optimizing for installs to optimizing for meaningful behavior helps growth teams track real user value rather than just traffic.  Why First-Session Metrics Are Becoming the New Focus in 2026 As user acquisition costs continue to rise and competition intensifies across social and in-app networks, UA teams need deeper visibility into how new users behave after installation. In 2026, leading mobile marketers are shifting away from install-centric KPIs to engagement and value-centric KPIs such as: OEM traffic uniquely accelerates these metrics because it catches users at moments of high intent — such as when they first set up their device or explore native recommendations. In an on-device environment, these early touchpoints are more contextual and less interruptive than typical feed ads, which can lead to higher quality users and faster paths to value. That shift makes time-to-value an indispensable metric for modern UA strategy. Conclusion: OEM as a First-Session Accelerator In 2026, thinking about OEM traffic only as a low-CPI channel leaves value on the table. Instead, marketers are coming to see OEM as a first-session accelerator — a source that not only drives volume but also speeds up critical user engagement moments. By focusing on meaningful events rather than just installs, growth teams can better measure true performance, optimize campaigns toward actions that drive revenue, and deliver sustainable growth. As mobile acquisition evolves, time-to-value will be one of the most important metrics for evaluating campaign success, and OEM traffic is positioned to accelerate that metric more reliably than many traditional channels.

Read More
03.03.2026

OEM Traffic and Android App Monetization: Why Revenue Patterns Differ from Google Play Installs

When mobile user acquisition teams evaluate performance, one common question keeps coming up: why does app revenue often look so different when installs come from OEM traffic compared with installs from Google Play? On the surface, it’s easy to focus strictly on install volume, but when you peel back the layers of Android monetization and user economics, the answer comes down to how users behave, how revenue is generated, and how different channels influence downstream value. From Install Metrics to Monetization Models Most developers and UA managers are familiar with install counts driven by Google Play campaigns or organic store traffic. On Google Play, installs are often closely tied to in-app purchases (IAPs) and subscription conversions, especially in games and premium services. According to industry analysis, in-app purchases make up a large share of Play Store revenue, with IAP alone accounting for a significant percentage of total mobile app income. On Google Play specifically, in-app purchase revenue has historically outpaced many other sources, with install numbers translating more predictably into revenue because of direct spending behavior within the app itself. However, OEM traffic — installs coming from pre-installed recommendation surfaces, device ecosystems, alternative app stores, and system-level placements on Android devices — operate under a different dynamic. OEM sources are natively integrated at the device level and often appear during setup or in system utilities, which gives them huge reach and strong conversion into installs, but this doesn’t always translate into equivalent revenue performance. For UA teams, this can be surprising when a high-volume OEM campaign produces robust install figures yet the monetization metrics lag behind what they see from Google Play installs. Why Revenue Patterns Diverge There are several reasons why monetization trends can diverge when comparing OEM traffic installs and Google Play installs: 1. User Intent and Purchase Behavior Differences Users who install an app through traditional Play Store discovery or search are often already considering the app in a value context — they’ve actively found your app and may be more likely to engage with paid elements like subscriptions or in-app purchases. In contrast, OEM traffic users often encounter the app through recommendations or discovery at system level, which increases install volume but doesn’t always indicate ready-to-pay audiences, especially for monetization models reliant on IAP or subscriptions. This difference in user intent impacts long-term value and revenue per install. 2. Heavy Reliance on Advertising Models in Android Another key factor is that Android monetization patterns favor advertising revenue more than paid app downloads or high-value IAP models, particularly in global markets where Android’s user base is concentrated in emerging regions. Android apps often generate money through banners, interstitials, and rewarded video ads rather than premium spending. Google Play statistics show that ad-based monetization continues to account for a large share of revenue, and hybrid models combining ads and purchases are common. But the effective revenue per ad view (eCPM) still depends heavily on user geography and engagement quality, not just install count. Because OEM traffic can deliver installs at scale that originate from high-volume OEM ecosystems — like preloads on devices or embedded app recommendations — the revenue from ad monetization or IAP doesn’t always scale proportionally with install volume. UA teams might see 10x the installs with only modest increases in revenue, especially if the users are less likely to engage deeply or spend money. Real-world discussions among developers highlight this issue: significant install spikes don’t always produce matching revenue growth unless engagement and monetization strategies are aligned with user behavior. 3. Geographic and Demographic Effects OEM installs often come from diverse regional markets where spending power, ad bid rates, and in-app purchase behavior differ significantly from Tier-1 Play Store traffic. Android’s broad global reach means installs from OEM channels can skew toward regions with lower average revenue per user (ARPU), which in turn depresses overall monetization metrics compared to installs from Google Play in premium markets. This geographic difference is a core part of why revenue per install varies widely across channels. Adapting Monetization Strategy for OEM Traffic For UA teams facing these discrepancies, the important shift is to treat OEM traffic not just as another install source but as a distinct monetization environment. It helps to: When UA teams recalibrate how they interpret revenue patterns across channels, they often find that OEM traffic can provide long-term value and complement Google Play installs, even if the revenue per install looks different at first glance.

Read More
27.02.2026

Android Growth Without Google Play Dominance: A UA Playbook for OEM-First Markets

Most Android growth strategies are built around one silent assumption: Google Play is the main discovery layer. Campaign structures, store optimization, and even attribution logic are often designed with a Play-first mindset. That model works well in many regions, but it breaks in others. In OEM-first markets, Google Play is not the primary place where users discover apps. Sometimes it is not the main store at all. For UA teams operating in these environments, sustainable growth requires a different approach. When Google Play Is No Longer the Center of Gravity In OEM-first markets, user behavior does not follow the classic Android playbook. Discovery happens through: Google Play is still present, but it does not dominate attention. Users may install apps without actively browsing Play or may treat it as a secondary confirmation step rather than a starting point. UA teams that assume Google Play is always the entry point quickly run into friction. Performance looks inconsistent, cohorts behave unexpectedly, and optimization becomes harder to explain. Why Play-First Assumptions Start to Fail Play-first strategies are built on search and comparison. OEM-first ecosystems are built on guidance and context. Users are shown apps before they actively look for them. When UA teams optimize messaging, creatives, and store pages for search-driven behavior, they miss the moment where choice actually happens. This mismatch leads to: The issue is not execution quality. It is a strategy designed for the wrong discovery layer. Alternative Stores Are Not Mirrors One of the most common mistakes in OEM-first markets is treating alternative app stores as copies of Google Play. In reality: When OEM stores are optimized as afterthoughts, organic and system-driven traffic underperforms. When they are treated as primary surfaces, performance stabilizes. Store parity feels efficient. Contextual optimization works better. What Breaks First in Measurement and Budgeting Play-first measurement assumes one dominant endpoint. OEM-first markets fragment that assumption. Installs are distributed across: Without store-level segmentation, performance data becomes noisy. Strong OEM sources look weaker than they are, while familiar channels receive more budget simply because they are easier to interpret. Over time, this leads to distorted budget allocation and missed growth opportunities.  Redefining the Primary Discovery Layer The most important shift for UA teams is conceptual. Instead of asking where installs land, teams need to ask where discovery starts: Once that consideration changes, strategy becomes clearer. Google Play stops being the default anchor and becomes one of several meaningful endpoints. Designing Store Strategy Instead of Store Parity OEM-first growth requires intentional differentiation. That means: This adds operational overhead, but it also unlocks relevance. Apps that feel native to OEM environments convert better and scale more predictably. Where Paid and Organic Growth Start Reinforcing Each Other In OEM-first markets, paid and organic growth are closely connected. Paid OEM traffic helps: Once those signals are established, organic placements often follow. UA teams that separate paid and organic thinking miss this feedback loop. Teams that align them benefit from compounding effects. Budgeting for Ecosystems, Not for Familiarity Effective budget allocation in OEM-first markets requires a mindset shift. Instead of defaulting to global benchmarks, teams need to: This reframes UA planning from channel-centric to ecosystem-centric. Operating Without a Single Control Point OEM-first markets feel fragmented by design. There are fewer universal rules, more operational complexity, and less predictability compared to Play-dominated regions. At the same time, there is less saturation, more distribution leverage, and more room for differentiated growth. UA teams that accept this reality build resilience. Teams that fight it spend resources trying to recreate a Play-first environment that does not exist locally. What OEM-First Markets Teach About Android Growth Android growth is not uniform. In markets where Google Play does not dominate discovery, success depends on understanding device ecosystems rather than forcing global assumptions. UA teams that adapt early stop chasing familiar patterns and start building strategies that reflect how users actually discover apps. In 2026, strong Android growth strategies will not be defined by loyalty to a single store. They will be defined by the ability to grow across ecosystems, even when Google Play is no longer in charge. That is the real advantage of thinking OEM-first.

Read More
20.02.2026

When Android App Stores Replace Ads: Organic Growth Inside OEM Ecosystems

For most UA teams, growth still starts with paid traffic. Budgets go up, installs follow. Organic growth is treated as something that happens later, usually inside Google Play. OEM ecosystems challenge that assumption. Inside OEM app stores, growth can happen without ads at all. Featuring, system recommendations, and curated collections increasingly act as acquisition channels on their own. For UA teams, the question is no longer whether OEM stores can drive organic installs, but whether they know how to influence that process. The Setup: Why Organic Growth Is No Longer Just About Google Play Google Play has trained the market to think of organic growth as a function of ASO. Rankings, reviews, keyword optimization. OEM app stores work differently. In OEM ecosystems, discovery is often guided, not searched. Users do not always look for apps. Apps are shown to them. This shifts organic growth from being keyword-driven to being system-driven. The store becomes an extension of the device, not a neutral marketplace. As a result, organic installs inside OEM stores behave less like classic “organic” and more like earned distribution. UA teams that only optimize for Google Play miss this layer entirely. The Climax: How OEM Stores Generate Installs Without Ads Featuring Is the New Reach OEM stores rely heavily on editorial and algorithmic featuring.Top charts matter less than: When an app appears in these surfaces, it benefits from immediate visibility without competing in an auction. For the user, this does not feel like advertising. It feels like guidance. This is where OEM stores start replacing ads. The distribution happens before any paid impression is needed. Recommendations Are Triggered by Context, Not Keywords Unlike search-based discovery, OEM recommendations often react to context: That makes them powerful and unpredictable at the same time. For UA teams, this means organic growth is no longer passive. It is influenced by how well the app fits into the ecosystem. Apps that clearly communicate their category, use case, and value are easier for the system to place and recommend. Vague positioning makes featuring harder. Clear utility makes it easier. System Collections Shape Demand OEM stores actively shape demand through system collections.“Essential apps,” “Recommended after setup,” “Apps you might need next.” These placements do not respond to bidding or CPI. They respond to relevance. Once an app enters these collections, organic installs often arrive in waves. Growth feels sudden, even though no campaign was launched. From the outside, it looks like luck. In reality, it is alignment. The Resolution: How UA Teams Can Influence Organic OEM Growth Organic growth inside OEM ecosystems is not random. It is influenced by decisions UA teams already make. What actually moves the needle: UA teams often think of OEM stores as something that “just exists.” In practice, they respond to signals, just like any other distribution system. Why Paid OEM Traffic Often Unlocks Organic OEM Growth There is a quiet connection between paid and organic inside OEM ecosystems. Paid OEM traffic can: Once those signals are strong enough, organic placements often follow. In that sense, paid OEM traffic acts less like direct acquisition and more like activation fuel for organic growth. This feedback loop is specific to OEM ecosystems and does not work the same way in Google Play. The New Role of UA in OEM Ecosystems In OEM environments, UA teams are no longer just traffic buyers.They are distribution strategists. Their job expands to: Ignoring this role means leaving growth on the table. When Distribution Becomes the Advantage OEM app stores are not replacing ads everywhere. But in certain moments, they reduce the need for them. When an app earns visibility inside OEM ecosystems, installs arrive without bids, without auctions, and without constant optimization. That is a different kind of growth. It is quieter, but often more sustainable. The Real Opportunity Organic growth inside OEM ecosystems is not about “getting lucky” with featuring. It is about making the app easy for the system to recommend. In 2026, the strongest Android growth strategies will not rely solely on paid traffic or classic ASO. They will treat OEM app stores as active distribution channels where organic growth can be influenced, accelerated, and protected. When that happens, ads stop being the only engine of scale. Sometimes, the store itself does the work.

Read More
10.02.2026

Android App Store Diversification: How UA Teams Should Split Traffic Between Google Play and OEM Stores

For years, Android user acquisition followed a simple rule: all roads lead to Google Play. No matter where traffic came from, installs were optimized around one store, one benchmark set, and one mental model. That rule is starting to break. As OEM ecosystems mature, UA teams are facing a new question that didn’t exist before: when does it make sense to deliberately move part of your traffic away from Google Play and into OEM app stores? For many apps, this is no longer a theoretical discussion. It’s a performance decision. How Google Play Became the Default Answer Google Play earned its role as the center of Android growth. It offers scale, predictable attribution, established ASO mechanics, and familiar monetization patterns. For a long time, OEM app stores existed on the periphery. They were treated as technical endpoints or regional requirements, not as places where acquisition strategy was shaped. That led to a привычный подход: This logic worked when discovery happened mostly in one place. It starts to crack when discovery spreads across device-level ecosystems. The Moment Diversification Stops Being Optional Most teams don’t diversify because they want to. They do it because reality pushes them there. Cost pressure is usually the first signal. As competition intensifies, Google Play–centric flows become more expensive, while incremental gains shrink. OEM stores often introduce additional supply where pricing behaves differently. The second signal comes from OEM-native formats. On-device placements naturally lead users into OEM stores. Forcing those users through Google Play can add friction instead of removing it. The third signal is geography. In some regions, OEM ecosystems are not alternatives. They are the default. Ignoring them means ignoring how users actually discover apps. Diversification becomes rational when Google Play stops being the only place where intent is formed. Splitting Budgets Without Turning It Into a Gamble The biggest mistake teams make is framing this as a choice between stores. It’s not. Strong UA teams don’t ask where traffic should go. They ask where it performs better in context. In practice, the split often looks like this: Over time, this creates balance. Google Play provides stability. OEM stores provide incremental reach and pricing flexibility. Where Diversification Usually Breaks App store diversification has real costs, and teams underestimate them at their own risk. Operational overhead is the most obvious one. Separate builds, compliance rules, store updates, and release timing all add friction. Without clear ownership, diversification stalls fast. Another issue is expectations. OEM stores don’t behave like Google Play. Rankings, reviews, and discovery mechanics follow different rules. Judging OEM store performance through Play-centric benchmarks leads to false negatives. Measurement is the quiet failure point. If store-level performance is not segmented properly, diversification gets lost inside “Android totals” and becomes impossible to evaluate honestly. The Benefits Teams Don’t Plan For Once diversification is implemented properly, unexpected advantages tend to surface. One is resilience. When performance on Google Play fluctuates due to competition or algorithm shifts, OEM stores provide an alternative path to volume. Another is better alignment with OEM traffic economics. When discovery and installation happen inside the same ecosystem, conversion rates often improve. There’s also a structural benefit. Diversification forces better discipline. Teams start analyzing performance by store, by entry point, and by user intent. That clarity usually improves decision-making across all Android UA, not just OEM campaigns. What a Mature Diversification Strategy Looks Like By 2026, app store diversification should feel intentional, not experimental. In practice, that means: Teams that work this way don’t move away from Google Play. They simply stop depending on it as a single point of failure. The Real Takeaway Android growth no longer happens in one place. Discovery is spreading across devices, ecosystems, and stores, and UA strategies need to reflect that reality. Google Play remains critical, but it is no longer the only environment shaping user intent. The strongest Android strategies in 2026 won’t choose between Google Play and OEM stores. They will understand exactly when each store works best and design acquisition flows accordingly. That’s what app store diversification actually unlocks: control, not complexity.

Read More
04.02.2026

The New UA Mix: How Brands Combine Social, OEM, and Programmatic Channels for Sustainable Growth

User acquisition is no longer driven by a single dominant channel. According to analyses from Business of Apps, Singular, Zoomd, AppSamurai, and OEM-focused partners such as AVOW, today’s highest-performing UA strategies combine social platforms, OEM advertising channels, and programmatic inventory within a unified growth framework. This diversified mix helps brands counter rising acquisition costs, protect performance against privacy constraints, and reach user segments that traditional networks no longer efficiently deliver. Why the UA Mix Is Changing Industry reports highlight the same set of forces reshaping how marketers acquire users: Across these sources, the conclusion is clear: relying only on social or programmatic channels no longer produces stable, scalable growth. Social Channels: Still the Foundation Meta, TikTok, Snap, and YouTube remain essential UA pillars. Business of Apps identifies social channels as the baseline layer of user acquisition – crucial for: But social platforms alone cannot sustain growth in an environment of rising CPIs and shrinking signal visibility. As AppSamurai notes, advertisers increasingly pair social with complementary channels. OEM Channels: The Underused but Essential Growth Engine OEM advertising: preloads, on-device placements, OEM app stores, system-UI inventory, has moved from niche to mainstream. According to Business of Apps, OEM partners (Huawei, Xiaomi, Samsung, OPPO, vivo, Transsion and others) provide access to more than 1.5 billion monthly active users. AVOW highlights OEM channels as one of the most effective ways to reach users beyond the touchpoints of standard networks. Industry documentation points to several unique advantages of OEM ads: Case studies from AVOW show that OEM campaigns consistently outperform traditional preload channels and complement established UA sources by unlocking cost-efficient installs and new user segments. AppsFlyer also frames OEM preloads as a way to “move beyond programmatic, search, and social,” providing new growth corridors for brands whose traditional channels have plateaued. Programmatic: The Scalable Middle Layer Programmatic channels: DSPs, exchanges, and in-app programmatic inventory, complete the modern UA mix. Zoomd and AppSamurai describe programmatic as the “connective tissue” of a diversified UA strategy, enabling: Digital Turbine explicitly pairs OEM traffic with programmatic campaigns to reach users from first boot (on-device) and then maintain engagement through targeted in-app ads. Programmatic therefore supports long-term UA expansion, adding flexibility across formats, audiences, and placements. The New UA Mix: A Three-Pillar Strategy Synthesizing insights across all referenced sources, the 2025 UA mix looks like this: 1. Social: Creative learning + scale + high-volume intent capture. 2. OEM: Incremental reach + device-native placements + market expansion into regions dominated by OEM ecosystems. 3. Programmatic: Ongoing scale + retargeting + cost balancing across channels. Singular emphasizes that diversified channels are now essential for performance stability; Business of Apps stresses the need for a multi-channel acquisition framework; and Zoomd positions OEM, social, and programmatic as the core combination for post-privacy growth. Conclusion The new UA mix is no longer an optional strategy, it is the industry standard. By combining social platforms, OEM advertising, and programmatic supply, brands can: As acquisition costs rise and global markets evolve, marketers that adopt a balanced, multi-channel UA portfolio are best positioned to compete and scale efficiently. The New UA Mix: How Brands Combine Social, OEM, and Programmatic Channels for Sustainable Growth User acquisition is no longer driven by a single dominant channel. According to analyses from Business of Apps, Singular, Zoomd, AppSamurai, and OEM-focused partners such as AVOW, today’s highest-performing UA strategies combine social platforms, OEM advertising channels, and programmatic inventory within a unified growth framework. This diversified mix helps brands counter rising acquisition costs, protect performance against privacy constraints, and reach user segments that traditional networks no longer efficiently deliver. Why the UA Mix Is Changing Industry reports highlight the same set of forces reshaping how marketers acquire users: Across these sources, the conclusion is clear: relying only on social or programmatic channels no longer produces stable, scalable growth. Social Channels: Still the Foundation Meta, TikTok, Snap, and YouTube remain essential UA pillars. Business of Apps identifies social channels as the baseline layer of user acquisition – crucial for: But social platforms alone cannot sustain growth in an environment of rising CPIs and shrinking signal visibility. As AppSamurai notes, advertisers increasingly pair social with complementary channels. OEM Channels: The Underused but Essential Growth Engine OEM advertising: preloads, on-device placements, OEM app stores, system-UI inventory, has moved from niche to mainstream. According to Business of Apps, OEM partners (Huawei, Xiaomi, Samsung, OPPO, vivo, Transsion and others) provide access to more than 1.5 billion monthly active users. AVOW highlights OEM channels as one of the most effective ways to reach users beyond the touchpoints of standard networks. Industry documentation points to several unique advantages of OEM ads: Case studies from AVOW show that OEM campaigns consistently outperform traditional preload channels and complement established UA sources by unlocking cost-efficient installs and new user segments. AppsFlyer also frames OEM preloads as a way to “move beyond programmatic, search, and social,” providing new growth corridors for brands whose traditional channels have plateaued. Programmatic: The Scalable Middle Layer Programmatic channels: DSPs, exchanges, and in-app programmatic inventory, complete the modern UA mix. Zoomd and AppSamurai describe programmatic as the “connective tissue” of a diversified UA strategy, enabling: Digital Turbine explicitly pairs OEM traffic with programmatic campaigns to reach users from first boot (on-device) and then maintain engagement through targeted in-app ads. Programmatic therefore supports long-term UA expansion, adding flexibility across formats, audiences, and placements. The New UA Mix: A Three-Pillar Strategy Synthesizing insights across all referenced sources, the 2025 UA mix looks like this: 1. Social: Creative learning + scale + high-volume intent capture. 2. OEM: Incremental reach + device-native placements + market expansion into regions dominated by OEM ecosystems. 3. Programmatic: Ongoing scale + retargeting + cost balancing across channels. Singular emphasizes that diversified channels are now essential for performance stability; Business of Apps stresses the need for a multi-channel acquisition framework; and Zoomd positions OEM, social, and programmatic as the core combination for post-privacy growth. Conclusion The new UA mix is no longer an optional strategy, it is

Read More
28.01.2026

From Notifications to Discovery: How Lock Screens Are Becoming a New App Acquisition Channel

For a long time, the lock screen was treated as dead space. A place for notifications, time, battery level — nothing more. In UA planning, it rarely appeared as a serious discovery surface. That assumption is no longer true. OEM ecosystems are actively transforming lock screens into high-visibility discovery environments, where apps are not just seen, but installed. For advertisers, this shift changes how discovery works — and what actually drives performance. The Setup: Why Lock Screens Were Ignored for So Long From a UA perspective, lock screens used to feel off-limits. They were passive. They weren’t scrollable. They didn’t behave like feeds, stores, or placements with intent signals. Most performance teams focused on environments where users were already “in motion”: social feeds, games, search results, app stores. The lock screen sat outside that logic — something the user passed through, not something they engaged with. But OEMs see the lock screen differently. It is the most frequently viewed screen on the device. Users unlock their phones dozens — sometimes hundreds — of times per day. That makes the lock screen not just visible, but habitual. Once OEMs started treating it as owned inventory rather than system UI, its role began to change. The Climax: How Lock Screens Became a Discovery Surface From Passive UI to Active Recommendation Layer Modern OEM lock screens are no longer just static backgrounds with notifications. In several ecosystems, they now include full-screen content modules, recommendations, and interactive units. A clear example is Glance, which operates as an OEM-partnered lock screen experience. In performance campaigns, Glance enables One-Click Install (OCI) flows — allowing users to initiate an app install directly from the lock screen, without first opening an app or browsing a store. At that point, the lock screen stops being a notification layer and becomes an entry point into the acquisition funnel. Why Lock Screen Discovery Behaves Differently Lock screen discovery does not compete with feeds or search. It competes with attention in idle moments. Users encounter lock screen content: That context explains why traditional ad logic often fails here. There is no scrolling behavior.There is no exploration mindset.There is no tolerance for complexity. The decision is binary and fast: ignore or act. This is why lock screen discovery rewards: Anything that looks like a conventional “ad” — multiple messages, small text, layered CTAs — tends to lose immediately. Install Initiation Changes the Funnel One of the most important shifts is where the install happens. In classic UA, install intent builds across multiple steps: impression → click → store → install. On lock screens with OCI-style flows, that process is compressed. The user sees a value proposition and can trigger an install without entering a store-first mindset. This has two implications for UA teams: As a result, lock screen campaigns often show: The lock screen doesn’t forgive weak first-session experiences. Why Creative Discipline Matters More Than Ever Lock screen inventory is unforgiving. You don’t get a second frame.You don’t get a swipe.You don’t get a scroll. That’s why the most successful lock screen campaigns follow a very strict creative discipline: From a media buying perspective, this is closer to outdoor advertising logic than digital feed advertising. Clarity beats cleverness. Recognition beats explanation. The Resolution: How UA Teams Should Treat Lock Screens in 2026 Lock screens should no longer be treated as an experimental side format. They are becoming a distinct discovery layer with its own rules. For advertisers and UA managers, the practical approach looks like this: Lock screen discovery is not about persuasion. It’s about interruption done right. Conclusion The lock screen is no longer just a place where apps wait to be opened. In modern OEM ecosystems, it’s where apps are found. As OEMs continue to productize device-level surfaces, lock screens are emerging as one of the most powerful — and misunderstood — acquisition environments. For teams willing to adapt their creative logic, measurement expectations, and onboarding strategy, lock screens offer access to user attention that few other channels can match. In the next phase of mobile growth, discovery won’t start in feeds or stores. It will start before the phone is even unlocked.

Read More
22.01.2026

OEMAD — New Features & Improvements

1) Smarter event-based optimization (avg. event cost ↓ 15%) We upgraded our event-optimization engine to learn faster from post-install signals and allocate spend more efficiently across placements. Result: clients are seeing ~15% lower average cost per event, while keeping volume stable. What improved behind the scenes: 2) New organization-based account structure (unlimited ad accounts & campaigns) We redesigned the way accounts are structured: Why it matters: it’s now much easier to separate budgets by app, geo, team, or business line—and manage everything cleanly in one place. 3) New OEM inventory added (lower user acquisition costs) We added new OEM inventory sources, expanding reach and improving pricing efficiency. More supply + better matching typically = better CPM/CPI dynamics, especially at scale. Expected impact: more stable volumes and an additional lever for lower cost per new user. 4) Self-serve cabinet is nearly ready (public access in a couple of months) The self-serve dashboard is in the final stage. Very soon, all clients will be able to: We’re polishing UX, permissions, and guardrails to make sure it’s safe and simple from day one. 5) Faster, tighter MMP integration (better optimization quality) We improved the way OEMAD connects to MMPs so that event data arrives and processes faster. What you’ll notice: Extra OEMAD updates (to show active development) To make it obvious that the product is moving quickly, you can also mention these recent “platform maturity” upgrades (choose what matches what you actually shipped): What to expect next

Read More
20.01.2026

Retention and LTV in OEM Traffic: What Really Happens After the Install

OEM traffic is often described in simple terms: clean installs, low fraud, strong early metrics. And in many cases, that’s true. But if you’ve actually scaled OEM campaigns, you know that installs are only the beginning. The real questions start later: Who stays? Who churns? And which OEM users are worth scaling for long-term value? This is where most misconceptions around OEM retention and LTV appear. The Setup: Why OEM Retention Is Easy to Misread Most teams look at OEM traffic the same way they look at paid social or in-app networks. CPI goes down, D1 looks strong — everything seems fine. Then someone opens a D7 or D30 report and the doubts begin. At that point, OEM traffic often gets labeled as “short-term” or “good for volume, not for quality”. In practice, the issue is not OEM traffic itself.The issue is how early OEM users are introduced to the product. On-device placements — setup flows, preloads, system recommendations — surface apps before users have fully formed their daily habits. That gives OEM traffic a unique advantage in scale, but it also changes post-install behavior. Expecting these users to behave exactly like social or search cohorts is where the mismatch starts. The Climax: What Retention and LTV Actually Look Like in OEM Why D1 Is Often Strong — and Why That’s Not the Full Story Strong Day-1 retention is one of the most common OEM patterns. Users install, open the app, maybe complete onboarding. From the outside, it looks great. But the install decision in OEM often happens with less deliberate intent. The user didn’t search, didn’t compare screenshots, didn’t read reviews. They accepted a recommendation at a moment of convenience. What we often see in data: This doesn’t mean OEM traffic is “low quality”. It means intent is distributed unevenly — and averages hide that. Formats Matter More Than Most Teams Expect Not all OEM formats create the same type of user. From real campaign data, the pattern is consistent: Calling all of this simply “OEM traffic” misses the point.Retention lives at the format level, not the channel level. Why OEM-Level Segmentation Is Non-Negotiable Another mistake we see often: evaluating OEM performance as one blended source. Different OEM ecosystems attract different users, device tiers, and usage patterns. The same app can show completely different LTV curves depending on where the install comes from. Some ecosystems skew toward: When OEM data is blended, good cohorts subsidize weak ones, and decisions get distorted. Teams that segment by OEM × format × entry point see much clearer signals — and scale with far more confidence. Cheap Install vs. Valuable User Low CPI is one of OEM’s strongest selling points — and one of its biggest traps. A cheap install usually means: A valuable OEM user shows up later: The difference only becomes visible in cohort analysis. If you’re not looking past install and D1, OEM will always feel confusing. The Resolution: How We See OEM Retention Done Right From the perspective of a traffic source, OEM works best when it’s treated as a long-game channel, not a CPI arbitrage tool. What consistently works for advertisers who scale OEM successfully: OEM traffic introduces users early. That’s its strength — and its responsibility. Products that can anchor themselves into daily behavior benefit disproportionately. Products that rely on delayed or unclear value struggle. Conclusion OEM traffic doesn’t have a retention problem.It has a timing problem — and timing cuts both ways. When OEM is treated as just another install source, it disappoints. When it’s treated as a system-level discovery channel with its own logic, it delivers users that other channels simply can’t reach at the same scale. The teams that win with OEM in 2026 won’t be the ones chasing the lowest CPI.They’ll be the ones who understand which OEM users stay — and why.

Read More
16.01.2026

How OEM Ads Are Changing the App Discovery Journey

For years, app discovery followed a familiar script: users saw an ad in an app, tapped, landed in an app store, and made a decision on the store page. OEM advertising is changing that script by moving discovery upstream into the device itself. Setup flows, lock screens, OEM stores, and on-device recommendation surfaces are becoming discovery engines, while “frictionless install” mechanics compress the time between awareness and install. The result: a new app discovery journey that can outperform traditional paths: if UA teams adapt their creative, measurement, and post-install experience. The Setup: Discovery Is No Longer “In-App → App Store” OEM campaigns aren’t just another placement. They represent a structural shift in where discovery happens. Measurement leaders now explicitly define “preload campaigns” as partnerships with OEMs, mobile carriers, and app discovery platforms that preload apps at the factory or trigger downloads at first device activation, before the user has settled into their usual app habits. That timing matters. If you reach users during device setup, you’re influencing decisions when the user is still building their “default app set”— which changes both conversion dynamics and downstream engagement patterns. What the New OEM Discovery Journey Looks Like 1) Setup-Time Discovery Becomes a First-Class Moment Dynamic preloads and onboarding prompts are effective precisely because users are highly engaged during setup, and recommendations can be aligned to preferences and context. Industry guides describe dynamic preloads as more flexible than static factory preloads and emphasize that setup is a uniquely high-attention window. What this means for UA: You’re not only competing with other ads, you’re competing with the user’s desire to “finish setup fast.” Your message must be instantly clear, and your value proposition must be obvious in seconds. 2) “Frictionless Installs” Shrink the Discovery Funnel A major OEM-driven change is reducing store friction. Some flows let users trigger an install without a traditional app store redirect. What this means for UA: When install friction drops, “cheap installs” become easier to generate but intent can be thinner. Your first-session experience (onboarding + deep links) becomes the real make-or-break step. 3) Lock Screen Moves From Passive Surface to Discovery Channel OEM ecosystems are turning lock screens into high-visibility discovery inventory. Glance’s OCI flow is a concrete example of how a lock screen can function as an install initiation surface rather than merely a notification layer. What this means for UA: Lock screen discovery favors bold simplicity: one idea, one visual, one CTA. “Ad-like” clutter tends to lose. 4) Alternative OEM App Stores Are Becoming Discovery Engines OEM advertising isn’t only about setup and lock screens. OEMs also operate their own app stores (e.g., Galaxy Store, GetApps, AppGallery). Industry guides highlight alternative app stores as less crowded environments where users are actively browsing for apps and where advertisers may see different cost and conversion dynamics compared to the main stores. What this means for UA: You need a store strategy beyond Google Play: creative sets optimized for OEM store layouts and merchandising logic, plus the operational readiness to publish/maintain builds where required. (Glance’s OCI notes, for example, that some OEM devices require apps to be hosted on specific OEM stores like GetApps for certain flows.) 5) Measurement Has Matured: OEM Is Now a Real Performance Discipline One reason OEM has become more performance-friendly is that attribution infrastructure has improved dramatically. What this means for UA: OEM can be measured cleanly but only if your SDK setup, partner configuration, and attribution rules are correct (lookback windows, priority, raw-data interpretation). 6) Deep Linking Becomes Mandatory When the Install Gets Easier If the install happens in fewer steps, you have less time to educate the user before first opening. That shifts the burden to post-install routing. What this means for UA: In OEM, deep linking isn’t a “nice-to-have.” It’s how you keep promise integrity when the user installs without spending time on a store page. How UA Teams Should Adapt in 2026? OEM ads are changing app discovery in one fundamental way: Discovery is becoming device-native; embedded in the OS journey, not just in apps and stores. To win in this new journey, advertisers and UA managers should operationalize OEM as its own discipline: Closing The classic app discovery journey “ad → store page → install” is no longer the only default. OEM ads are building new discovery paths inside the device experience: setup-time recommendations, lock screen install initiation, alternative store merchandising, and frictionless installs supported by deterministic attribution. For performance teams, this is both an opportunity and a responsibility: the upside is real, but success requires OEM-native creative, correct measurement, and post-install journeys that deliver on the promise fast.

Read More

Contact

hi@oemad.ai

About Us

Blog
Faq

Company

Solutions
Testimonials
Portfolio
Contact

Legal

Privacy Policy
Terms and Conditions

Copyright @ 2025 oemad.ai inc.