Mobile Advertising Technology Primer: $79 Billion Independent Platform Opportunity and New AI Variables

Overview

This research report is Morgan Stanley's introductory deep dive into the mobile advertising technology industry, aimed at helping investors understand the operating mechanisms, key players, and future trends of this ecosystem. The core conclusion of the report is: despite debates on the sustainability of growth, independent in-app advertising platforms still have huge under-monetized opportunities. With AI lowering the barrier to content creation and e-commerce platforms increasing ad spending, the industry is witnessing new structural growth drivers, while privacy policies and platform control remain不可忽视 risk variables.

Core views

Market Size and Growth Potential: The research report estimates that the near-term Serviceable Addressable Market (SAM) for global independent in-app advertising platforms is approximately $79 billion, expected to grow to $136 billion by 2030, corresponding to a Compound Annual Growth Rate (CAGR) of about 11% from 2025-2030. This growth rate significantly exceeds the expected 5% growth rate for in-game purchases during the same period. From a broader perspective, total global in-app advertising expenditure, including 'walled gardens,' was approximately $332 billion in 2025, while the entire mobile advertising market stood at $554 billion. The report emphasizes that compared to traditional TV and CTV, hourly user ad spend on third-party in-app ads remains low, showing clear under-monetization and growth potential. Unit Economics and Efficiency Improvement: The report proposes a key view: improving conversion rates is the core lever for platform revenue growth, even more important than increases in total advertiser budgets. Data shows that the 'real' conversion rate for top platforms like Meta is about 0.25%, while independent platforms represented by AppLovin are only around 0.03%, a difference of nearly 10 times. This means that even if independent platforms cannot fully reach Meta's level, simply narrowing the gap through algorithm optimization and data accumulation can double net income without relying on external budget growth, by increasing the effective take rate. For example, if the number of impressions required per install drops from 20 to 15, the platform's effective take rate can double from 20% to 40%. Competitive Landscape and New Entrants: There is market concern that giants like Meta entering the game advertising space will squeeze AppLovin and Unity. The report believes this direct competitive risk is overestimated. Currently, Meta focuses mainly on IDFA Opt-in traffic, while independent platforms like AppLovin have built deep moats in handling IDFA Opt-out traffic and probabilistic attribution. Additionally, although new mediation platforms like CloudX attempt to enter, they still lag far behind incumbents in scale and two-sided network effects. The real competitive barrier lies in who can consistently provide higher Return on Ad Spend (ROAS), rather than simple market share grabs. Dual Impact of AI and Privacy: The report holds a positive attitude towards AI, believing that AI lowering the barriers to game and content development will lead to an explosion in the number of apps and fragmentation of user attention, which instead increases market dependence on efficient user acquisition and monetization tools, benefiting existing ad tech platforms. Conversely, privacy policy is the largest source of uncertainty. The implementation of Apple's ATT framework has proven that the loss of data signals can severely hit ad effectiveness. If Google or Apple further restricts data access or even 'de-platforms' in the future, it will pose a survival threat to third-party advertising companies that do not control the operating system. However, historical data also shows that during bear markets for games, developers often increase ad monetization efforts to compensate for declines in in-game purchases, providing a certain macro-hedging attribute to the advertising ecosystem.

Analysis framework

The research report adopts a comprehensive framework of 'ecosystem map + unit economic model + scenario analysis'. First, by breaking down roles such as DSP, SSP, Mediation and their cash flows, it constructs a clear picture of value distribution along the industry chain, clarifying the business model where Publishers take the lion's share (about 68%) and intermediaries earn technology service fees. Second, instead of simply linearly extrapolating market size, it introduces a dynamic model of 'conversion rate × take rate', benchmarking quantitatively against industry leader Meta to demonstrate the feasibility of endogenous growth. Finally, targeting the two major variables of AI and privacy, it uses dialectical scenario analysis to distinguish between short-term noise (such as Meta doing game ads) and long-term structural changes (such as normalization of signal loss), thereby deriving a more resilient investment logic.

Methodology notes

• Industry/Industrial Analysis FrameworkVolume-Price Breakdown

  Decomposing advertising platform revenue into the product of ad impressions, effective conversion rate, and take rate

  The report doesn't just look at how much advertisers spend (total volume), but more importantly, how much net profit the platform earns for every dollar spent on buying traffic (efficiency). This breakdown method can identify companies that can make money through technological improvements even if budgets don't rise.

• Competition and Strategy FrameworkMoat / competitive advantage

  Competitive barriers built based on IDFA Opt-out traffic processing capabilities and MAX mediation platform scale

  Under new privacy regulations, whoever can handle precise targeting for 'identifier-less' traffic has real skill. The report uses this logic to judge that AppLovin is more defensive than Meta in the game vertical, because the latter is strong in identifier-based traffic.

• Industry/Industrial Analysis FrameworkSupply and Demand Framework

  AI lowering supply-side barriers leads to content oversupply, thereby boosting the value of demand-side matching tools

  It is usually thought that new technologies will disrupt old platforms, but the report thinks in reverse: when games become too numerous and messy (supply glut), users can't find good games, so they need efficient ad recommendation systems (demand matching) even more, which is a boon for existing leaders.

• Company Fundamentals and Financial FrameworkProfitability Quality Analysis

  Assessing the quality of platform monetization by comparing 'nominal conversion rate' with 'real conversion rate' (including payment ratio)

  Simply looking at clicks or installs can be distorted. The report introduces 'whether payment occurs after install' as a correction factor. This helps investors distinguish which platforms merely drive traffic and which truly bring high-value users.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• AppLovin (APP)

  Core Beneficiary: Leader in independent in-app advertising platforms, possessing the MAX mediation platform moat

  Strengths

  Leading in IDFA Opt-out traffic processing; MAX platform has built strong two-sided network effects; Conversion rate has 10x room for improvement

  Weaknesses

  Conversion rate is still one order of magnitude lower than Meta's; Highly dependent on the mobile gaming ecosystem

  Comparison

  Compared to Unity, its mediation platform is larger and demand side is richer; Compared to Meta, it is more defensive in the game vertical

  Risks

  Further tightening of privacy policies; Expansion into new verticals like e-commerce falls short of expectations; Macroeconomic downturn affecting advertiser ROI

• Unity (U)

  Important Participant: Combines engine and advertising business, reorganizing ad department to enhance competitiveness

  Strengths

  Possesses a massive developer ecosystem and first-party data; Merging with IronSource has enhanced the ad tech stack

  Weaknesses

  Ad business integration is still ongoing, efficiency awaits verification; Scale in pure ad monetization is slightly inferior to AppLovin

  Comparison

  Belongs to the independent platform camp alongside AppLovin, but the engine business provides a differentiated entry point

  Risks

  Failure of ad business restructuring; Slowing engine business growth dragging overall performance; Intensified competition putting pressure on profit margins

• Meta Platforms (META)

  Industry Benchmark and Potential Competitor: Possesses the highest conversion rate, but game ads are not currently a priority

  Strengths

  Real conversion rate reaches 0.25%, the industry ceiling; Possesses massive first-party data and user reach capabilities

  Weaknesses

  Focuses mainly on IDFA Opt-in traffic, advantage weakens in identifier-less environments; Game ads are not a core strategic priority

  Comparison

  Efficiency far exceeds independent platforms, but lacks the focus and adaptability of professional players like AppLovin in the game vertical

  Risks

  Continued regulatory pressure; Large-scale entry into game ads may worsen competition; Impact of AI investment on short-term profits

Key data

• Forecast for Independent In-App Advertising Platform Market Size in 2030$136 billionGrowth from $79 billion in 2025, CAGR approx. 11%
• Meta vs AppLovin Real Conversion Rate0.25% vs 0.03%Meta is approx. 10 times that of AppLovin, showing huge room for efficiency improvement
• Publisher Share in CPM~68%In a $3 CPM, Publishers receive approx. $2.04, with DSP/SSP taking the remainder
• Mobile Game UA Expenditure Growth Rate (2020-2025)15% CAGRFar exceeding the 3% growth rate of in-game purchases during the same period, verifying the trend of ad monetization
• Global Smartphone Users5 billion90% of mobile time is spent in Apps, laying the foundation for traffic

Impact & implications

For independent ad platforms like AppLovin (APP) and Unity (U), the report believes their long-term value depends on whether they can replicate success in non-game verticals (such as e-commerce) and whether they can continuously improve conversion rates to approach the levels of top platforms. If executed effectively, their revenue growth will no longer solely depend on macro ad budgets, but more on their own efficiency dividends. For giants like Meta and Google, although massive in scale, they face differentiated competition from professional players in specific verticals (such as in-game performance ads) and are limited by their own ecosystem positioning, making it difficult to dominate all scenarios. For the entire industry, the content explosion brought by AI will reshape traffic distribution logic, with platforms possessing the strongest matching algorithms gaining greater bargaining power; meanwhile, all third-party players must remain vigilant about tightening privacy policies from operating system manufacturers, which could fundamentally change the rules of the game.

Risks

• Privacy Policies and Platform Rule Changes: Apple's ATT and future similar measures may lead to loss of data signals, weakening targeting and attribution capabilities
• De-platforming Risk: If OS vendors restrict SDK access or measurement interfaces, third-party ad platforms may lose their operational basis
• Macroeconomic Cyclicity: Weak consumption may lead advertisers to cut budgets, especially affecting performance ad spending
• Failure to Expand into New Verticals: If e-commerce and other non-game businesses fail to achieve high conversion rates, the TAM expansion story will be disproven
• Intensified Competition: If giants like Meta or new entrants like CloudX break through technical bottlenecks, they may compress the profit margins of existing platforms

What to watch

• Quarterly trends in Conversion Rate and Take Rate for each platform
• Proportion of ad revenue and client retention in e-commerce and other non-game verticals
• Latest policy developments regarding privacy sandboxes, SKAdNetwork, and Play Integrity API from Apple and Google
• Changes in the number of AI-generated content (AIGC) listings in games and app stores and user acquisition costs
• Progress of product testing and actual deployment scale of Meta in the field of game performance ads