AppLovin Corporation (APP.US) 2026年第三季度业绩电话会

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会议摘要

AppLovin reported record Q3 revenue of $2.18 billion (+55% YoY), net income of $1.44 billion (66% margin), and $1.84 billion adjusted EBITDA. Gaming grew ~50% YoY and the consumer segment posted triple-digit growth, supported by a partial rollout of the Axon 3.0 architecture that prioritizes engineered model enhancements over organic learning. Data center costs declined as a share of revenue despite higher compute investment. The company repurchased $1.4 billion in shares and raised its authorization by $3.2 billion. E-commerce growth is strongest in APAC, with dynamic product ads outperforming video; onboarding remains a focus as the company expands CTV pilots and refines creative tools.

会议速览

Apple E's Q3 Earnings Call: Forward-Looking Statements and Non-GAAP Measures

The earnings call for Apple E's third quarter ended September 30, 2026, features forward-looking statements regarding future platform development, growth opportunities, and financial performance. Non-GAAP financial measures are discussed, emphasizing their supplementary nature to GAAP results. The call is recorded, with replay and transcript availability post-event.

Record Revenue and Model Transition: Axon's Path to Future Growth

The company achieved record revenue, exceeding guidance, driven by model transition, gaming growth, and disciplined investment. The future focuses on completing the transition, expanding customer base, improving creative tools, and exploring CTV. Long-term goals include 30% annual growth, with a commitment to transparency and operational excellence.

Apple 11 Achieves Record Earnings, Surpasses Guidance with Strong Revenue Growth and Share Repurchases

Apple 11 posted record third-quarter earnings with a 55% year-over-year revenue growth, exceeding guidance by $100 million, driven by core mobile gaming and consumer advertising. The company also repurchased $1.4 billion worth of shares and increased its share repurchase authorization by $3.2 billion, maintaining strong financial health with a net leverage below 0.1 times adjusted EBITDA. The outlook for Q4 2026 forecasts continued growth with revenue and adjusted EBITDA projected to increase by 43% to 45% year-over-year, reflecting investments in model development and scaling in the consumer vertical.

New Model Generations and Q4 Revenue Guidance Insights

Discussion on the rollout of advanced model generations with potential for optimization, alongside Q4 revenue guidance reflecting cautious growth expectations amidst strong e-commerce trends.

Update on Referral Program Progress and Future Trajectory

The referral program is in its early stages, showing accelerating customer acquisition rates. More partnerships and ad campaigns are planned, aiming for long-term growth and positive market sentiment.

Gaming Ad Revenue Growth Potential and Advancements in Connected TV Advertising

Discussion focused on the potential for long-term growth in gaming ad revenue, emphasizing a unified auction model that allows for optimized vertical growth. The dialogue also highlighted advancements in connected TV advertising (CCD), noting promising early results from pilot campaigns and increased confidence in the product roadmap, though it remains a nascent market with no immediate financial impact.

Data-Driven Model Evolution: Enhancing Output Quality with Advanced Architecture and Incremental Investments

The dialogue emphasizes the importance of accumulating customer data and refining models for improved performance. It highlights the synergy between data density, model complexity, and computational resources in achieving better outcomes. The new architecture facilitates the integration of more data, leading to enhanced model capabilities and output quality, with a focus on strategic investments in data acquisition and processing technologies.

Navigating Seasonal Advertising Trends and Growth Strategies

The dialogue explores the impact of seasonal advertising cycles on business growth, highlighting the strong returns during the holiday shopping season and the subsequent challenges in Q1. It emphasizes the strategic benefits of customer acquisition rates and the competitive dynamics in the gaming industry, suggesting a more insulated position compared to other advertising sectors. The conversation also anticipates tougher Q1 periods as the business delves deeper into economic cycles, advocating for a focus on sequential growth and leveraging high return on ad spend opportunities.

Navigating Ad Spend Growth: Managing ROI and Inventory Demand in a Competitive Market

The dialogue discusses strategies for handling increased ad spend without compressing ROI, emphasizing the company's technological advancements in improving ad targeting and conversion rates, which leads to better returns on ad spend despite rising CPMs. The company asserts its market leadership and ability to absorb additional ad spend effectively, contrasting with concerns about potential market saturation and competition.

Generalization of Models Across Media and Client Types in Evolving Architectures

Discussion on the potential for models to become more generalized over time, spanning different media types and client categories, while maintaining distinct consumer and gaming models.

Mobile App Inventory: A Booming Advertising Opportunity Beyond Social and Search

The dialogue highlights the shift towards mobile app inventory as a significant advertising opportunity, emphasizing its performance in optimizing incremental Roas and audience reach. It suggests that with advancements in mobile web and iOS, more brands are likely to allocate advertising dollars to apps, viewing it as a lucrative space for performance marketing and audience discovery.

Expanding Inventory & Addressing Share Price Discrepancy

The dialogue explores the potential benefits of expanding available ad inventory within the gaming advertising market and the company's strategy to address the disconnect between the current share price and its intrinsic value, including an increased focus on buybacks.

Evolving Ad Formats for Enhanced E-Commerce Advertising and Learning Curve Optimization

The dialogue discusses the potential of diversified ad formats to boost e-commerce effectiveness, emphasizing the evolution of dynamic product ads and the anticipation of improved AI video creation. It also addresses the learning budget and time for e-commerce customers, highlighting advancements in model architecture and customer validation processes for new advertising relationships.

Consumer Advertising Growth & Data-Driven Model Evolution

Discusses the current state and future roadmap of consumer advertising, emphasizing the role of data and model sophistication in enhancing ad outcomes. Highlights the importance of ad creativity, scale, and watch time in achieving success on the platform. Future focus includes accelerating data integration for improved business scalability.

Building Confidence in Ad Tech Growth: Visibility and Durability of Business Model

Discusses the company's confidence in its business model's durability, highlighting consistent outperformance against expectations. Emphasizes the importance of technology improvements, new customer growth, and the scale of operations. Acknowledges the unpredictability of growth due to the early stage of the consumer segment, while asserting the value of engineering, models, and data integration.

High-Level System Creation and Transition to Ralph Shakar's William Blair Session

The dialogue highlights the creation of a sophisticated system, followed by a transition to a session with Ralph Shakar at William Blair, emphasizing strategic planning and expert engagement.

Significant Model Update and Market Competition Update

Discusses a major model update likened to Axon 3.0, emphasizing improved data processing and future potential, amidst strong market competition and growth in the industry, highlighting the collaborative improvement of models for customer benefits.

Strategies for Achieving Long-Term Growth in Gaming and Consumer Sectors

The dialogue discusses strategies for achieving long-term growth, emphasizing the importance of new customer acquisition, model improvements, and the seasonal performance in both gaming and consumer sectors, with an expected 8% to 10% sequential growth embedded in the guidance.

Data Acquisition and Market Penetration Strategies for Accelerating Business Growth

The dialogue explores the strategic acquisition of data and customer relationships to expedite business growth, emphasizing the importance of leveraging market penetration in regions like APAC. It highlights successful past acquisitions, such as buying Max, which significantly accelerated customer base expansion and data integration, setting a precedent for future strategic moves.

Sustained Growth from Model Retraining and Future Projections

The dialogue explores the impact of continuous model retraining on growth, questioning if the 3-5% uplift from self-learning remains consistent, its inclusion in Q4 forecasts, and future reliance on model enhancements versus engineered directed improvements.

Self-learning Models Enhance Business Growth Through Continuous Improvement

Deep learning models in companies improve through self-learning, akin to human learning, enhancing business growth unpredictably. Despite not being trackable to specific percentages, these models' enhancements, including annual big updates and quarterly tests, significantly contribute to the company's success over time.

Strong Double-Digit Growth in Max Market Despite Slower Supply Expansion

Max market continues to grow at a strong double-digit rate annually, contrasting with slower growth in supply and value within the advertising ecosystem, which is expected to increase at low double digits to possibly single digits.

Analyzing Rising Supply Costs and Technological Innovation in Advertising

Discusses the increase in supply acquisition costs and how technological advancements have allowed companies to monetize impressions more effectively, driving business growth faster than market rates. The dialogue highlights the balance between rising costs and improved technology in maintaining competitive advantage in the advertising industry.

Understanding Take Rate Fluctuations and Model Differences in Consumer and Gaming Sectors

The discussion revolves around the concept of take rate in business, explaining it's not a primary focus due to its post-facto nature. It highlights how conversion rates and technological innovation impact take rates. The conversation also explores the potential for different take rate fluctuations between consumer and gaming models, concluding that inherent differences are minimal due to competitive parity in predicted values.

Ownership of Mediation Data in Gaming Transactions

Discusses who owns data processed in gaming transactions, clarifying that original data belongs to the ad company, while mediation platforms commoditize data for fair bidding, maintaining data ownership with the source.

Consumer Onboarding & Sophisticated Customer Focus in Advertising Platforms

The dialogue highlights the learning curve for new media buyers adapting to innovative advertising platforms, emphasizing the need for education on optimizing content and targeting. It also underscores the strategy of prioritizing sophisticated customers through strategic partnerships to enhance immediate revenue generation and long-term business growth.

要点回答

Q：What were the financial results for Apple's third quarter ended September 30, 2026?

A：Apple's third quarter revenue was $2.18 billion, marking a 55% year-over-year increase. EBITDA came in well above the high end of guidance. The quarter included a record net income of $1.44 billion and an industry-leading 66% net income margin. Adjusted EBITDA was $1.84 billion, with an 84% margin, up approximately 190 basis points from the same period last year.

Q：What is the projected growth and revenue for the fourth quarter of 2026?

A：For the fourth quarter of 2026, Apple expects revenue between $2.365 billion and $2.395 billion, representing approximately 43% to 44% year-over-year growth or 8% to 10% sequential growth. The projected adjusted EBITDA is between $1.995 billion and $2.025 billion, indicating approximately 43% to 45% year-over-year growth at the midpoint.

Q：Can you describe the new generations of models that are being rolled out?

A：The new generations of models being rolled out are built on architectural changes that allow for better performance and more room for optimization compared to the previous generation. The company aims to create larger models with improved output by utilizing more compute power. However, a specific timeline for a full rollout was not disclosed, and the progression of these models will not be committed to.

Q：What factors are influencing the conservative sequential revenue growth outlook for Q4?

A：The guidance for Q4 sequential revenue growth reflects the same philosophy as previous quarters, with expectations aligned with known variables at the time of the call. Factors include normal seasonality within the quarter, the performance of the model update already live, and the anticipated increase in data center costs. These elements have not changed from previous guidance, explaining the conservative outlook.

Q：What are the expectations for the growth of gaming ad revenue and how does the company plan to achieve it?

A：The company expects to grow its gaming ad revenue by 30% year over year for the long term. It plans to achieve this by continuing to expand partnerships, running more ad campaigns, and generating more positive sentiment for the product in the market. Additionally, incremental studies need to prove effectiveness before scaling for the long term.

Q：How will the new model affect gaming revenue growth?

A：The new model is more accurate than the old one and has significant room for optimization, which could allow gaming revenue to grow at higher rates in the long term. However, it is not a requirement for reaching the 30% growth rate if both parts of the business (consumer and gaming) grow quickly.

Q：What is the progress and potential impact of connected TV ads on the product roadmap?

A：The company is making progress with connected TV ads, with pilot campaigns showing promising results. Although it is a new market and it's too early to expect significant accretive impacts to numbers, the team is gaining confidence in the product roadmap and is excited about the potential for future growth.

Q：What is the company's view on the potential for the gaming business to experience a tipping point similar to past growth stages?

A：The company believes that as the gaming business continues to grow and gather more data, it will eventually require a more complex model to process and generate better output. The architecture allows for this data to be incorporated, and the company anticipates that as it adds more data, it will be able to train a larger model, resulting in better output.

Q：How is the company incorporating consumer data to refine its model and improve performance?

A：The company is incorporating consumer data into its system to improve the model's predictions and potentially enhance customer acquisition and data-driven targeting. This strategy has been shown to improve model complexity and output every time more data is added.

Q：How is the company addressing the potential for increased competition and pricing in the auction as a result of new advertisers entering the space?

A：The company's response to increased competition and pricing is to note the growth in the business over the last three years and the significant increase in customer return on ad spend. It suggests that the market and technology are performing well, and while prices may rise, the targeted approach increases conversion rates and overall return on ad spend. The company believes its scale provides a competitive advantage and the ability to handle additional ad spend without significantly impacting incumbent customer ROI.

Q：How will the architecture handle increasing amounts of data and become more generalizable across media types and client types?

A：The architecture is designed to potentially handle more generalizable data across media types and client types over time, although the specific details on how it will be implemented were not provided in the transcript.

Q：What is the company's view on the performance of its advertising solutions for brands, particularly in the context of mobile web and iOS 16 updates?

A：The company acknowledges the challenges that brands face with mobile web inventory supply and the iOS 16 updates but suggests that performance marketers are likely to shift more dollars into the app space due to its scale and substantial growth potential. Performance brands are expected to find the app space attractive for its size and opportunities.

Q：What could be the impact of expanding the non-gaming inventory on the advertising market?

A：The expansion of non-gaming inventory could lead to a significant increase in the advertising market, which is bigger than people realize, opening up opportunities for more supply. This could result in a substantial amount of inventory that could be moved in one shot and have a compounding effect over time.

Q：How does the speaker describe the potential of the conversion rate in the gaming ecosystem?

A：The speaker indicates that there is a low conversion rate within the gaming ecosystem and that by diversifying ads, such as reducing the number of gaming ads and increasing product ads, they can make the model more targeted and effective. This is identified as the largest needle mover for the short to medium term.

Q：What does the speaker see as the ultimate goal for e-commerce advertising formats and how does it relate to learning time and volume?

A：The speaker believes that a more diversified ad format could be the ultimate goal to make e-commerce more effective. They suggest that as dynamic product ads evolve and improve, they will create better ad formats for advertisers and that learning time will be improved as the ad format matures and more data becomes available.

Q：How has the learning time and budget for e-commerce customers improved over time?

A：The learning time and budget for e-commerce customers have seen improvements over time. The model and model architecture have improved and are faster with less data. However, customers, especially risk-averse ones, still require validation of new relationships, necessitating both spending and return on outlay as well as incremental studies. Nonetheless, the speaker notes that the product is getting better every quarter with new releases.

Q：What is the current state of AI tools in the advertising industry and how does it affect customer ad creative?

A：The speaker mentions that there is less research and development outside the company regarding AI tools for ad creative. They acknowledge that ad creative has been a primary sticking point and point of failure for many customers. Although some customers are successful without it, others may be stalled due to a lack of understanding of the importance of scale. In the current state, the company is providing an opportunity for customers to benefit from ad creative that leverages scale and the large amount of watch time their ads generate.

Q：How does ad placement on the platform contribute to customer success and the visibility of the business model?

A：Ad placement on the platform contributes to customer success by ensuring ads are seen for an average of over 35 seconds of watch time, which is unique to the platform and significantly contributes to ad visibility. The visibility of the business model is enhanced by this, as customers that understand the value of scale become large spenders. Additionally, the business has strong margins and is performing well, which adds confidence in the durability of top-line growth.

Q：What factors currently influence the company's ability to predict future growth?

A：The company's ability to predict future growth is currently tied to improving technology and new customer acquisition. However, due to being in a nascent consumer segment, there isn't yet any material information that can predict future trends. The company has been consistently outperforming expectations, with a track record of beating high-end guidance 14 out of 16 quarters.

Q：How does the ad tech company measure its success and what does it plan to achieve in the future?

A：The ad tech company measures its success through the billions of dollars of revenue it generates from the billions of dollars of spend by customers on its platform. Despite not being able to provide certain KPIs because of the business's growth stage, the company is excited about its future potential, with a large business that is growing quickly and focusing on creating value through its engineers, models, and data systems.

Q：Can the company be compared to a previous model update (Axon 2.0)?

A：The company has experienced a model update that is considered as significant as the previous one (Axon 2.0), which has provided a much larger path for future growth, such as processing more data, creating bigger clusters, and improving output. Although not a direct-to-consumer AI company, the new model update offers a longer development roadmap and excites the team about future potential.

Q：What is the company's perspective on market performance and competition?

A：The company views the industry as zero-sum, where one company's gain does not necessarily equate to another's loss. It notes that all companies in the market are performing well, and the pace of other companies' growth is not squeezing them out. The company has experienced a massive quarter and is optimistic about future growth, with several factors contributing to it.

Q：How does the company plan to achieve long-term growth and what are the expected contributions from gaming and consumer segments?

A：Long-term growth is expected to come from new customer acquisition in gaming and the continuous data improvement in the consumer segment, where the company is still in a nascent stage. Gaming is projected to have seasonality and a strong Q4, while consumer growth is anticipated to accelerate over time as more customers become aware of the company's offerings. The company expects both gaming and consumer segments to grow consistently, with the consumer side being particularly robust due to its market penetration.

Q：What are the company's expectations for pixel data and APAC region growth?

A：Pixel data is driving e-commerce customer growth, particularly in the APAC region. APAC is experiencing stronger product-market fit due to more tailored advertising and the absence of some complexities present in Western markets. The company aims to acquire customer relationships that are valuable and would look for deals that bring in a substantial number of customers quickly, thus accelerating the business.

Q：How does the company perceive the impact of self-optimizing models and model retraining on quarterly growth?

A：The company believes that self-optimizing models and model retraining provide a steady tailwind to quarterly growth, which is distinct from engineered model uplifts. These mechanisms enable the models to learn from new data and become smarter over time. While the exact percentage of this self-optimizing contribution to growth is not quantified, it is an inherent characteristic of the models used by the company.

Q：What is the growth rate of the max market compared to other parts of the advertising ecosystem?

A：The max market is growing at a very strong double-digit growth rate every year, which is significantly faster than the growth rate in most other parts of the advertising ecosystem, which is probably in very low double digits or possibly even single digits.

Q：What are the two main drivers of supply costs in the advertising ecosystem?

A：The two main drivers of supply costs are more supply entering the market and companies becoming more efficient at monetizing impressions, which increases the value of the auction and thus the cost that publishers receive.

Q：What is the impact of the company's technology innovation on their cost of supply acquisition?

A：The company's innovation has allowed them to outperform the market in terms of monetizing impressions. They have been able to improve their technology better than the market, which means their business has grown much faster than the market, without needing to outspend their competitors in supply costs.

Q：Why is the take rate not an optimized focus in the business?

A：The take rate is not optimized as it happens after the fact and is a result of the business's performance. Since it is influenced by factors like conversion rates and the cost of acquiring impressions, the business focuses on these areas rather than the take rate itself.

Q：What role does technological innovation play in the company's ability to outperform competitors?

A：Technological innovation is critical in the company's ability to outperform competitors. When the company's engineers innovate at a faster rate, the company can improve its take rate and performance. If they innovate at the rate of the market, they maintain their current position, but if competitors innovate faster, it can lead to a contraction in the take rate due to better market pricing.

Q：What differentiates the take rate in consumer versus gaming sectors?

A：The take rate in consumer versus gaming sectors is not significantly different. Both sectors are dynamic and when a model is highly predictive, like a gaming ad with a predicted value of $20 CPM, the variability between consumer and gaming ads is minimal, with consumer ads potentially coming close to matching the gaming ads in value.

Q：Who owns the data within the mediation platform that processes transactions?

A：In a mediation platform that processes transactions, the ownership of the data lies with the companies that wrote the models which process the data. These companies have relationships with customers and consumers and the data is an output of their models that remain with them. The platform commoditizes access to this data, ensuring fairness and allowing all bidders equal access to maximize the price of each impression.

Q：What challenges do new customers face with ad launching and optimization?

A：New customers face challenges with ad launching and optimization because they are not accustomed to creating ads that are as engaging or perform as well as ads that have been optimized over time. Additionally, the learning curve for new platforms requires a shift in understanding for customers who are not used to launching ads or creating content that stands out in the marketplace.

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