Despite multi-billion dollar lawsuits and litigation, Meta demonstrates impressive revenue growth, especially in the third quarter. How does the company manage to stay afloat and even thrive amidst such financial challenges? The answer lies in strategic investments in artificial intelligence, which is becoming a key driver of Meta’s advertising revenue growth, even when new products like Muse are not yet profitable. Let’s delve into the details of this phenomenal success and learn how Meta uses AI to optimize its advertising platforms.
Meta: 26% revenue growth despite Muse’s unprofitability and AI’s influence
Meta has had a challenging year, marked by multi-billion dollar lawsuits and litigation. One of them, related to the harmful effects of social networks on children, led to an $18 billion settlement. Another lawsuit, concerning data privacy violations, resulted in an order to pay the state of New Mexico $25 billion. This decision was made hours before Meta’s third-quarter report, and the company has already stated its intention to appeal it.
Despite these legal battles, the third quarter was strong for Meta. Revenue from the family of apps grew by 26% year-over-year, reaching $64.2 billion. Of this amount, $63.1 billion came from advertising revenue. The number of ad impressions also increased by 10%.
Muse: Popularity without Profit
Weeks after Muse’s launch in early September, Meta introduced Muse for small businesses. This is a “new set of skills and connectors” within the Muse app that helps companies find customers, analyze ad effectiveness, optimize it, and develop campaigns, as Meta CFO Susan Li told investors.
From a consumer perspective, the launch of Muse was “one of the most successful launches in the company’s history,” according to Meta CEO Mark Zuckerberg. This claim may be debatable given the privacy concerns associated with early versions of the model. However, as with other Meta platforms, privacy concerns have not hindered widespread adoption.
Zuckerberg noted that all these agents are “very computationally intensive.” Meta expects cost efficiency to improve 10x over the next year, which “will allow it to become profitable once revenue lines scale,” according to Zuckerberg. In other words: Muse is popular for now, but not making money.
If Meta’s ad revenue growth cannot be attributed to Muse, then what is the reason? The answer is artificial intelligence, which has long been central to Meta’s overall ad platform strategy.
Earlier this year, Meta launched Generative Recommender — an LLM-based tool that analyzes ad content and user preferences to determine the most relevant ads for a specific person. Target audience segments have seen an almost 2% increase in conversions since the tool’s launch in Facebook feeds, Meta CFO Susan Li said.
Meta also expanded GEM, its generative ad recommendation model, to include more user touchpoints, Li said. This means Meta can now unify recommendation data from various platforms in one place. This capability has led to:
A 1.7% increase in conversions for external campaigns.
A 9.6% increase in in-app conversions last quarter.
“AI investments have been benefiting Meta’s advertising business for many years. As LLMs become the foundation of more and more of the AI infrastructure, Meta will gain more insights into people’s preferences and interests, both in organic content and recommendations,” — Susan Li, Meta CFO.
The goal is not only to fuel Meta Advantage+’s ad optimization engine but also Meta’s creative personalization features.
Netflix: Revenue Growth and Advertising Challenges
Netflix’s revenue grew 12% year-over-year to $12.9 billion in the third quarter, meeting forecasts. However, the advertising business is slightly behind expectations, which led Netflix to adjust its forecast for the remainder of the year.
Frequently Asked Questions
What was Meta’s total revenue growth in the third quarter?
How much did Meta’s total revenue grow in Q3?
Meta’s total revenue grew by 26% year-over-year in the third quarter, reaching $64.2 billion.
How much ad revenue did Meta generate in Q3?
Meta’s ad revenue was $63.1 billion in the third quarter.
Is Muse profitable for Meta?
No, Muse is not currently profitable. Mark Zuckerberg noted that Muse agents are “very computationally intensive,” but Meta expects a 10x improvement in cost efficiency next year.
Which AI tools contributed to Meta’s ad revenue growth?
Growth was driven by the Generative Recommender, which increased conversions by 2%, and the expansion of GEM, which led to a 1.7% increase in conversions for external campaigns and a 9.6% increase for in-app campaigns.
How much did Netflix’s revenue grow in Q3?
Netflix’s revenue grew by 12% year-over-year, reaching $12.9 billion.
Conclusion
So, Meta is demonstrating strong revenue growth, primarily due to investments in AI, which significantly improve advertising performance. Products like Muse are currently unprofitable but have potential. While Netflix faces challenges in its advertising business, Meta continues to prove that favorable CPM and cheap hypothesis testing with AI optimization are a reality. Want to know how much money each ruble spent will bring? Learn how AI is changing the unit economics of advertising campaigns.
In a world where neural networks and AI avatars are becoming the norm, tech giants are actively restructuring their strategies. Recent events show how AI transformation and mass video generation by neural networks are changing the market landscape, forcing companies to optimize processes and cut costs. A Reuters report sheds light on Meta’s large-scale “Organizational Transformation” (Project OT), aimed at significantly reducing staff by transferring functions to agency technologies.
Welcome to a new era where artificial intelligence is not just a tool, but a driving force behind global corporate changes. From Meta, re-evaluating its priorities after ambitious projects, to The Trade Desk, implementing intelligent assistants for advertising campaigns, and USA Today, adapting content for AI bots — each company is finding its way in this rapidly evolving reality. Get ready to learn how AI is changing the rules of the game, optimizing processes, cutting costs, and opening new horizons for business.
Meta: From Metaverse to AI Optimization
After an ambitious but not very successful dive into the metaverse, Meta has focused on staff optimization and automation. Project OT is an internal project to reduce the number of employees and transfer services to agency technologies.
These are not just cutbacks, but a strategic redistribution of resources, where AI efficiency versus real UGC becomes a key factor.
The Trade Desk: “Ask Koa” — A New Level of AI Interaction
Intelligent Assistant for Advertising Campaigns
The Trade Desk (TTD) introduces “Ask Koa” — a centralized AI interface that serves as a “single point of entry for various AI agents.” These chatbots will manage various aspects of the programmatic workflow, including audience creation, campaign optimization, and insight generation.
This significantly increases AI production efficiency, allowing for scaling the impossible.
Expanding Functionality and Combating “Ad Fatigue”
Transition to closed beta: “Ask Koa” is transitioning from alpha to closed beta this week, with plans for further expansion.
Frequency Capping Tool: A new tool automatically adjusts ad frequency based on brand performance data and campaign pace. This reduces “ad fatigue” and increases AI creative conversion.
“Much of the input for our product development process comes from customer feedback,” notes Eric Bosco, VP of Product Management at TTD. This confirms a customer-centric approach to AI solution development.
USA Today Co. joins publishers like Time and The Economist in restructuring its content for AI bots. The new format will make it easier for AI systems to process and cite USA Today content.
This is part of the publisher’s broader GEO strategy aimed at optimizing for search engines using AI.
Invisible Changes for Users
Kara Chiles, Senior Vice President of Product Management, emphasizes that these changes will not affect how people perceive content. “Most of the modifications will not be visible to people. This concerns infrastructure, metadata, how we structure our formats and templates to be as discoverable as possible for AEO and GEO,” she says.
The goal is to conclude more licensing agreements with AI companies and increase the value of current deals, which opens up new opportunities for AI UGC for crypto projects and other niche markets.
Other AI Industry News
Meta agrees to pay up to $18 billion to 48 states as part of a settlement of a federal lawsuit over the harm of social media to children and adolescents.
Attaching a celebrity name to a brand does not replace good marketing.
Reddit is no longer a leading source of citations in ChatGPT, but remains important for marketers.
AI-generated content is so prevalent that even images of cute animals can be fake.
X (formerly Twitter) demands that companies that allow content to be viewed without accessing the X site cease operations.
Frequently Asked Questions
What are “agent technologies” in the context of Meta?
“Agent technologies” at Meta are AI systems capable of performing tasks and providing services that previously required human involvement. This allows for significant staff reductions and scaling operations, for example, in subscription neuro-production.
How will The Trade Desk’s “Ask Koa” improve advertising campaigns?
“Ask Koa” integrates various AI agents to optimize advertising campaigns. It assists in audience creation, improving efficiency, and generating insights, leading to more effective AI advertising and a reduction in the cost per AI creative.
Why are publishers restructuring content for AI bots?
Publishers, such as USA Today, are restructuring content for AI bots to improve its discoverability in AI systems, facilitate citation, and secure more licensing agreements with AI companies. This also aids in SEO optimization and text-to-video generation.
Conclusion
The era of AI video generation and automation has arrived. Companies like Meta and The Trade Desk are actively investing in neural networks and agent technologies to remain competitive. This opens up unprecedented opportunities for mass video generation by neural networks, creating AI commercials, and even AI video factories for e-commerce.
If you want to know how much one AI creative costs or how a neural network writes scripts and edits, follow our updates. The future of content production is in AI. Don’t miss your chance to be at the forefront of this revolution! Learn more about AI content production.
