Category: Internet

  • Meta Deep Dive

    Meta Platforms (Facebook’s parent company) continues to post robust advertising revenue growth in 2024–2025, even as usage on its flagship social apps shows signs of stagnation or decline. In 2024, Meta’s ad revenue jumped to $164.5 billion (up from $134 billion in 2023)sproutsocial.com, and the trend carried into 2025 (Q1 2025 ad revenue grew 16% year-over-year to $41.4 billion)ppc.land. This record growth persists despite “declining” user engagement on Facebook and Instagram – for example, Mark Zuckerberg has admitted that time spent on Meta’s apps has fallen since TikTok’s risesocialmediatoday.com, and Facebook’s usage has plateaued (total hours on Facebook were flat year-over-year in mid-2024)sensortower.com. Notably, Facebook’s monthly active users even saw a first-ever slight decline from Q3 to Q4 2024thesocialshepherd.com. The following report analyzes why Meta’s ad business remains on a growth trajectory amid these engagement headwinds, focusing on six strategic factors:

    • AI and machine learning advancements in Meta’s ad platform (better targeting & optimization)
    • Shifts in advertiser behavior and strategy (performance marketing focus, brand safety, cross-platform campaigns)
    • The role of Reels, Stories, and new ad formats in capturing attention and revenue
    • Global user base expansion and the contribution of non-U.S. markets
    • Advertiser responses to engagement trends – overlooking declines vs. adapting tactics
    • Insights from executives and investor reports (e.g. earnings calls commentary)

    Each section below delves into these areas, with data and primary-source commentary illustrating how Meta converts its massive user base and technological investments into advertising dollars – seemingly regardless of softening engagement on individual platforms.

    1. AI and Machine Learning Enhancing Ad Targeting & Performance

    Meta has increasingly leveraged artificial intelligence (AI) and machine learning to boost the effectiveness of its advertising platform. These innovations have improved ad targeting, delivery, and conversion, allowing Meta to extract more revenue per user and per ad, even if user activity growth is slow. Key points include:

    • Advanced AI-driven targeting: Meta’s algorithms now do much of the work in finding the right audience for ads. Mark Zuckerberg noted that Meta’s ad system can often “better predict who would be interested” in an ad than advertisers can manuallys21.q4cdn.com. In practice, AI has made Meta’s ads better at finding the right audiences and optimizing spend, as the company integrates AI across ad productscreativestrategies.com. This translates to higher return on investment (ROI) for advertisers, encouraging them to keep or increase ad budgets despite any user engagement dips.
    • Algorithmic ad optimization: New machine learning models have significantly improved ad performance. In Q1 2025, Meta introduced a Generative Ads Ranking model (GEM) for ads. According to CFO Susan Li, this model uses a novel architecture that is “twice as efficient at improving ad performance” for a given amount of data/computeppc.land. Early results were impressive – testing GEM on Facebook Reels ads showed up to a 5% increase in ad conversionsppc.land. By improving conversion rates and outcomes, such AI optimizations boost the value of each ad impression. (Notably, in Q1 2025 ad impressions grew only 5% while the average price per ad rose 10%, indicating Meta is monetizing better via targeting/optimization rather than sheer volumeppc.land.)
    • AI-boosted user engagement: Meta is also using AI to enhance the user experience, which indirectly supports the ad business. More powerful recommendation algorithms surface content that keeps users watching, scrolling, and returning. Internally, Meta reported that improvements to its AI-driven feed and video recommendations led to roughly an 8% lift in time spent on Facebook and Instagrams21.q4cdn.com. Zuckerberg highlighted that “advances in AI continue to improve the quality of recommendations and drive engagement” – for instance, a new unified video recommendation system increased engagement on Facebook Reels substantiallys21.q4cdn.com. By regaining some of the user attention (even as TikTok competes for it), Meta ensures a healthy supply of eyeballs for advertisers. In short, AI helps Meta squeeze more engagement and ad clicks out of a given user base.
    • Automation of ad creation and delivery: Meta’s vision is that AI will eventually handle many aspects of advertising automatically. Zuckerberg has described a future where a business can simply specify its goal and budget, and Meta’s AI will “just do the rest”ppc.land – finding the audience, optimizing bidding, and even generating creative. While not fully realized yet, steps in this direction (like Advantage+ automated campaigns) are already attracting advertisers. This AI-driven automation makes advertising on Meta easy and efficient for marketers, which keeps demand high. Zuckerberg framed this as “redefining what advertising is into an AI agent that delivers measurable business results at scale”ppc.land – a strategy to capture more advertising dollars by outperforming traditional manual campaign setups.

    Meta’s heavy investment in AI (it significantly raised capital expenditure guidance to build AI data centersreuters.com) underpins these improvements. In essence, better AI is allowing Meta to monetize each user more effectively, offsetting slower user growth or engagement. Advertisers are willing to spend more when the targeting and outcomes improve, which has propped up Meta’s revenue growth.

    2. Shifts in Advertiser Behavior and Strategy

    Changes in how advertisers allocate budgets and plan campaigns have also benefited Meta. In 2024–25, marketers are prioritizing platforms that deliver strong performance and broad reach, and Meta fits the bill – engagement concerns notwithstanding. Several strategic shifts on the advertiser side explain the continued revenue influx:

    • Focus on performance marketing and ROI: Advertisers have increasingly gravitated toward direct-response and performance-based advertising, especially in uncertain economic times. Meta’s platforms (Facebook/Instagram) are highly developed for performance marketing – offering detailed targeting, conversion tracking, and sales-oriented ad formats. This makes Meta a top destination for advertisers who need to show concrete results (app installs, e-commerce sales, etc.). Indeed, even as overall marketing budgets tightened in 2024, advertisers saw Meta as a “reliable go-to” channel to drive outcomesreuters.com. The sheer scale of Meta’s user base (3+ billion daily actives) gives advertisers confidence they can find enough customers, even if individual user sessions might be shorter or people are more scattered across apps. In short, brands keep spending on Meta because it reliably delivers ROI, which matters more to them than time-spent stats.
    • Advertisers largely undeterred by engagement dips: Notably, there has been little evidence of advertisers pulling back solely due to lower engagement metrics. Industry insiders suggest that even when Meta makes controversial changes or faces usage stagnation, most advertisers don’t make major spending shiftsbusinessinsider.com. For example, when Meta announced looser content moderation (a potential brand safety concern), ad buyers expressed worry but “generally didn’t expect the changes to hurt Meta’s [ad] business”businessinsider.com. The same appears true for engagement declines – advertisers are aware of the trends but are not fleeing. Meta’s advertising reach is too valuable, and no comparable alternative can yet match its combination of scale and ad efficacy. Essentially, advertisers are willing to “ride out” any dips in user engagement as long as their ads continue performing well on the platform.
    • Brand safety improvements and stability: Meta has taken steps to reassure advertisers on issues like brand safety, which helps keep big brand budgets in the ecosystem. In late 2024, Meta introduced new brand safety tools – for instance, giving advertisers control to mute comments on their ads and block ads from appearing alongside certain contentemarketer.com. These measures address advertisers’ concerns about ad adjacency to toxic content, which had led to boycotts in the past. By 2025, many marketers seem to have accepted Meta’s safeguards; there is a sense that “brand safety is a myth” and that leaving Meta would hurt reach more than it helps safetydigiday.com. The outcome is that advertisers continue spending on Meta instead of shifting budgets elsewhere, further fueling revenue growth.
    • Cross-platform campaign integration: Advertisers today approach Meta’s Family of Apps as an integrated marketing channel. Rather than buying Facebook or Instagram in isolation, they use Meta’s unified Ads Manager to run campaigns across Facebook, Instagram, Messenger, and the Audience Network simultaneously for maximum reach. Meta has made this extremely simple – adding Instagram or Reels placements to a Facebook campaign is “as easy as checking a box,” according to analystsreuters.com. This ease of cross-platform advertising means marketers can follow user attention within Meta’s ecosystem without friction. For example, as Instagram Reels gained popularity, advertisers quickly expanded campaigns into Reels ads. Meta’s CFO noted that over 75% of Meta’s advertisers were running ads in Reels by mid-2023reuters.com – reflecting rapid adoption. This cross-app flexibility lets advertisers maintain effective reach even if engagement shifts from one Meta app/surface to another. In effect, advertisers are not abandoning Meta due to engagement changes – they’re adapting within Meta (e.g. shifting spend from Feed to Reels or Stories) while keeping overall budgets in the Meta family.
    • Reliance on Meta amid industry shifts: Broader industry trends (like Apple’s privacy changes limiting third-party tracking and the deprecation of cookies) have paradoxically made Meta more important for advertisers. With less visibility into open web ads, many brands turned back to “walled gardens” like Meta that have rich first-party data and AI to optimize targeting. Additionally, during economic volatility or events (e.g. in 2024 some advertisers cut spend on experimental channels), those budgets often flowed to the known performers – with Meta benefitingreuters.com. In summary, advertiser strategy in 2024–25 has been to consolidate around platforms that drive results at scale, and Meta’s dual focus on performance and brand accommodations keeps it at the top of that list.

    3. The Role of Reels, Stories, and Emerging Ad Formats

    Meta’s introduction and monetization of new content formats – particularly Reels (short-form video) and Stories (ephemeral photo/video posts) – has been crucial in sustaining ad revenue growth. These formats help capture user engagement that might otherwise be lost (e.g. to TikTok or Snapchat) and create new inventory for ads. Key observations:

    • Reels driving video engagement: Reels (vertical short videos on Facebook and Instagram, akin to TikTok) have exploded in popularity. By mid-2024, Meta’s data showed that on Facebook, 30% of a user’s time was spent on Reels – double the share from January 2024sensortower.com. Instagram has effectively become a “video-first” platform, with users now spending about two-thirds of their time on Instagram watching videos (Reels or longer form)emarketer.com. This shift addresses the TikTok threat by keeping users engaged with Meta’s own short-form videos. While Reels initially launched in 2020 to skepticism, by 2023 Meta was touting huge usage: the number of Reels plays across FB and IG reached 200 billion per day (up from 140B/day in late 2022)reuters.comThis surge in Reels engagement provides Meta a fresh avenue to show ads, compensating for any decline in scrolling the news feed.
    • Monetization of Reels (and Stories): Meta has rapidly ramped up advertising in these new formats. Zuckerberg revealed that by mid-2023, Reels reached a $10 billion annual revenue run rate – a steep climb from about $3B in late 2022 and just $1B in mid-2022reuters.com. In other words, Reels went from a zero-revenue format to a significant chunk of Meta’s business in ~18 months, nearly catching up to TikTok’s ~$10B in ad revenuereuters.comStories (the 24-hour posts copied from Snapchat) have also become a mature revenue driver: by 2024, Instagram Stories contributed roughly 25% of Instagram’s ad revenueemarketer.com. (Feed ads were ~54% and Reels/Explore ~9.6%, with Reels share rising fastemarketer.com.) The success of Stories over the past few years proved Meta could introduce a new format and monetize it heavily; now Reels is on the same path. These emerging formats expand the total ad inventory and help offset any revenue loss from users spending less time in feeds. Even if a user’s feed scrolling dropped, the ads they now see in Reels or Stories can make up the difference.
    • Advertiser adoption of new formats: A major factor in monetization success is that advertisers have been quick to embrace Reels and Stories. Meta’s integration of formats means advertisers don’t need a whole new strategy – they can use existing assets or slightly tweaked creatives to run ads in Reels and Stories. According to Meta, more than three-quarters of its advertisers were placing ads on Reels by 2023reuters.com. Analysts noted “it’s as easy as checking a box” in the ad interface to extend a campaign to Reelsreuters.com. This high adoption rate shows that advertisers followed the user shift into short-form video instead of pulling spending. Zuckerberg had predicted this behavior: when Reels usage started cannibalizing some feed time, he told investors he expected advertisers to “embrace the format over time, as they had with…Feed to Stories” transitionsreuters.com. That prediction came true – advertisers adapted by spreading budgets across Feed, Stories and Reels, ensuring that even if one surface (like traditional feed) saw lower engagement, the overall campaign could still reach users elsewhere in Meta’s apps. This adaptability has been key to Meta retaining ad dollars that might have otherwise left for TikTok or other platforms.
    • Emerging platforms and ad opportunities: Beyond Reels and Stories, Meta is also exploring entirely new platforms and ad formats – which, while nascent, represent future growth potential. For example, Meta launched Threads (a Twitter-like text social app) in mid-2023 and quickly amassed 275 million users by Q4 2024jonloomer.com. As of late 2024 Threads had no significant ads and Meta does not expect Threads to contribute meaningful revenue until it scales further in 2025jonloomer.com. However, when the time is right, Threads could open another revenue stream (eMarketer predicts Threads ads will roll out cautiously, likely contributing modestly by late 2025)emarketer.com. Similarly, WhatsApp and Messenger are being monetized via “click-to-message” ads and business messaging. These allow advertisers to pay to start conversations with users in chat apps. While small today, the segment is growing fast – the WhatsApp Business Platform’s revenue grew 55% YoY to $519 million in Q4 2024fifthperson.com (though that sits outside “advertising” in Meta’s reporting). The key takeaway is that Meta is continually adding new ad real estate – whether within its main apps (Reels/Stories/Explore) or in new apps (Threads) or services (messaging). This pipeline of formats ensures that if user engagement shifts, Meta has somewhere to monetize it. Reels and Stories have proven this strategy effective, capturing user time that might have been lost and converting it into revenue.

    In summary, Meta’s agility in product innovation has kept its platforms sticky to users and attractive to advertisers. Reels and Stories helped Meta retain users (especially younger ones) and gave advertisers new ways to reach them. The rapid monetization of these formats is a critical reason ad revenue rose in 2024 even though Facebook usage was flatsensortower.com – Meta simply monetized different behaviors (short videos, ephemeral sharing) instead of the old news feed scrolling.

    4. Global User Base Expansion and Non-U.S. Markets’ Impact

    Meta’s advertising growth is also fueled by its vast international user base, which continues to expand. While Facebook and Instagram may be saturating in North America or seeing engagement declines in some cohorts, the global scale and growth in emerging markets provide a counterbalance. Key points on global dynamics:

    • Sheer user growth overseas: Meta’s family of apps is still adding users worldwide, especially in Asia-Pacific, Africa, and other emerging regions. As of early 2025, 3.43 billion people use at least one Meta app each day (Family DAP), an increase of 6% year-over-yearreuters.com. Monthly active users on Facebook hit ~3.08 billion in 2024thesocialshepherd.com (Instagram and WhatsApp add even more on top). Most of the new users are outside the U.S. Even if an average user in, say, India spends less time or sees fewer ads than an average American user, the volume of new users helps drive up total ad impressions. In Q4 2024, for example, ad impressions delivered across Meta’s apps rose 6% overallfifthperson.com – primarily driven by usage growth in Asia-Pacific (APAC). More people coming online and using Meta in populous countries like India, Indonesia, and Brazil directly translates into more ad views globally.
    • High growth in ad revenue from non-U.S. regions: Advertisers in emerging markets are also ramping up spending on Meta as those digital ad ecosystems mature. Meta’s financials show faster ad revenue growth internationally than in its home market. In Q2 2024, Meta’s worldwide ad revenue was up 22% YoY, but U.S. & Canada ad revenue was up a lesser 17%sensortower.com – implying regions like APAC, Latin America, and Europe grew well above 20%. Indeed, in some quarters Europe and “Rest of World” (Latin America, Africa, etc.) saw 30%+ year-over-year ad revenue growthsensortower.com as advertisers in those regions increased their Meta budgets. By contrast, North America’s ad revenue growth was in the teens. This means an increasing share of Meta’s incremental revenue is coming from outside the U.S. For instance, Asia-Pacific ad demand (especially from e-commerce and gaming advertisers) was very strong in 2024, helping boost pricing and fill more impressionss21.q4cdn.com. Meta’s global diversification has thus mitigated the impact of any stagnation in U.S. user engagement – even if Facebook usage is flat in the U.S., the company can still grow ad sales by expanding in markets where Facebook/Instagram usage is still rising.
    • Majority of revenue now international: Meta’s monetization of its international user base has improved over time, to the point that the majority of ad revenue now comes from outside the U.S.. In 2024, roughly $72 billion of Meta’s ad revenue (about 44%) was generated in the U.S. & Canada, while the remaining ~56% came from other regionsbusinessofapps.com. (Notably, North America accounts for only ~9% of Meta’s usersbusinessofapps.com, but yields a high ARPU; still, non-North America collectively contributes more dollars now.) This global revenue mix means Meta’s growth is less beholden to any single region’s engagement levels. Even as North American usage is mature, there are billions of users in APAC and other areas where advertising on Meta is still gaining traction. In markets like India, where Facebook’s user base grew ~16% from 2022 to 2024 (to over 400 million MAUs)statista.com, Meta is just beginning to tap into the ad budgets of local businesses and global brands targeting those users. Increasing internet penetration and digital ad spend in emerging economies funnel directly into Meta’s ad revenue.
    • Lower ARPU offset by volume and growth: It’s true that average revenue per user (ARPU) is lower in non-U.S. markets, and engagement per user may also be less in developing regions. However, the gap is narrowing. As smartphones become ubiquitous and e-commerce grows globally, advertisers from all industries (CPG, fintech, entertainment, etc.) are pouring money into Meta to reach these new online consumers. Meta’s ability to localize ads (supporting local languages, local businesses advertising on WhatsApp, etc.) has improved, which helps monetize international users more effectively. The strategy of focusing on “monetizing engagement over time”warc.com pays off here – Meta often grows user engagement first in a market (sometimes with years of user growth with minimal ads), then gradually increases ad load or ARPU. We saw this with Instagram: between 2015 and 2025, Instagram’s U.S. user base grew 142%, but its ad revenue grew many times that, as ARPU climbed to surpass Facebook’s by 2019emarketer.com. A similar dynamic is occurring in international markets now. Thus, even if engagement per user is not skyrocketing, Meta is better at monetizing each user each year – especially outside the U.S. – leading to overall revenue gains.

    In summary, Meta’s global expansion ensures that “flat” engagement in one region doesn’t translate to flat revenue. The company’s reach into every continent provides a growth engine: new users and new advertisers coming on board worldwide. Non-U.S. markets both expand the user base and increasingly contribute to ad revenue growth, offsetting any engagement fatigue in core Western markets.

    5. Advertisers: Overlooking Engagement Trends or Adapting to Them?

    A critical part of this puzzle is how advertisers react to reported engagement declines. Are they ignoring these warning signs, or actively adjusting their strategies? The evidence suggests advertisers are aware of engagement shifts but remain confident in Meta – largely because they can adapt their advertising tactics within the platform to still achieve results. Key insights:

    • Outcomes matter more than engagement metrics: Advertisers ultimately care about their own marketing objectives (sales leads, app installs, brand lift) more than they do about Facebook’s internal engagement stats. As long as campaigns on Meta continue to deliver strong outcomes, advertisers will keep spending, even if time spent per user is down. Meta’s Q1 2025 results underscore this – ad revenue rose 16% YoYcreativestrategies.com at a time when some engagement indicators (e.g. Facebook friend content consumption) were down. This implies advertisers were still getting value. Analysts have noted that Meta’s unmatched scale (3.4B daily users) makes it a “go-to ad venue” for marketerscreativestrategies.com. From an advertiser’s perspective, a modest decline in average user session length doesn’t outweigh the fact that almost everyone is still on Facebook/Instagram. Advertisers appear to be overlooking soft engagement trends because Meta’s platforms remain one of the only ways to reach billions of people with sophisticated targeting. In short, so long as Meta ads yield a positive ROI, advertisers aren’t overly concerned with whether users spent 5% less time on the app this year.
    • Adaptation within Meta’s ecosystem: Advertisers have proven very nimble in adapting to how users use Meta, rather than abandoning it. When engagement shifts, they shift their ad placements accordingly. For example, as users devote more attention to Reels videos and less to the news feed, advertisers have expanded into Reels ads (as discussed, 3 in 4 advertisers now run Reels ads)reuters.com. This flexibility means advertisers can follow the user journey within Meta’s walled garden. If engagement declines in one format, they increase focus on another. Zuckerberg gave the example that when Stories first gained popularity, advertisers eventually moved budget there from feed; the same pattern is happening with Reelsreuters.com. The ability to serve ads across multiple surfaces (Feed, Stories, Reels, Messenger, etc.) insulates advertisers from platform changes – they don’t have to leave Meta to find the eyeballs, they just redistribute how they buy inside Meta. Thus, advertisers are effectively mitigating the engagement issue by aligning their campaigns with whatever part of Facebook/Instagram is most engaging at the moment. This adaptability has been critical in Meta retaining ad dollars. Rather than panic about TikTok stealing user time, advertisers waited to see Meta offer a competing format (Reels) and then swiftly adopted it, thereby neutralizing the risk of lost reach.
    • Selective attention to engagement metrics: It’s also worth noting that “user engagement” is multifaceted, and not all declines are relevant to advertisers. For instance, one reported trend is that people spend less time on content from friends and more on algorithmic content. From a brand’s perspective, that shift might even be positive (users paying more attention to public content where ads live, versus private friend updates). In fact, Meta has stopped emphasizing time-spent metrics publicly, and advertisers mostly focus on ad performance metrics. Mark Zuckerberg’s acknowledgment that Meta’s share of social media time has declined with TikTok’s risesocialmediatoday.com was a notable public admission, but advertisers seem to have taken it in stride. Part of the reason is that no single competitor has significantly eroded Meta’s advertising efficacy yet. TikTok, for example, is growing but still smaller in ads (estimated ~$13B revenue in 2023 vs. Meta’s $117B in just the first nine months of 2024). Advertisers typically trial new platforms but often keep the bulk of budgets on proven ones. So while engagement trends are monitored, advertisers appear to be betting that Meta’s innovations (AI, Reels, etc.) will keep users sufficiently engaged. Many advertisers also discount some engagement stats as short-term fluctuations or demographic specifics that don’t affect their particular campaigns.
    • Confidence in Meta’s countermeasures: Advertisers take cues from Meta’s leadership on how the company is addressing engagement challenges. When Zuckerberg outlines plans to improve content discovery with AI or sees Reels as key to winning back young users, advertisers gain confidence that Meta is proactively working to increase engagement again. The fact that Meta’s leadership prioritized “increasing user engagement… before turning to monetization” of new experiencesreuters.com shows a long-term commitment to keeping the user base active. Advertisers are thus willing to stick with Meta, trusting that these efforts (e.g. the pivot to video, AI chatbots to spur interaction, etc.) will bear fruit. Furthermore, the lack of a significant user exodus – Facebook is “dying” slower than predicted, still over 3 billion users – reassures advertisers that they won’t find comparable scale elsewhere. As one industry expert put it, Meta’s ad business has “proven reliability” even in tough timesreuters.com. This reliability makes advertisers tolerant of engagement dips. They assume (so far correctly) that Meta will adapt and user activity will stabilize or shift into new forms that Meta can monetize – and thus they don’t pull their budgets at the first sign of trouble.

    In summary, advertisers are neither blind to engagement trends nor alarmist – they are pragmatic. They continue to allocate large budgets to Meta because it remains essential for reaching audiences and driving results. If anything, engagement declines have prompted advertisers to become more agile in how they use Meta (embracing Reels, leveraging cross-platform ads, etc.), rather than prompting them to abandon ship. As long as Meta provides the tools to reach users effectively (which it has, via AI and new formats), advertisers appear content to maintain or even increase their spending, effectively overlooking the engagement noise in favor of the signal: marketing performance.

    6. Executive and Investor Commentary

    Meta’s leadership and financial reports have provided insight into the strategy behind sustaining ad revenue growth and how the company communicates about engagement. Comments from Meta executives and industry analysts on earnings calls reveal the deliberate approach Meta is taking:

    • Zuckerberg on AI’s role in ads: Mark Zuckerberg has repeatedly emphasized that AI is the key driver of Meta’s advertising momentum. In late 2024, he noted on an earnings call that advances in AI recommendation models had “increased engagement on Facebook Reels” significantlys21.q4cdn.com, underscoring that boosting engagement is foundational. He also explained that on the advertising side, “our ads system [can] predict who would be interested [in an ad] better than the advertisers could themselves” thanks to AIs21.q4cdn.com. This was a candid way to assure investors that Meta’s AI targeting makes the platform extremely effective for marketers. Zuckerberg has even described Meta’s evolving ad strategy as turning advertising into an AI-driven agent for business outcomes“If we deliver on this vision…AI will make advertising a meaningfully larger share of global GDP than it is today,” he told investorsppc.land – a bold statement reflecting confidence that AI will unlock more advertiser spend. Such commentary signals that Meta is doubling down on AI to both keep users engaged and keep ads relevant, which in turn gives investors confidence that the company can navigate engagement headwinds (with AI as the solution).
    • CFO on engagement vs. monetization strategy: Meta’s Chief Financial Officer, Susan Li, has explicitly broken down the formula for revenue growth in terms of user engagement and monetization efficiency. On an earnings call, she highlighted two primary factors driving Meta’s revenue“our ability to deliver engaging experiences for our community and our effectiveness at monetizing that engagement over time.”warc.com She noted that AI is crucial to both – it helps make the apps more engaging and also powers better ad delivery. This reflects Meta’s classic playbook: first grow or maintain engagement (e.g. get people watching Reels), then monetize that engagement more and more effectively (e.g. improve Reels ads yield). Li has frequently updated investors on the monetization gap between new formats and old ones. For example, she acknowledged that Reels was still less monetized than Feed/Stories, but closing the gap was a priorityreuters.com. By Q4 2024, she reported ad prices rising 14% on average, partly due to improved ad performance, even as impressions grew 6%fifthperson.com. That indicates Meta was successfully monetizing existing engagement better – a point she tied to investments in AI and infrastructure. Investor takeaway: Meta’s finance chief is effectively saying “we know engagement isn’t growing like before, but we are making more money per unit of engagement”, and that’s how revenue keeps rising. This clear messaging has kept Wall Street on board with Meta’s strategy.
    • Analysts on advertiser demand and Meta’s position: Industry analysts and observers on earnings calls have provided context that supports why Meta’s ad revenue can grow amid engagement questions. For example, one eMarketer principal analyst noted in December 2024, “As other social platforms flood their services with more ad placements, Meta is focused on making its ads more efficient, primarily through AI.”emarketer.com Reels was cited as a major driver of Instagram’s growth in that comment. This suggests that outsiders see Meta taking a quality-over-quantity approach with ads, which tends to win long-term advertiser dollars. Another analyst remarked that Meta’s huge user base makes it uniquely resilient: during a period when marketers were wary of the economy, Meta’s scale and reliability meant it “rode strong advertising performance” to beat revenue expectationscreativestrategies.com. Advertisers consolidating spend to the biggest platforms played to Meta’s advantage. Additionally, Reuters reported an analyst observation that Meta’s “proven advertising reliability means it stands to gain” even when companies tighten ad budgets elsewherereuters.com. These external commentaries echo the themes that Meta’s executives push – namely, that Meta remains a must-buy for advertisers, and its focus on AI-driven efficiency is yielding tangible revenue benefits.
    • Meta’s guidance and engagement commentary: In investor communications, Meta’s management has also addressed the engagement concern directly at times, aiming to set expectations. Zuckerberg has stated that for newer initiatives (like the AI chatbot features or potentially Threads), Meta will prioritize user growth and engagement “for the next year” before ramping up monetizationreuters.com. This kind of statement is meant to reassure investors that the company is mindful of not squeezing the golden goose too soon. It also implies Meta believes it can increase engagement through product improvements given some time, and that monetization will follow naturally. Such commentary is essentially saying: short-term, we focus on keeping users interested; long-term, we’ll make money off those users. This patient approach was validated by past successes (e.g., Instagram Stories was unmonetized at launch, then became a major ad vehicle). Investors, hearing this, can tolerate flat engagement in the immediate term if they trust Meta’s plan to reignite engagement. And indeed, by late 2024, Meta was reporting some turnaround in engagement: new AI recommendations and video features were boosting time spent on Instagram and Facebook againcreativestrategies.com. That narrative – “we fixed the feed to show more Reels and it’s increasing time spent” – has been emphasized to alleviate concern that TikTok had permanently stolen growth. In essence, Meta uses its earnings calls not just to report numbers but to convince stakeholders that engagement is under control or will be won back, thanks to strategic product moves, and that meanwhile ad business is thriving.

    In conclusion, executive and investor commentary underline a coherent picture: Meta acknowledges engagement challenges but presents a strategy (largely AI-powered and format innovation) to overcome them, and consistently highlights the ongoing strength of the ad business. This transparency and strategy have kept investors optimistic. Meta’s stock performance rebounded in 2024 as the company demonstrated it could navigate Apple’s privacy changes, cut costs, and still grow revenue double-digits with AI and Reels at the forefrontcreativestrategies.comfifthperson.com. The confidence from the C-suite, backed by real financial results, illustrates why Meta’s advertising revenue not only continues to grow in 2024–25 but accelerates, seemingly defying the headwinds of user engagement declines on its core social platforms.

    Conclusion:Meta’s ability to grow advertising revenue in 2024–2025, despite flattening engagement on Facebook/Instagram, boils down to strategic execution on multiple fronts. Advanced AI and machine learning are extracting more value from each user and each ad (better targeting, higher conversion rates), which keeps advertisers spending. Advertisers themselves have shifted toward a performance-driven mindset and have shown loyalty to Meta – adapting their campaigns across Facebook and Instagram’s evolving formats rather than cutting budgets. Meanwhile, new engagement surfaces like Reels and Stories have given users fresh ways to spend time on Meta’s apps, and Meta has monetized these vigorously to offset any decline in legacy feeds. The company’s expansive global user base ensures that growth continues in regions where engagement is still climbing, balancing out saturation in the U.S. Ultimately, advertisers appear to be “looking past” engagement dips, trusting Meta’s massive reach and AI-enhanced ad platform to deliver results. Meta’s leadership has reinforced this trust by openly addressing challenges and investing heavily in solutions (AI, product innovation). All of these factors combine into a robust strategic story: Meta has effectively decoupled revenue growth from the need for ever-increasing user engagement by improving the quality of ad delivery and expanding what “engagement” means (to new formats and markets). This strategy has so far proven successful, as evidenced by Meta’s strong 2024 financials, and provides a template for how the company can continue to thrive even in a world where the Facebook/Instagram of old are no longer the shiny new thing

  • Meta and platfrom names

    Meta’s Strengths (Why It Could Win)

    • Top-tier AI talent (FAIR lab, Yann LeCun, Llama models)
    • Open-source strategy (LLaMA family)—widely adopted, shaping the open-source ecosystem
    • Massive infrastructure (tens of thousands of GPUs, custom silicon plans)
    • Ownership of distribution (Facebook, Instagram, WhatsApp) gives it a natural edge for deploying AI at scale

    🚧 Meta’s Challenges

    • No dominant cloud platform (unlike Azure, GCP, AWS)
    • No enterprise software footprint (unlike Microsoft or Salesforce)
    • Monetization uncertainty for open-source AI (vs. closed-source subscription models)
    • Intense competition from Google (Gemini), OpenAI, Anthropic, etc.

    🔮 Verdict:

    Meta is well-positioned to win in open-source AI influence and consumer-facing AI integration, but it’s less likely to dominate enterprise AI or cloud AI infrastructure, where Microsoft, AWS, and Google are ahead.

    Google and Amazon will benefit from generative ads, but I expect the effect will be the most powerful at the top of the funnel where Meta’s advertising operates, as opposed to the bottom-of-the-funnel search ads where Amazon and Google make most of their money.

    Moreover, there is that long tail I mentioned above: one of the challenges for Meta in moving from text (Feed) to images (Stories) to video (Reels) is that effective creative becomes more difficult to execute, especially if you want multiple variations.

    Meta has devoted a lot of resources over the years to tooling to help advertisers make effective ads, much of which will be obviated by generative AI. This, by extension, will give long tail advertisers more access to more inventory, which will increase demand and ultimately increase prices.

    There is one more channel that is exclusive to Meta: text-to-message ads. These are ads where the conversion event is initiating a chat with an advertiser, an e-commerce channel that is particularly popular in Asia. The distinguishing factor in the markets where these ads are taking off is low labor costs,

    And then the one that I think is going to have the fastest direct business loop is going to be around helping people interact with businesses. You can imagine a world on this where over time, every business has as an AI agent that basically people can message and interact with. And it’s going to take some time to get there, right? I mean, this is going to be a long road to build that out. But I think that, that’s going to improve a lot of the interactions that people have with businesses as well as if that does work, it should alleviate one of the biggest issues that we’re currently having around messaging monetization is that in order for a person to interact with a business, it’s quite human labor-intensive for a person to be on the other side of that interaction, which is one of the reasons why we’ve seen this take off in some countries where the cost of labor is relatively low. But you can imagine in a world where every business has an AI agent, that we can see the kind of success that we’re seeing in Thailand or Vietnam with business messaging could kind of spread everywhere. And I think that’s quite exciting.

    Both of these use cases — generative ads and click-to-message AI agents — are great examples as to why it makes sense for Meta to invest in its Llama models and make them open(ish): more and better AI means more and better creative and more and better agents, all of which can be monetized via advertising.

    Image 35
    Image 36

    1. General Tech & Business Trends

    • Stratechery (Ben Thompson) (stratechery.com)
      • Focus: Deep dives on tech strategy (Apple, Google, Amazon, AI, cloud).
      • Why Follow?: One of the best for understanding tech business models.
    • The Information (theinformation.com)
      • Focus: Premium tech/business reporting with scoops on startups and Big Tech.
      • Why Follow?: High-quality investigative journalism (paywall).
    • Protocol (now part of Politico) (politico.com/protocol)
      • Focus: Enterprise tech, cloud, and policy impacts on tech.
      • Why Follow?: Good for regulatory and infrastructure trends.
    • Axios Pro Rata & Axios Tech (axios.com)
      • Focus: Quick, sharp insights on tech deals, startups, and policy.
      • Why Follow?: Great for daily tech business briefings.

    2. Semiconductors, AI & Hardware

    • SemiAnalysis (semianalysis.com)
      • Focus: Deep semiconductor, AI chip, and supply chain analysis.
      • Why Follow?: One of the best for advanced chip tech (subscription-based).
    • AnandTech (anandtech.com)
      • Focus: CPU/GPU deep dives, data center hardware.
      • Why Follow?: Technical benchmarks and architecture breakdowns.
    • EE Times (eetimes.com)
      • Focus: Semiconductor and electronics engineering trends.
      • Why Follow?: Good for hardware innovation insights.

    3. Cloud, Enterprise & AI

    • Enterprise AI (enterpriseai.news)
      • Focus: AI adoption in enterprises, ML infrastructure.
      • Why Follow?: Niche coverage of AI deployments.
    • Data Center Knowledge (datacenterknowledge.com)
      • Focus: Hyperscale cloud, data center trends.
      • Why Follow?: Key for infrastructure investors.
    • AI Business (aibusiness.com)
      • Focus: AI applications in industry.
      • Why Follow?: Practical AI adoption case studies.

    4. Networking & Connectivity

    • Light Reading (lightreading.com)
      • Focus: Telecom, 5G, optical networking.
      • Why Follow?: Critical for networking industry trends.
    • Fierce Telecom (fiercetelecom.com)
      • Focus: Broadband, wireless, and ISP strategies.
      • Why Follow?: Good for regulatory shifts.

    5. Investor-Focused Tech Research

    • Above Avalon (Neil Cybart) (aboveavalon.com)
      • Focus: Apple ecosystem and consumer tech.
      • Why Follow?: Unique Apple-focused investment insights (paid).
    • Benedict Evans (benedictevans.com)
      • Focus: Big-picture tech trends (AI, mobile, autos).
      • Why Follow?: Great for long-term thematic investing.
    • Matthew Ball’s Essays (matthewball.vc)
      • Focus: Metaverse, gaming, media disruption.
      • Why Follow?: Deep analytical essays on future tech.

    6. News Aggregators & Real-Time Trends

    • Hacker News (news.ycombinator.com)
      • Focus: Crowdsourced tech/startup news.
      • Why Follow?: Early signals on tech shifts.
    • Techmeme (techmeme.com)
      • Focus: Tech news aggregator with smart curation.
      • Why Follow?: Best for daily headline scanning.

    Final Thoughts

    • For investors: Prioritize SemiAnalysis, Stratechery, The Information.
    • For engineers/developersAnandTech, EE Times.
    • For cloud/AI trendsEnterprise AI, Protocol.

    📰 Tech News Websites

    These are the most up-to-date sources for breaking news and industry developments:

    1. TechCrunch – Startups, funding, big tech moves
      https://techcrunch.com
    2. The Verge – Tech culture, product reviews, gadgets
      https://www.theverge.com
    3. Wired – Broader tech and science stories
      https://www.wired.com
    4. Ars Technica – Deep dives into hardware, software, policy
      https://arstechnica.com

    📬 Newsletters for Trends and Analysis

    Concise, often curated by experts:

    1. Benedict Evans – Weekly analysis of tech and strategy
      https://www.ben-evans.com/newsletter
    2. Stratechery by Ben Thompson – Sharp business/strategy insights
      https://stratechery.com
    3. The Pragmatic Engineer – Deep engineering, tech org insights
      https://newsletter.pragmaticengineer.com
    4. TLDR Newsletter – Daily brief of key tech/startup news
      https://www.tldrnewsletter.com

    📈 Trend Analysis & Market Insights

    Great for identifying broader movements and long-term shifts:

    1. CB Insights – Market maps, tech trend reports
      https://www.cbinsights.com/research
    2. Gartner & Forrester – Enterprise-level tech forecasting
    3. PitchBook / Crunchbase – Startup activity and funding trends
      https://www.crunchbase.com

    🌐 Community & Crowd-Sourced Trendspotting

    Follow what developers, entrepreneurs, and early adopters are saying:

    1. Hacker News (Y Combinator) – Tech and startup discussions
      https://news.ycombinator.com
    2. Reddit – Subreddits like r/technology, r/Futurology, r/MachineLearning
      https://www.reddit.com
    3. Product Hunt – New product launches, early trend signals
      https://www.producthunt.com

    📊 Tools to Watch What’s Gaining Traction

    Helpful for identifying rising technologies or companies:

    1. Google Trends – Track keyword popularity over time
      https://trends.google.com
    2. Exploding Topics – Curates fast-growing topics across tech/business
      https://explodingtopics.com
    AspectMeta (LLaMA)Microsoft / OpenAIGoogle (Gemini)
    AI Research TalentTop-tier (FAIR, LeCun)Strong (OpenAI + MSR)Strong (DeepMind + Brain)
    Model StrengthLLaMA 3, strong open modelsGPT-4, ChatGPT dominanceGemini 1.5+, competitive
    Open vs ClosedOpen-sourceMostly closedMostly closed
    Cloud InfrastructureNo public cloudAzure + OpenAI APIsGCP + TPUs
    Enterprise Software ReachWeakVery strong (Office, Copilot, Dynamics)Moderate (Workspace, Cloud AI tools)
    Consumer IntegrationStrong (Instagram, FB, WhatsApp)ModerateVery strong (Search, YouTube, Android)
    Hardware InvestmentBuilding custom silicon, heavy GPU spendOpenAI clusters on Azure; growing hardware partnershipsTPUs, advanced infra
    Revenue Model MaturityEmergingMature APIs + SaaS + Office bundlesAdvanced but fragmented
    Dev Ecosystem InfluenceGrowing fast via LLaMAStrong (Copilot, GitHub, Azure AI Studio)Strong (TensorFlow, Android, Colab)
  • Third-Party Cookies

    The Decline of Third-Party Cookies and Its Impact on Online Advertising

    What Are Cookies and Types
    Cookies are small text files stored on a user’s device by a web browser. They are used to remember information about a user, such as login status, preferences, or browsing activity.
    Types of Cookies:
    – First-Party Cookies: Set by the website being visited.
    – Third-Party Cookies: Set by a domain other than the one the user is visiting.
    – Session Cookies: Deleted when the browser is closed.
    – Persistent Cookies: Remain until a set expiration date.
    – Necessary, Functional, Performance, Targeting, and Social Media Cookies: Based on purpose.

    How Third-Party Cookies Work
    When you visit a website, it can load third-party resources like ads, social plugins, or analytics scripts. These third-party services can set cookies via their own domains, thus tracking you across different websites.
    Yes, these third parties often have contractual terms (not direct contracts) with site owners, such as terms of service or data processing agreements (DPAs).

    Do Google and Meta Have Agreements with All Websites?
    No, Google and Meta do not have individual agreements with every site. However, they offer widely-used services (Google Analytics, Facebook Pixel, etc.), and site owners agree to standard terms, enabling third-party tracking.
    Google and Meta Tracking Ecosystem
    Google uses tools like Google Analytics, AdSense, and DoubleClick. Meta uses Facebook Pixel and social plugins. When these tools are embedded in websites, they can set cookies and track users.
    – Google uses cookies like _ga, IDE, NID
    – Meta uses cookies like fr, _fbp
    They can recognize users across websites and deliver targeted ads or measure conversions.
    Do First-Party Websites Share Data with Third Parties?
    Yes, first-party data can be shared with third parties, either automatically via embedded scripts (e.g., Google Ads) or manually via uploads and APIs.
    Sharing is often allowed under legal frameworks like GDPR if user consent is obtained.
    Major Concerns with Third-Party Cookies
    – Privacy Invasion
    – Lack of Transparency
    – Data Security & Misuse
    – Consent Fatigue
    – Loss of User Control
    – Legal & Regulatory Risk
    – Sensitive Profiling
    – Ad Fraud
    – Big Tech Consolidation
    Why Third-Party Cookies Get More Attention Than First-Party Sharing
    Because third-party cookies enable cross-site tracking without user knowledge, they are seen as more invasive and are a primary focus of privacy regulations.
    First-party sharing, while not rare, is more visible, controllable, and legally contained.
    Commercial Reasons – Why It’s Not the End of Tracking
    The $1.4 trillion ad industry depends on personalized targeting. Instead of ending tracking, the ecosystem is shifting to new tools:
    – First-party data strategies
    – Server-side tracking (e.g., Meta CAPI)
    – Identity solutions (e.g., UID 2.0)
    – Contextual advertising
    How Big Tech Is Managing the Decline
    – Google: Privacy Sandbox (Topics API, FLEDGE, Attribution API, Trust Tokens)
    – Meta: Conversion API, server-side tracking, on-platform signals
    – Amazon: Logged-in, first-party retail data, Amazon Ads
    – Ad Tech: UID 2.0, identity graphs, clean rooms
    – FLoC: Replaced by Topics API
    – Contextual Ads: Growing due to privacy safety
    – Server-Side Tracking: Major workaround
    – Identity Graphs & UID 2.0: Cross-site user linking using consented identifiers
    Detailed Overview of Privacy Sandbox APIs
    1. Topics API: Shares high-level interest categories from browser
    2. Protected Audience (FLEDGE): Retargeting via on-device auctions
    3. Attribution Reporting API: Conversion tracking without cross-site cookies
    4. Trust Token API: Bot detection without user identity
    All aim to maintain ad functionality while reducing privacy risks.
    Industry Impact of Cookie Phase-Out
    – Loss of precise behavioral targeting
    – Rise of first-party data strategies
    – Stronger walled gardens (Google, Meta, Amazon)
    – Contextual advertising resurgence
    – Attribution becomes modeled or aggregated
    – Increased complexity and cost
    – Regulatory scrutiny continues
    – Less precise targeting and attribution without cookies
    – Reduced effectiveness of arbitrage-based ads
    – Server-side tracking and clean room integration potential

    3P Cookies
    Cookies are small text files stored on a user’s device by a web browser when they visit a website. These files contain data about the user’s interaction with the site and are used to remember information such as login status, preferences, and browsing activity.
    Cookies help websites provide a more personalized and efficient user experience, but they also play a significant role in tracking and advertising.
     
    Type
    Set By
    Purpose
    Duration
    Based on Origin
     
     
     
    First-party
    Website visited
    User preferences, login, etc.
    Session or persistent
    Third-party
    External domains
    Ads, tracking, analytics
    Persistent
    Based on Duration
     
     
     
    Session
    Website
    Temporary interactions
    Until browser closes
    Persistent
    Website or third party
    Remember settings/logins
    Fixed expiration
    Based on Purpose
     
     
     
    Necessary
    Website
    Core functionality
    Varies
    Functional
    Website
    Enhance user experience
    Varies
    Performance/Analytics
    Website or third party
    Understand user behaviour
    Varies
    Advertising/Targeting
    Third party
    Personalized ads
    Varies
    Social Media
    Social platforms
    Sharing and tracking
    Varies
     
     
    How Third-Party Cookies Get Set on a Website You Visit?
    The ability of a third-party website to set cookies while you’re visiting another website hinges on how web pages are built and how third parties are integrated into them.
    Here’s a breakdown of how it works
    When you visit a website (say, example.com), that site can include resources from other domains — such as:
    Ad networks (e.g., ads.doubleclick.net)
    Social media widgets (e.g., Facebook “Like” buttons)
    Analytics tools (e.g., Google Analytics)
    Embedded videos (e.g., YouTube)
    Chatbots, fonts, CDNs, etc.
     
    When your browser loads these resources, it sends requests to the third-party servers. If those servers respond with a Set-Cookie header, your browser stores that cookie — even though you never visited that third party directly.
    So, technically, the third party isn’t setting the cookie without permission — it’s doing so because the first-party site embedded their code.
    In most commercial cases, there is a service agreement between The first-party website owner, and The third-party service provider (e.g., an ad network, analytics company).
    This includes:
    Terms of Service or SDK/API Licensing Agreements. Example: To use Google Analytics or Facebook Pixel, the site owner agrees to Google/Facebook’s terms.
    Data Processing Agreements (DPAs). Required under GDPR and similar privacy laws. Outlines how user data (including cookies) is handled between parties.
    Consent Frameworks (e.g., IAB TCF). Used to manage user consent and ensure compliant cookie behavior with privacy laws.
    In theory, third party can only set cookies if they’re embedded into the site’s code — which usually doesn’t happen without some form of agreement. However, there are malicious or negligent cases where:
    Sites unknowingly include third-party scripts (e.g., from infected plugins).
    Shadow tracking occurs using hidden pixel tags or scripts.
     
    These are generally considered privacy violations, and major browsers, ad blockers, and privacy laws (like GDPR, CCPA) aim to crack down on them.
     
    Do First-Party Websites Share First-Party Data with Third Parties?
    Yes – The first-party data often becomes third-party data through tool integration.

    1. Via Embedded Third-Party Scripts (Automatic Sharing)
    When a first-party site uses tools like Google Analytics, Facebook Pixel, or AdSense, they’re already sending data to third parties.
    Even though the site collects the data as “first-party,” the scripts transmit:
    Page views
    Click events
    Browser info
    IP address
    Possibly personal data (if not anonymized)

    2. Via Backend Data Sharing (Manual or API-based)
    A website might export or share its user data with third parties like:
    Ad tech platforms
    Data brokers
    Business partners
    CRM or marketing tools (e.g., Salesforce, HubSpot)
    They can do this by:
    Uploading email lists or conversion events
    Using APIs to sync user data
    Sharing hashed identifiers (e.g., email or phone) for matching in ad platforms
    Example: An e-commerce store uploads purchase data to Facebook for conversion tracking or lookalike audience targeting.
    Is This Legal for 1st party websites to share data with third parties? Under GDPR, CCPA, etc consent must be explicit for data to be shared with third parties for marketing or analytics. Sites must list what data they collect; who they share it with and why they share it.
    First-party data can also be shared with third parties, and in fact, it’s becoming more valuable than ever in the post-cookie world. So, why is the focus — or fuss — still on third-party cookies?
    They Enable Unseen Cross-Site Tracking. Third-party cookies track users across unrelated websites without direct user interaction or awareness.
    No Direct Relationship With Users. First-party cookies are set by the site you’re actually visiting. There’s a direct interaction and implied trust. Third-party cookies come from unknown entities (ad tech firms, trackers, data brokers), and users have no relationship with them.
    Regulators Draw a Clear Line. Laws like GDPR and ePrivacy Directive (EU), and CPRA (California) treat third-party data as more sensitive. Because third-party cookies leak data to other domains, regulators see them as less controllable and riskier. That’s why consent banners specifically mention third-party cookies — they are considered inherently problematic.
    Why Isn’t First-Party Sharing as Controversial?
    It’s more transparent and contained
    The data is collected by the site you’re visiting.
    Sites are expected to disclose any data sharing in privacy policies.
    Sharing often happens through explicit business partnerships or server-to-server APIs (e.g., uploading hashed emails to Facebook).
    It’s easier to control and audit. First-party sharing is generally easier to:
    Log
    Secure
    Justify legally (e.g., based on user consent or contract)
    What’s Happening Now?
    Third-party cookies are being deprecated (Google Chrome plans to phase them out fully).
    As a result, first-party data is becoming the new “gold” — and scrutiny of how it’s shared is increasing.
    Tools like server-side tagging, Conversion APIs, and identity graphs are replacing third-party cookie functionality — often with less user visibility, not more.
    First-party data sharing is not rare, and it’s not being ignored. It’s just more tightly coupled to site responsibility and less inherently sneaky than third-party cookies. Is First-Party Sharing Rare? No. Is It Ignored? Also No — but it’s regulated differently.
    Factor
    First-Party Sharing
    Third-Party Cookies
    Common?
    ✅ Very
    ✅ Very
    User control?
    🟡 Sometimes
    ❌ Often none
    Transparency?
    🟡 Depends on site
    ❌ Often none
    Legal focus?
    🟡 Increasing
    🔥 High-priority target
    Public awareness?
    🟡 Low
    🔥 High concern
     
    3P Cookies and the role in Online Advertising
    Impact on global advertising industry
    The global digital advertising industry, valued at over $1.4 trillion, relies heavily on behavioural data — and third-party cookies have historically been the backbone of:
    Targeted advertising
    Retargeting (e.g., “you forgot something in your cart” ads)
    Attribution modelling (which ad led to a sale)
    Real-time bidding in programmatic advertising
    Targeted Advertising:
    Advertisers use third-party cookies to track users across websites and build profiles based on browsing habits, interests, and demographics.
    This allows for personalized ads, which tend to perform better than generic ones.
    Retargeting Campaigns:
    If a user visits an e-commerce site but doesn’t make a purchase, cookies allow advertisers to “follow” that user with ads for the same or similar products on other sites.
    Attribution Tracking:
    Advertisers use cookies to determine which ads led to conversions (sales, sign-ups, etc.), improving ad campaign optimization and budget allocation.
    Audience Segmentation:
    Cookies help group users into segments for more efficient targeting (e.g., frequent travellers, sports fans).
    Key concerns: Negative Impacts and Criticisms
    Privacy Concerns: Third-party cookies are often seen as intrusive, tracking users without their explicit consent. This has led to growing backlash and calls for stricter data privacy regulations.
    Security Risks: Cookies can potentially be exploited for malicious purposes, including cross-site tracking and data leakage.
    Poor User Experience: Over-personalization or retargeting fatigue can annoy users, who may see the same ads repeatedly.
     
    Role of larger Tech firms
    Dominance of large Tech firms.
    Google, Meta, and other large tech firms  – their presence across the web is widespread due to the services they provide.
    Ubiquity of Their Embedded Services. Millions of websites voluntarily integrate services from Google (e.g., Google Analytics, AdSense, DoubleClick) or Meta (e.g., Facebook Pixel, Like/Share buttons). When a website includes these services, it also includes scripts from Google or Meta servers. These scripts can set third-party cookies and track user behaviour across websites.
    Overall
     
    Tool
    Purpose
    Google
    Google Analytics, AdSense, DoubleClick, reCAPTCHA, Google Fonts
    Meta (Facebook)
    Facebook Pixel, Like/Share buttons, Meta Business Tools
    Amazon
    Amazon Ads, tracking pixels in affiliate programs
    Microsoft
    Bing Ads, LinkedIn tracking scripts
     
    Data Network Effects. More websites using Google/Meta → more user data → better ad targeting → more ad spend → more adoption. This creates a self-reinforcing feedback loop that makes it hard for smaller players to compete.
    They Control Key Infrastructure. 
    Google owns both the demand (advertisers) and supply (AdSense publishers) side of the ad market.
    Demand side = Advertisers (they want to buy ad space). E.g. Brands, Ad agencies, Google Ads (formerly AdWords), Google Display & Video 360 (DV360), Google’s enterprise-level Demand-Side Platform (DSP).
    Supply Side = These are publishers — websites, apps, or platforms that have a) Ad inventory (banner slots, video ad placements, etc.) b) Visitors who see the ads (i.e., user attention). E.g. News sites, blogs, platforms, publishers, forums, Google AdSense (for small publishers), Google Ad Manager (for large publishers), YouTube inventory
    Where Users (website traffic) fit In. Users are the target of the ads. Their attention, behavior, and data are what give the ad space value. But users are not considered buyers or sellers (demand and supply equation) in this market — they are more like the commodity being traded around (though that’s ethically and legally controversial).
    Google also develops the browser (Chrome) — the largest in the world — giving it enormous influence over cookie policies and APIs.
    Meta controls a massive logged-in user base, allowing it to match anonymous cookies to real identities.
     
    Google’s Dual Role
    Market Side
    What Google Owns
    Demand
    Google Ads (formerly AdWords), DV360 (DSP)
    Supply
    AdSense (for small publishers), Ad Manager (for large publishers), YouTube inventory
    Exchange
    Google Ad Exchange (connects buyers and sellers)
    Measurement
    Google Analytics, Campaign Manager
    Google owns platforms across both supply and demand, giving it market dominance. This end-to-end control has led to antitrust scrutiny, because 1) Google can prioritize its own inventory in auctions; 2) It knows all sides of every transaction; 3) It charges fees on both ends
    Implications of This Dominance from large Tech firms
    User Privacy Risks. These companies track users on sites they don’t own. They collect data even when users don’t have accounts with them or are logged out. This results in surveillance capitalism — monetizing behavior and attention at scale.
     
    Market Consolidation. Smaller ad tech companies, publishers, and tools struggle to 1) Access similar-scale data; 2) Attract advertisers without the precision of Google/Meta. It leads to a “winner-takes-most” ecosystem where the top platforms absorb the value chain.
     
    Conflict of Interest. Google is simultaneously 1) Regulating tracking technologies (via Chrome and Privacy Sandbox); 2) Using those same technologies in its own ad business. Critics argue that privacy changes may favor Google’s walled garden (e.g., YouTube, Search ads) over open web advertising.
     
    Unequal Bargaining Power. Publishers and smaller sites are dependent on Google and Meta for 1) Traffic (search, social). 2) Monetization (ads) 3) Analytics. This gives Big Tech tremendous leverage over pricing, policies, and data use.
    Most websites do not negotiate individual agreements with Google or Meta. Instead, they agree to standard Terms of Service and Data Processing Agreements (DPAs) provided by the platforms. For example, using Google Analytics requires accepting Google’s terms and privacy policy. Facebook Pixel use is governed by Facebook’s Business Tools Terms.
    If you visit any site with Google services / Facebook Pixel this allows Google/Meta to build a behavioral profile of you.
    If multiple sites embed these same Google services, Google can recognize your browser across them. This enables cross-site tracking, user profiling, and ad targeting.
    What Happens When Cookies Go Away?
    First-Party Data Becomes Gold
    Companies with direct customer relationships (e.g., Amazon, Apple, Netflix) benefit most.
    Those dependent on third-party data suffer — especially open web publishers and small advertisers.
    Big Tech Still Wins. Google and Meta are building alternatives.
    Google Privacy Sandbox: Proposes Topics API, FLEDGE, etc., as cookie replacements.
    Meta Conversions API: Server-side tracking that bypasses browser cookie restrictions.
    Google Tracking Ecosystem
     
    Tool
    Purpose
    Google Analytics
    Tracks user behavior on a website
    Google Ads / AdSense / Ad Manager
    Delivers and tracks ad performance
    Google Tag Manager
    Manages other tracking scripts
    DoubleClick / gtag.js
    Tracks ad impressions, clicks, conversions
     
    Meta Tracking Ecosystem
     
    Tool
    Purpose
    Facebook Pixel
    Tracks conversions and user behavior
    Facebook Login SDK
    Enables logins and collects user info
    Like/Share Buttons
    Collect user interaction data
    Meta Business Tools
    Includes APIs and Pixel integrations
     

    What are major concerns over use of Third Party Cookies
    The use of third-party cookies has triggered widespread concern from regulators, privacy advocates, and even browser developers. Here are the major concerns,
    Privacy Invasion. Third-party cookies track users across multiple websites without them fully understanding or consenting.
    Lack of Transparency. Many websites don’t clearly disclose what third-party trackers are present. Users often don’t know who is tracking them or why, and no direct relationship exists between users and most third parties collecting the data.
    Data Security and Misuse.
    They create detailed behavioural profiles 1) What you read; 2) What you buy 3) What sites you visit and when.
    These profiles are often used for targeted advertising or sold to data brokers. Third-party data can be 1) Sold; 2) Leaked in data breaches;
    Combined with other datasets for re-identification (linking back to real identities. Your anonymous browsing history can become personally identifiable, leading to unintended consequences (e.g., discrimination, manipulation).
    Consent Fatigue and Poor Compliance. Sites show cookie banners, but often:
    Use dark patterns to push users to “Accept All”.
    Don’t offer real choice (e.g., no “Reject All” button)
    Loss of User Control. Most users don’t understand how to 1) View or block cookies; 2) Delete them selectively; 3) Opt out of cross-site tracking
    Regulatory Compliance Risks. GDPR (EU), CCPA/CPRA (California), and other laws require. Non-compliance = legal and financial risk with massive fines.
    Informed consent
    Transparency
    Right to opt out
    Cross-Site Profiling Without Context. Advertisers track you across unrelated sites. Sensitive interests are inferred and monetized, without your awareness or consent.
    You read a mental health article on one site and then get served ads about therapy on social media
    Opaque surveillance networks and surveillance capitalism. You can be profiled by companies you’ve never heard of, just because their trackers are embedded on multiple sites. Example: You never visit doubleclick.net, but Google tracks you across thousands of sites via that domain. This creates massive, opaque surveillance networks and surveillance capitalism — monetizing behavior and attention at scale — and that’s what regulators and privacy advocates target.
    Ad Fraud and Over-Reliance. Third-party cookies enable fraudulent ad practices (like spoofed impressions). Brands sometimes waste ad budgets targeting bots or misclassified users enabling ad fraud and inefficiencies.
    Walled Gardens and Market Concentration.
    Cookie-based adtech reinforces monopoly power and limits competition.
    Google, Meta, and other big players dominate third-party cookie infrastructure while smaller publishers or advertisers struggle to compete.
     
    Compliance & Consent
    In regions like the EU, websites must:
    Ask for user consent before loading these scripts (using CMPs like OneTrust, Cookiebot).
    Offer opt-outs and explain data use in privacy policies.
    Both Google and Meta provide Consent APIs to handle this legally.
     
    Industry Changes and the Decline of Third-Party Cookies
    As third-party cookies are phased out (especially in Google Chrome, which still dominates browser market share), tech companies are not giving up on tracking — they’re reinventing it.
    Browser Restrictions:
    Major browsers (Safari, Firefox) already block third-party cookies by default.
    Google Chrome, the most used browser, plans to phase them out completely (initially set for 2022, now delayed but still planned).
    Shift to First-Party Data:
    Companies are focusing more on collecting first-party data (data gathered directly from users through interactions on their own websites).
    Emergence of Alternatives:
    Solutions like Google’s Privacy Sandbox, FLoC (Federated Learning of Cohorts), and Topics API aim to balance privacy and advertising effectiveness.
    Contextual advertising is regaining popularity, where ads are shown based on page content rather than user behavior.
     
    The end of third-party cookies doesn’t mean the end of tracking, because the Industry Is Adapting — Not Retreating.
    Instead of killing data-driven advertising, the phase-out of third-party cookies is prompting a shift in methods, not in motives
    Replacement Tech
    What It Does
    First-party data strategies
    Brands collect and control their own data (logins, subscriptions)
    Server-side tracking
    Avoids browser restrictions by sending data directly from server to ad platforms
    Conversion APIs (Meta, Google)
    Share event data without needing browser cookies
    Identity graphs / Unified ID
    (UID 2.0)
    Anonymously link users across sites using hashed emails or device signals
    Google Privacy Sandbox
    New browser-based tracking proposals like Topics API, FLEDGE
     
    Lost with 3P Cookies
    Replacement Strategy
    Easy cross-site user tracking
    First-party data and identity graphs
    Real-time auction user profiling
    On-device processing (FLEDGE, Topics)
    Cookie-based attribution
    API-based server-to-server attribution
    Broad retargeting across web
    Contextual and cohort-based targeting
     
    Company
    Key Strategy
    Core Tools
    Google
    Replace cookies with in-browser APIs
    Privacy Sandbox, Chrome, Topics, FLEDGE
    Meta
    Shift tracking server-side, use own platforms
    Conversions API, on-platform data, AI targeting
    Amazon
    Rely on rich first-party shopper data
    Amazon Ads, Marketing Cloud
    Others (DSPs/SSPs)
    Use identity solutions and data alliances
    UID 2.0, RampID, clean rooms
    Future Outlook
                                                 .
    Greater reliance on AI and machine learning to make sense of first-party and contextual data.
    Regulatory compliance (e.g., GDPR, CCPA) will be central to all ad strategies.
    Publishers and marketers will need to innovate in how they collect and use data ethically.
    Why the Transition Is Politically Convenient.
    Regulators and Big Tech get to say “We’re improving privacy by killing third-party cookies!”. But in practice:
    The ad ecosystem continues – just more centralized and opaque.
    Walled gardens (Google, Meta, Amazon) grow stronger, because they don’t need cookies — they already control massive first-party user data.
    Commercial Reality:
    Targeted Ads Work – Behavioral ads based on user data outperform generic ones.
    Ad platforms and brands have billions at stake in maintaining personalization. So even as third-party cookies die, tracking evolves quietly in the background.
    Laws like GDPR and CPRA target third-party cookies because they’re the most visible and egregious — but they’re just one layer. Newer tools (server-side APIs, fingerprinting, identity graphs) are less visible to users, and often harder to regulate.
    So yes — the third-party cookie is going away, but tracking isn’t. It’s just going server-side, platform-side, and more invisible than ever.
    The public narrative is “privacy improvement,” but the business reality is a shift in power:
    Away from open ad tech and independent publishers
    Toward platforms that own massive first-party data (Google, Meta, Amazon)
    Some critics call this the “cookie apocalypse” but because it could consolidate control in the hands of a few dominant players.
     
    How Tech Giants Are Managing the Cookie Decline?
    Contextual Advertising – ✅ Major Comeback
    What it is: Showing ads based on the content of the page, not the user’s behavior.
    Example: Ads for running shoes on an article about marathons.
    Why it’s important: 1) Doesn’t rely on cookies or user tracking 2) Fully privacy-compliant.
    Rising fast as a privacy-safe alternative, especially for publishers outside big tech ecosystems. Modern contextual advertising uses AI/NLP to understand deeper content context (tone, sentiment, etc.).
    Server-Side Tracking – ✅ Crucial Workaround
    Moves data collection from browser to server, bypassing:
    Ad blockers
    ITP (Safari)
    Cookie consent banners
    Platform
    Server-Side Solution
    Meta
    Conversions API
    Google
    Enhanced Conversions, Server-Side GTM
    Others
    Direct API integrations with CDPs (e.g., Segment, Tealium)
    Identity Graphs – ✅ Critical Infrastructure
    Connect user data across devices and platforms using a) Logins b) Hashed emails c) Phone numbers; d) IP/device fingerprinting
    Use Cases a) Personalized advertising; b) Frequency capping; c) Attribution without cookies
    Example platforms: LiveRamp, Neustar, Oracle BlueKai
    Often operate behind the scenes, and users rarely know they exist.
    Unified ID 2.0 (UID 2.0) – ✅ Next-Gen Identifier
    Developed by The Trade Desk as an open-source, cookie alternative.
    Uses hashed email addresses collected with user consent.
    Maintains cross-site tracking while offering transparency and opt-outs.
    Adoption:
    Supported by publishers, SSPs, DSPs
    Requires user login/identity to work
    Growing, but limited by lack of universal adoption
    Seen as a “bridge” between third-party cookies and true privacy solutions.

    Summary Table: Strategies Replacing 3rd-Party Cookies
    Strategy
    What It Does
    Privacy-Friendly?
    Controlled By
    Topics API
    Interest-based targeting in-browser
    🟡 Partially
    Google
    FLoC
    Cohort-based targeting
    ❌ Abandoned
    Google
    Contextual Ads
    Page-based targeting
    ✅ Yes
    Publishers / Ad tech
    Server-Side Tracking
    Moves tracking to servers
    ❌ Less transparent
    Brands / Platforms
    Identity Graphs
    Cross-device/user linking
    ❌ Risky if opaque
    Data brokers, platforms
    UID 2.0
    Email-based identity for ads
    🟡 More transparent
    The Trade Desk (open source)
    These solutions are less visible to users, often harder to opt out of, and increasingly platform-controlled. So while the death of third-party cookies is framed as a privacy victory, the truth is Tracking isn’t dying — it’s just evolving

    What each company is doing?
    Google Privacy Sandbox
    Google is replacing third-party cookies with browser-native, privacy-focused APIs – Google Privacy Sandbox, the initiative meant to replace third-party cookies in Chrome and keep ad targeting and measurement alive.
    API
    Purpose
    Replaces
    Topics API
    Targets users based on broad, recent interests (e.g., “Fitness”)
    Behavioral tracking
    Protected Audience (FLEDGE)
    Enables on-device ad retargeting without sharing browsing history
    Retargeting via 3P cookies
    Attribution Reporting API
    Measures ad conversions without revealing user identity
    Cookie-based attribution
    Trust Token API
    Differentiates bots from real users without tracking
    Anti-fraud cookies
    Google is pushing this as a “privacy-preserving” alternative, but:
    It still enables user profiling (just with less granularity).
    Google controls the entire framework (Chrome, Ads, and the Sandbox).
    FLoC (Federated Learning of Cohorts) – ❌ Abandoned
    FLoC was Google’s early Privacy Sandbox proposal to group users into “cohorts” based on browsing behaviour.
    Google pulled the plug on its Federated Learning of Cohorts (FLoC) project.
    FLoC was created to replace third-party cookies (which track individual users’ behavior across the web) by grouping users into ‘cohorts’ in accordance with their interests.
    In lieu of FLoC, Google introduced Topics. Topics takes a relatively different approach. Instead of lumping users together, Topics enables a user’s browser to learn about them on an individual level based on their browsing behaviors.

    Topics API (Replaces interest-based targeting)
    🔧 What It Does:
    Assigns users broad interest categories (e.g., “Fitness”, “Autos & Vehicles”) based on their recent browsing history.
    Advertisers can use this info to serve relevant ads, but without accessing your full browsing history.
    🧠 How It Works:
    Chrome identifies topics from sites you visit (only those that opt in).
    The browser stores up to 5 topics per week, kept for 3 weeks.
    When a site calls for an ad, Chrome shares up to 3 topics with the site and ad partners.
    🆚 Difference from 3rd-Party Cookies:
    Third-Party Cookies
    Topics API
    Track users across many sites
    Only share high-level interest categories
    Enables fine-grained behavioral profiling
    Limits exposure to broad, rotating topics
    Stored server-side by ad platforms
    Stored locally in the browser
    ✅ Pros:
    No persistent identifiers or cross-site IDs
    More transparent and user-controllable
    Interest data stays in the browser
    ⚠️ Privacy Concerns:
    Still based on behavioral history — which some see as a privacy risk
    Potential for re-identification via fingerprinting when combined with other signals
    Limited granularity may reduce ad relevance

    Protected Audience API (FLEDGE) (Replaces retargeting)
    https://privacysandbox.google.com/private-advertising/protected-audience
    🔧 What It Does:
    The Protected Audience API enables on-device auctions by the browser, to choose relevant ads from websites the user has previously visited.
    Allows retargeting (showing you ads based on previous visits to a product) without sharing your browsing history with ad platforms.
    🧠 How It Works:
    When you visit a site (e.g., add shoes to cart), your browser stores that data in a “custom audience”.
    Later, when you visit another site, the browser runs an on-device auction to select a relevant ad from that audience.
    No browsing data leaves the device.
    🆚 Difference from 3rd-Party Cookies:
    Third-Party Cookies
    Protected Audience API
    Retargeting based on cross-site tracking via ad networks
    Retargeting happens inside the browser using local data
    Centralized tracking servers
    Decentralized, on-device processing
    Broad visibility into user behavior
    Each party only sees what the browser lets them see
    ✅ Pros:
    Ad targeting without exposing your browsing trail
    Keeps sensitive user data local to the device
    Supports custom audiences without direct identity
    ⚠️ Privacy Concerns:
    Opaque to users — hard to audit or opt out of audience definitions
    On-device auctions could increase fingerprinting risk
    Advertisers might try to game the system to infer user traits

    Attribution Reporting API (Replaces cookie-based conversion tracking)
    🔧 What It Does:
    Measures which ads led to conversions (e.g., a purchase or sign-up) without using cookies or cross-site identifiers.
    🧠 How It Works:
    When you click an ad, Chrome stores that event locally.
    If you later convert, the browser sends a limited, anonymized report back to the advertiser.
    Supports event-level (per-action) and aggregated reporting.
    🆚 Difference from 3rd-Party Cookies:
    Third-Party Cookies
    Attribution Reporting API
    Persistent IDs link ad clicks to purchases
    No persistent user identifiers
    Tracks across domains
    Sends delayed, aggregated, privacy-filtered reports
    Server-side tracking by platforms
    Browser controls what data is reported
    ✅ Pros:
    Preserves ad effectiveness measurement without user-level tracking
    Can’t be used to build user profiles
    ⚠️ Privacy Concerns:
    Limited attribution data may hurt small advertisers
    Complexity of implementation
    Still requires trust in browser to accurately and honestly report data

    Trust Token API (Replaces CAPTCHA / bot detection & fraud tracking)
    🔧 What It Does:
    Helps websites and ad platforms distinguish between real users and bots, without tracking individuals.
    🧠 How It Works:
    A trusted site (like a login page) can issue a “trust token” to a user’s browser. That token can be redeemed by other sites to verify that the user is legitimate. No identifying information is shared — only that the user is likely not a bot.
    🆚 Difference from 3rd-Party Cookies:
    Third-Party Cookies
    Trust Tokens
    Used for user profiling, fraud prevention, and more
    Used only to verify authenticity (is this a human?)
    Contain identifying information
    Are cryptographic, anonymous, non-linkable
    Persist across sites
    One-time use tokens, non-trackable
    ✅ Pros:
    Improves fraud detection without compromising user privacy
    Prevents abuse without needing fingerprinting or login
    ⚠️ Privacy Concerns:
    If widely adopted, could be used as a soft identifier
    Opaque to users, who may not understand how trust is assigned
    API
    Purpose
    Replaces
    User Identifiable?
    Key Privacy Risk
    Topics API
    Interest-based targeting
    Behavioral profiling
    ❌ Not directly
    Fingerprinting risk
    Protected Audience (FLEDGE)
    Retargeting ads
    Cookie-based ad IDs
    ❌ No shared ID
    On-device data misuse
    Attribution Reporting API
    Ad-to-conversion tracking
    Cross-site attribution
    ❌ No
    Limited data may reduce visibility
    Trust Token API
    Verify authenticity (not bots)
    CAPTCHAs, fraud checks
    ❌ No
    Can be misused if abused at scale


    Meta (Facebook): Going Server-Side
    Meta is losing cookie visibility due to:
    iOS App Tracking Transparency (ATT)
    Browser restrictions on third-party cookies
    Key solution: Meta Conversions API (CAPI) – Sends user interaction data from a brand’s server to Meta, bypassing browser limits.
    Meta is also investing heavily in AI-driven targeting, modeled conversions, and engaging users in Meta-owned apps (e.g., Instagram, Facebook) where tracking is easier.
    Amazon: The First-Party Data FortressAmazon never relied much on third-party cookies because:
    Users are almost always logged in
    It collects huge amounts of first-party data: searches, purchases, device use (Echo, Kindle)
    Amazon owns the entire supply chain: data, content, shopping, and ads. Amazon’s strategy is to growing Amazon Ads and building tools like Amazon Marketing Cloud for insights and measurement.
    Smaller Ad Tech Companies: Collaborate or Die
    Without cookies, smaller players can’t track across domains like they used to.
    Emerging workarounds:
    Unified ID 2.0 (by The Trade Desk): Uses hashed emails instead of cookies for identity.
    LiveRamp’s RampID: Another identity solution based on deterministic (logged-in) signals.
    Data clean rooms: Secure environments where companies can match data without exposing raw user info.
    Google Ads Data Hub
    Amazon Marketing Cloud
    Meta Advanced Analytics
    The shift away from third-party cookies and toward privacy-preserving technologies like those in Google’s Privacy Sandbox is causing a major transformation in the online advertising industry — economically, technologically, and strategically.
    Here’s a breakdown of the main impacts:
    Clip Image003
    🧨 1. Collapse of Legacy Ad Targeting Models
    Third-party cookie-based behavioral targeting is becoming obsolete.
    This disrupts:
    Cross-site user tracking
    Lookalike audiences
    Retargeting campaigns
    Ad tech firms built on cookie-based profiling (e.g., many DSPs, DMPs) are losing relevance or pivoting fast.
    📉 Impact: Shrinking effectiveness of traditional programmatic advertising, especially for small-to-mid-sized players.
    Clip Image003
    🏰 2. Strengthening of Walled Gardens
    Platforms like Google, Meta, Amazon, TikTok don’t need third-party cookies — they already collect rich, first-party user data (logins, activity, purchases).
    These companies now control:
    Identity
    Inventory (ad space)
    Attribution and analytics
    Targeting tools
    🧱 Result: Advertisers are increasingly dependent on platform ecosystems, giving Big Tech more leverage and reducing market diversity.
    Clip Image003
    📈 3. Rise of First-Party Data Strategies
    Publishers and brands are investing heavily in:
    Email collection
    Login systems
    CRM integrations
    Loyalty programs
    First-party data is becoming the new currency in advertising.
    🛠️ Tools supporting this shift:
    Server-side tagging (e.g., Google Tag Manager Server)
    Clean rooms (e.g., Amazon Marketing Cloud)
    CDPs (Customer Data Platforms like Segment, Tealium)
    Clip Image003
    🔍 4. Greater Emphasis on Contextual Advertising
    As behavioral data declines, advertisers return to contextual signals:
    Page content
    Keyword themes
    Sentiment, tone, and placement quality
    🧠 Enhanced by AI/NLP to make context targeting more effective and privacy-compliant.
    Clip Image003
    🔄 5. Shift in Attribution Models
    Without third-party cookies, multi-touch attribution (MTA) becomes less reliable.
    Advertisers now rely on:
    Aggregated conversion reporting (via APIs like Google’s)
    Modeled attribution using AI/ML
    Incrementality testing (e.g., A/B, geo splits)
    ⚖️ This means less precision, but more privacy-aligned strategies.
    Clip Image003
    💸 6. Increased Cost and Complexity
    Implementing first-party tracking, server-side APIs, clean rooms, and Privacy Sandbox tools:
    Requires engineering resources
    Increases compliance burden
    Raises cost for smaller players
    👨‍💻 Winners: Large brands with technical capabilities
    📉 Losers: Small advertisers and publishers lacking data or infrastructure
    Clip Image003
    ⚠️ 7. Regulatory Pressure and Legal Uncertainty
    Privacy laws (GDPR, CPRA, etc.) continue to evolve.
    Consent management, data minimization, and purpose limitation are now core parts of adtech operations.
    Even Google’s Privacy Sandbox has drawn antitrust scrutiny (e.g., UK’s CMA, US DOJ) for potentially reinforcing Google’s dominance.
    Area
    Impact
    Targeting
    Less precision, more reliance on contextual and 1P data
    Attribution
    Shift from individual tracking to modeled/aggregated methods
    Tech Stack
    Server-side, privacy APIs, clean rooms are rising
    Market Power
    Concentrated in large platforms with user identity
    Cost of Advertising
    Rising for smaller players, due to complexity and data gaps
    User Privacy
    Improved surface-level privacy; deeper concerns remain
     
     
    Google Privacy Sandbox
    The Google Privacy Sandbox is a comprehensive initiative to replace third-party cookies with privacy-preserving alternatives that still support online advertising, measurement, and anti-fraud. It’s Google’s answer to growing privacy demands from regulators (like GDPR, CCPA), browser competition (Safari, Firefox blocking 3P cookies), and the broader public.
    Clip Image003
    🧱 What Is the Google Privacy Sandbox?
    A set of browser-based APIs and technologies designed to:
    Protect user privacy by reducing cross-site tracking
    Allow advertisers and publishers to:
    Show relevant ads
    Measure conversions
    Detect fraud
    Maintain the economic model of the open web (which relies on ad funding)
    Clip Image003
    🧠 Why It Exists
    Third-party cookies:
    Track users across websites
    Enable precise behavioral targeting and retargeting
    Are now seen as privacy-invasive
    Google, which owns Chrome (the most used browser), announced the phase-out of third-party cookies, but wants to avoid breaking the ad industry — especially since ads fund much of the open web.
    Privacy Sandbox is Google’s attempt to “have it both ways” — user privacy and effective digital advertising.
    Clip Image003
    🧩 Core Components of the Privacy Sandbox
    Here are the main APIs, each designed to replace specific third-party cookie use cases:
    1. 🔍 Topics API (Interest-Based Targeting)
    Replaces: Behavioral tracking across sites
    The browser infers high-level topics based on your recent browsing.
    Advertisers can use these to show relevant ads.
    Topics are stored for 3 weeks and rotated.
    2. 🛡️ Protected Audience API (FLEDGE) (Retargeting)
    Replaces: Ad retargeting using 3P cookies or ad IDs
    Custom audiences are stored locally in the browser.
    When ad space loads, the browser conducts an on-device auction to choose the best ad.
    No browsing history is sent to ad networks.
    3. 📊 Attribution Reporting API (Ad Conversion Tracking)
    Replaces: Multi-touch attribution using cookies or tracking pixels
    Measures which ads led to conversions, but sends anonymized, aggregated reports.
    Avoids revealing detailed paths or personal identifiers.
    4. 🔐 Trust Token API (Bot & Fraud Prevention)
    Replaces: Tracking-based fraud systems and CAPTCHAs
    Allows trusted sites to issue non-identifiable tokens to real users.
    Other sites can redeem those tokens to verify authenticity without tracking the user.
    Clip Image003
    📈 Emerging/Experimental Components
    Privacy Budget: Limits how much identifying information a site can extract via fingerprinting.
    CHIPS: Partitioned cookies that allow stateful behavior (e.g., login) across embedded content without tracking.
    Fenced Frames: A privacy-preserving way to embed content that cannot share data with the parent page.
    Clip Image003
    🔄 How It Differs from Third-Party Cookies
    Feature
    Third-Party Cookies
    Privacy Sandbox
    Data Storage
    Cross-site tracking on servers
    Mostly local in-browser storage
    User Profile
    Detailed, persistent profiles
    High-level, ephemeral interests
    Identity
    Shared IDs across domains
    No cross-site identifiers
    User Control
    Opaque and hard to opt-out
    Chrome settings offer transparency
    Tracking
    Always on (often invisible)
    Explicitly privacy-scoped APIs
    Clip Image003
    📉 Concerns and Criticisms
    Despite its privacy claims, the Privacy Sandbox has drawn strong criticism:
    🧱 1. Market Power Concerns
    Critics argue it further entrenches Google’s dominance:
    Google controls Chrome, the ad exchange, and the ad tools.
    It gets to decide which APIs are used — essentially becoming the gatekeeper of the web’s ad system.
    🔎 2. Transparency Issues
    Many parts of the Sandbox operate in the browser, hidden from users.
    Users still won’t fully understand how their data influences ads.
    🤖 3. Fingerprinting Risks
    While cookies are removed, other identifiers (e.g., screen size, fonts, device specs) can still uniquely identify users.
    Google is trying to limit this with “Privacy Budget”, but it’s not foolproof.
    🛠️ 4. Complexity for Developers
    New APIs require significant changes to how advertisers, SSPs, DSPs, and publishers operate.
    Smaller players may struggle to adapt — while Google’s own ad products integrate seamlessly.
    Clip Image003
    ✅ Potential Benefits
    Removes the most invasive form of tracking (cross-site cookies)
    Encourages on-device processing and minimal data sharing
    Offers a privacy-respecting foundation for a sustainable ad-supported web
    Clip Image003
    🚦 Current Status (as of 2025)
    Google began testing these APIs in Chrome (some are live in stable versions).
    Full third-party cookie deprecation was delayed several times, now expected in late 2025.
    Google is working with the UK’s Competition and Markets Authority (CMA) to ensure fair competition during rollout.
    Clip Image004
     
    🧠 Summary Table
    API
    Purpose
    Replaces
    Privacy Mechanism
    Topics API
    Interest-based ads
    Behavioral tracking
    In-browser topic generation
    Protected Audience
    Retargeting
    3P cookie lists
    On-device auctions
    Attribution API
    Ad conversion
    Pixel-based tracking
    Aggregated, anonymized reports
    Trust Token
    Anti-bot detection
    Tracking-based fraud tools
    Anonymous, non-linkable tokens
    Clip Image003
    🎯 Final Thought
    Google’s Privacy Sandbox is an ambitious re-engineering of how web advertising works — aiming to be privacy-aware, ad-effective, and browser-controlled. But it’s still under intense scrutiny from:
    Regulators
    Privacy advocates
    Publishers and rival ad tech companies
    The balance between privacy, control, and open competition is still being debated — and the outcome will shape the future of the web economy.

    MVeBMZhFMZiDMZjJEZkNMZkZMZldEZlhMZmjMZnlMZqpMZrnMZstEZtxMZt9MZuBEduFMdvHMdwHMZatBaBCAgAOw==
     
    iOS App Tracking Transparency (ATT) is a critical piece of the broader privacy shift — especially in mobile advertising.
    Clip Image003
    📱 iOS App Tracking Transparency (ATT) – Explained
    🔧 What is ATT?
    Introduced by Apple in iOS 14.5 (2021), App Tracking Transparency requires explicit user permission before apps can:
    Access the IDFA (Identifier for Advertisers) — a unique device-level ID used for ad tracking.
    Track users across other apps or websites owned by different companies.
    🧱 Before ATT:
    Apps like Facebook, TikTok, or games could track users silently using IDFA.
    Advertisers could retarget users, attribute conversions, and build behavioral profiles.
    🔒 After ATT:
    Apps must show a system-level prompt:
    “Allow [App] to track your activity across other companies’ apps and websites?”
    Most users tap “Ask App Not to Track” — over 75–85% opt out.
    Clip Image003
    🚨 Impact of ATT
    For Advertisers:
    Retargeting and precise attribution became far less effective on iOS.
    Ad performance on iOS dropped dramatically in early 2021.
    Platforms lost visibility into conversion funnels.
    For Meta (Facebook):
    Estimated a $10+ billion loss in ad revenue in 2022 alone.
    Accelerated shift to server-side tracking (e.g., Meta Conversions API).
    Forced investment in AI modeling and on-platform actions (e.g., Shops, Lead Gen in-app).
    For Users:
    More awareness and control over app tracking.
    But limited visibility into server-side data sharing.
    Clip Image003
    🧠 ATT vs. Google’s Privacy Sandbox
    Feature
    Apple ATT
    Google Privacy Sandbox
    Platform
    iOS (apps)
    Chrome (web)
    Focus
    Mobile app tracking (IDFA)
    Browser-based web tracking (cookies)
    Enforcement
    User prompt + hard block
    Controlled via APIs, no user prompt yet
    Control
    User-level, immediate opt-out
    More behind-the-scenes control
    Privacy Model
    Opt-in only
    Scoped tracking with alternatives
    Market Impact
    Severe disruption to mobile ad industry
    Gradual disruption to web advertising
    Clip Image003
    🎯 Key Takeaway
    ATT was the first real-world privacy disruptor that directly hit Big Tech’s bottom line. It paved the way for:
    Google’s Privacy Sandbox
    Regulatory enforcement (GDPR/CPRA)
    Consumer awareness about tracking
    The real-world impact of Apple’s App Tracking Transparency (ATT) on the mobile advertising ecosystem, especially focusing on:
    Mobile gaming companies
    Facebook/Meta
    Ad tech platforms
    Consumers
    Apple itself
     
    1. Impact on Mobile Gaming Companies
    🚫 Loss of User-Level Attribution:
    Without access to IDFA, gaming companies lost the ability to measure which ad led to an install or in-app purchase.
    Harder to optimize return on ad spend (ROAS) or do lookalike targeting.
    📉 Drop in Ad Performance:
    User acquisition (UA) became less efficient and more expensive.
    ROAS and install rates declined sharply, especially for hyper-casual and mid-core games.
    📊 Shift in Strategy:
    Increased focus on first-party data (in-game behavior, sign-ins).
    Heavy investment in creative testing, since targeting was weakened.
    Pivot toward on-platform ad buying (e.g., TikTok, Google Ads) with more direct control.
    ✅ Winners:
    Studios with strong brand recognition or organic user bases (e.g., Supercell, Roblox).
    Companies that adapted quickly using server-side tracking or moved to Android-heavy regions.
    Clip Image003
    👥 2. Impact on Facebook / Meta
    💸 Revenue Hit:
    Meta said ATT cost it $10–13 billion in lost ad revenue in 2022 alone.
    Core product (Facebook Ads) became less effective on iOS devices.
    🔄 Shift in Infrastructure:
    Rolled out Conversions API (CAPI) for server-side event tracking.
    Invested in machine learning for modeled attribution and targeting.
    Focused on on-platform commerce (Facebook/Instagram Shops) to avoid tracking gaps.
    🧠 Strategic Impacts:
    Reoriented ad products to be less dependent on IDFA.
    Diminished Meta’s dominance in mobile performance advertising.
    Clip Image003
    🏗️ 3. Impact on Other Ad Platforms
    👇 DSPs / Performance Ad Networks:
    Snapchat and Twitter also took financial hits (Snap lost ~30% of its stock value after ATT).
    Ad networks that relied on cross-app user graphs (e.g., ironSource, Unity Ads) had to rebuild using probabilistic or contextual data.
    🧰 Response:
    Use of SKAdNetwork (Apple’s privacy-safe attribution framework) became standard — though it:
    Provides delayed, aggregated results
    Offers far less granularity than IDFA
    Clip Image003
    🧑‍💻 4. Impact on Consumers
    ✅ Gains:
    More transparency: users see a clear prompt asking for tracking permission.
    Less silent tracking: IDFA is disabled unless explicitly allowed.
    🟡 Trade-offs:
    Still tracked within apps via first-party data and email/device linking.
    Many ads became less relevant or more frequent, since personalization declined.
    Clip Image003
    🍏 5. Impact on Apple
    📈 Reputation Boost:
    Positioned itself as a champion of privacy.
    💰 Business Benefit:
    Benefited indirectly as advertisers:
    Shifted budgets toward App Store Search Ads
    Focused more on Apple-owned channels
    ⚠️ Criticism:
    Accused of using privacy to tighten its ecosystem control and weaken rivals (e.g., Facebook).
    Facing antitrust scrutiny in the U.S. and EU.
     
    Walled Garden
    A closed platform, walled garden, or closed ecosystem is a software system wherein the carrier or service provider has control over applications, content, and/or media, and restricts convenient access to non-approved applicants or content.
    This is in contrast to an open platform, wherein consumers generally have unrestricted access to applications and content.

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