The Big Story
Google Dodges Breakup, But Still Faces Consequences
After a lengthy trial that proved Google’s monopolistic behavior and an extended deliberation period, Judge Amit Mehta ruled that while Google won’t be forced to break up its search operations by selling off Chrome, it can no longer rely on the exclusive distribution deals that helped cement its position as the go-to search engine. For years, Google paid billions to companies like Apple and Samsung to make its search engine the default on their devices, an arrangement the court described as “extremely valuable real estate” that locked out rivals. Those deals are now banned, and Google must also share portions of its search index and user-interaction data with qualified competitors. It’s a softer outcome than the structural breakup the Department of Justice sought, but it marks a clear attempt to open the door for competition in a market where Google has maintained about a 90% share for the last decade.
The ruling follows another major case earlier this year, when a different federal court found that Google illegally monopolized digital advertising markets. In that trial, internal documents revealed how Google manipulated its ad auctions through so-called “pricing knobs.” By raising prices in small increments, between 5% and 15%, Google made the increases look like ordinary market fluctuations. Advertisers noticed costs rising but, according to Google’s own surveys, but did not realize Google itself was behind the changes. Judge Mehta described the practice as designed to avoid blowback, allowing Google to quietly boost long-term revenue “without fear of losing advertisers.” As part of the remedies, the court has now ordered Google to provide regular reports on auction adjustments and disclose material changes that could affect advertiser costs.
For marketers, the changes won’t be overnight, but they will have an impact. The end of exclusive deals could give new search engines like OpenAI, Perplexity and other emerging players a real shot at reaching users, which means brands may need to think beyond Google when chasing search intent. In truth, they should already be doing that, given how quickly AI-generated search results are reshaping how people find information. On the ad side, new transparency rules around auction mechanics could finally shed light on why costs rise, giving marketers more control over budgets and spend. Google is expected to appeal, and real change will take time. Still, it’s clear that regulators are continuing to push for a more open and competitive system. For marketers, that means paying attention now and preparing for a future where search and ads aren’t locked inside of Google’s black box.
Social Media Updates
Consumer Marketing Meets LinkedIn
LinkedIn is evolving beyond its B2B roots and attracting new attention from consumer brands. The shift is fueled by the platform’s premium audience of professionals and executives, who are perceived to be more affluent and influential than users on other channels. For marketers, this creates an opportunity to reach consumers in a trusted, brand-safe environment where information is seen as credible because it comes from other professionals. That’s why the introduction of creator marketing has the potential to be so powerful on a platform like this to a certain extent, of course. Productivity app Notion has already leaned into this by partnering with LinkedIn creators to push tools and templates that users can bring into their workplaces, bridging consumer interest with professional adoption. As more consumer campaigns test the waters, costs will rise and standing out will become harder, but early movers can carve out a strong position before the platform becomes crowded.
Meta Expands Attribution With AI-Powered Tracking
Attribution is the way platforms connect ads to the actions people take afterward, like making a purchase or signing up. Until now, Meta’s standard attribution measured this by tracking clicks, impressions, or video views within a short time window, usually 1 to 7 days. The issue is that this often misses the bigger picture of how people actually make decisions, since many conversions happen after longer or less direct paths. Meta’s new incremental attribution model uses machine learning to predict whether a conversion was truly caused by an ad, taking into account a wider range of behaviors and data points. While Meta hasn’t revealed exactly how the model works, it’s designed to show the hidden influence ads have beyond immediate clicks. For advertisers, this means more accurate reporting and optimization opportunities, with the ability to better capture the real value of campaigns in today’s fragmented, non-linear customer journeys.
Digital Updates
Sydney Sweeney May Have Great Jeans, But American Eagle Has Even Greater Returns
Whether you love it, hate it, or just saw it against your will, American Eagle’s Sydney Sweeney campaign is proof that even controversial attention can translate into business results. The campaign sparked backlash from people who criticized it as objectifying and tone-deaf, with the “great jeans/genes” wordplay called out as outdated and off the mark. But while the internet was busy arguing, the numbers told a different story. American Eagle reported that the campaign has delivered 40 billion impressions and brought in 700,000 new customers since launch. On top of that momentum, the company’s stock climbed 33% after its latest earnings call, where leadership credited the campaign for driving growth. Paired with Travis Kelce’s Tru Kolors push, AE proves that start power and cultural relevance can beat bad press, and for marketers, the real metric isn’t social sentiment but whether campaigns are bringing in new customers and sales.
AI Search Sends Users to 404s Nearly 3x More Than Google
A new Ahrefs study shows AI search tools are a lot more likely to send users to dead ends than Google. ChatGPT referrals hit 404 pages about 1% of the time compared to Google’s 0.15%, and when you look at all links AI surfaces, not just the clicked ones, that rate jumps to 2.38%. Other players like Claude, Copilot, Perplexity, and Gemini all perform worse than Google too, with only Mistral coming close. The issue comes from AI tools surfacing outdated links or straight-up inventing URLs that don’t exist. A closer look at how answer engines decide what to surface shows the system is fundamentally different from how Google ranks pages. AI isn’t crawling and indexing the whole web in the same way. Instead, it’s weighing clarity, authority, and patterns in language to pick its “winners.” That helps explain why AI can sometimes elevate outdated or even fabricated links. Right now, AI assistants drive just 0.25% of site traffic, but if usage keeps growing, broken links & content structuring could become a bigger headache for marketers and site owners.
