That process really messed with my head. But I did it. I got the visa, got the awards, worked with big clients, built a studio and hired a team. I did what I was supposed to do. Even so, I didn’t feel like I fit the mould; I don’t sound like a typical founder. I didn’t grow up speaking English. I didn’t come from money. I never had training in public speaking. And I’ve tried to play the part, but it’s not really me. I’ve always felt like I had to prove myself twice – once with the work, and again to be taken seriously.
A few months ago, I was invited to close the main stage at one of the biggest design conferences in the world. It felt like a big moment. But the whole process leading up to it was more intense than what I’m used to. There were multiple rounds of content feedback, rehearsals, a lot of back and forth. I went along with it, but it didn’t feel great.
Then, a couple of nights before my talk, during a speakers’ dinner, someone from the company pulled me aside and said they wanted another rehearsal. The person hadn’t even seen my talk – they were just passing along the message. It felt off. Out of context, and kind of undermining. Like what I’d done so far wasn’t good enough.
I went back and rehearsed on my own. Not because I needed to, but because I felt like I had to prove something. Again.
This post was sponsored by MarketBrew. The opinions expressed in this article are the sponsor’s own.
Is Google using AI to censor thousands of independent websites?
Wondering why your traffic has suddenly dropped, even though you’re doing SEO properly?
Between letters to the FTC describing a systematic dismantling of the open web by Google to SEO professionals who may be unaware that their strategies no longer make an impact, these changes represent a definite re-architecting of the web’s entire incentive structure.
It’s time to adapt.
While some were warning about AI passage retrieval and vector scoring, the industry largely stuck to legacy thinking. SEOs continued to focus on E-E-A-T, backlinks, and content refresh cycles, assuming that if they simply improved quality, recovery would come.
But the rules had changed.
In late 2023 and early 2024, Google began rolling out what it now refers to as AI Mode.
AI Mode breaks content into passages, embeds those passages into a multi-dimensional vector space, and compares them directly to queries using cosine similarity.
In this new model, relevance is determined geometrically rather than lexically. Instead of ranking entire pages, Google evaluates individual passages. The most relevant passages are then surfaced in a ChatGPT-like interface, often without any need for users to click through to the source.
Beneath this visible change is a deeper shift: content scoring has become embedding-first.
Embedding vectors are mathematical representations of meaning. When Google processes a passage of content, it converts that passage into a vector, a list of numbers that captures the semantic context of the text. These vectors exist in a multi-dimensional space where the distance between vectors reflects how similar the meanings are.
Instead of relying on exact keywords or matching phrases, Google compares the embedding vector of a search query to the embedding vectors of individual passages. This allows it to identify relevance based on deeper context, implied meaning, and overall intent.
Traditional SEO practices like keyword targeting and topical coverage do not carry the same weight in this system. A passage does not need to use specific words to be considered relevant. What matters is whether its vector lands close to the query vector in this semantic space.
Keywords focus on exact matches. Embedding vectors focus on meaning.
Traditional SEO relied on placing target terms throughout a page. But Google’s AI Mode now compares the semantic meaning of a query and a passage using embedding vectors. A passage can rank well even if it doesn’t use the same words, as long as its meaning aligns closely with the query.
This shift has made many SEO strategies outdated. Pages may be well-written and keyword-rich, yet still underperform if their embedded meaning doesn’t match search intent.
The story isn’t just about Google changing the game, it’s also about how the SEO industry failed to notice the rules had already shifted.
As rankings dropped, many teams assumed they’d been hit by a quality update or core algorithm tweak. They doubled down on familiar tactics: improving E-E-A-T signals, updating titles, and refreshing content. They pruned thin pages, boosted internal links, and ran audits.
But these efforts were based on outdated models. They treated the symptom, visibility loss, not the cause: semantic drift.
Semantic drift happens when your content’s vector no longer aligns with the evolving vector of search intent. It’s invisible to traditional SEO tools because it occurs in latent space, not your HTML.
No amount of backlinks or content tweaks can fix that.
This wasn’t just platform abuse. It was also a strategic oversight.
SEO teams:
Many believed that doing what Google said, improving helpfulness, pruning content, and writing for humans, would be enough.
That promise collapsed under AI scrutiny.
But we’re not powerless.
Google told the industry to “focus on helpful content,” and SEOs listened, through a lexical lens. They optimized for tone, readability, and FAQs.
But “helpfulness” was being determined mathematically by whether your vectors aligned with the AI’s interpretation of the query.
Thousands of reworked sites still dropped in visibility. Why? Because while polishing copy, they never asked: Does this content geometrically align with search intent?
The new SEO playbook begins with a simple truth: you are optimizing for math, not words.
Here’s what we now know:
It depends on your goals; for success in SERPs, you need to focus on tools that not only show you visibility data, but also how to get there.
Profound was one of the first tools to measure whether content appeared inside large language models, essentially offering a visibility check for LLM inclusion. It gave SEOs early signals that AI systems were beginning to treat search results differently, sometimes surfacing pages that never ranked traditionally. Profound made it clear: LLMs were not relying on the same scoring systems that SEOs had spent decades trying to influence.
But Profound stopped short of offering explanations. It told you if your content was chosen, but not why. It didn’t simulate the algorithmic behavior of AI Mode or reveal what changes would lead to better inclusion.
That’s where simulation-based platforms came in.
Market Brew approached the challenge differently. Instead of auditing what was visible inside an AI system, they reconstructed the inner logic of those systems, building search engine models that mirrored Google’s evolution toward embeddings and vector-based scoring. These platforms didn’t just observe the effects of AI Mode, they recreated its mechanisms.
As early as 2023, Market Brew had already implemented:
🔍 Market Brew Tutorial: Mastering the Top Cluster Similarity Ranking Factor | First Principles SEO
This meant users could test a set of prompts against their content and watch the algorithm think, block by block, similarity score by score.
Where Profound offered visibility, Market Brew offered agency.
Instead of asking “Did I show up in an AI overview?”, simulation tools helped SEOs ask, “Why didn’t I?” and more importantly, “What can I change to improve my chances?”
By visualizing AI Mode behavior before Google ever acknowledged it publicly, these platforms gave early adopters a critical edge. The SEOs using them didn’t wait for traffic to drop before acting, they were already optimizing for vector alignment and semantic coverage long before most of the industry knew it mattered.
And in an era where rankings hinge on how well your embeddings match a user’s intent, that head start has made all the difference.
SEO didn’t die. It transformed, from art into applied geometry.
To help SEOs adapt to this AI-driven landscape, Market Brew has just announced the AI Mode Visualizer, a free tool that simulates how Google’s AI Overviews evaluate your content:
This is the only tool that lets you watch AI Mode think.
Nate Hake is right: Google restructured the game. The data reflects an industry still catching up to the new playbook.
Because two things can be true:
It’s time to move beyond guesses.
If AI Mode is the new architecture of search, we need tools that expose how it works, not just theories about what changed.
We were bringing you this story back in early 2024, before AI Overviews had a name, explaining how embeddings and vector scoring would reshape SEO.
Tools like the AI Mode Visualizer offer a rare chance to see behind the curtain.
Use it. Test your assumptions. Map the space between your content and modern relevance.
Search didn’t end.
But the way forward demands new eyes.
Book Your AI Mode Strategy Session
________________________________________________________________________________________________
Image Credits
Featured Image: Image by MarketBrew. Used with permission.
Large Language Model (LLM) agents aren’t very good at key parts of CRM, according to a study led by Salesforce AI scientist Kung-Hsiang Huang.
The report showed AI agents had a roughly 58% success rate on single-step tasks that didn’t require follow-up actions or information. That dropped to 35% when a task required multiple steps. The agents were also notably bad at handling confidential information.
“Agents demonstrate low confidentiality awareness, which, while improvable through targeted prompting, often negatively impacts task performance,” the report said.
While the agents struggled with many tasks, they excelled at “Workflow Execution,” with the best agents having an 83% success rate in single-turn tasks. The main reason agents struggled with multi-step tasks was their difficulty proactively acquiring necessary, underspecified information through clarification dialogues.
Dig deeper: 7 tips for getting started with AI agents and automations
The more agents asked for clarification, the better the overall performance in complex multi-turn scenarios. That underlines the value of effective information gathering. It also means marketers must be aware of agents’ problems handling nuanced, evolving customer conversations that demand iterative information gathering or dynamic problem-solving.
One of the biggest takeaways for marketers: Most large language models have almost no built-in sense of what counts as confidential. They don’t naturally understand what’s sensitive or how it should be handled.
You can prompt them to avoid sharing or acting on private info — but that comes with tradeoffs. These prompts can make the model less effective at completing tasks, and the effect wears off in extended conversations. Basically, the more back-and-forth you have, the more likely the model will forget those original safety instructions.
Open-source models struggled the most with this, likely because they have a harder time following layered or complex instructions.
Dig deeper: Salesforce Agentforce: What you need to know
This is a serious red flag for marketers working with PII, confidential client information or proprietary company data. Without solid, tested safeguards in place, using LLMs for sensitive tasks could lead to privacy breaches, legal trouble, or brand damage.
The bottom line: LLM agents still aren’t ready for high-stakes, data-heavy work without better reasoning, stronger safety protocols, and smarter skills.
The complete study is available here.
I’ve long waxed lyrical about the Apple Watch SE 2, and questioned the need for anyone (who isn’t mountaineering) to have any of the fancier watches on offer. It did everything I needed it to and I was happy. But then I tried the Apple Watch 10 and for some inexplicable reason, I like it more.
It’s not that I use any of the features – I don’t need to track underwater activity, and I haven’t turned any of the more advanced health alerts on. But it does actually have benefits that seem more basic yet make a big difference to the user experience. It’s currently at the lowest price ever at Amazon, by the way (only $299.99 with $100 off), so if you agree with my thinking it’s a great time to get your own.
(Image credit: Apple)
Today’s best Apple Watch Series 10, Apple Watch SE (2022) GPS + Cellular and Apple Watch Series 9 deals
Today’s Memo is a download straight from my brain about the current state of Search and AI. So much happened in the last few weeks, and I haven’t had a chance to sort out my thoughts.
Until now.
I’m finishing this Memo with exclusive insight into the KPIs I measure for search right now for premium subscribers .
In this issue, we’re looking at:
Let’s dive in!
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On April 16 at 9 a.m., OpenAI dropped ChatGPT o3.
By noon, I’d already scrapped the slide deck I had finished the night before.
That whiplash has become routine: Each new model triggers the same loop – panic that it’s smarter than I am. Relief when I find the edges. Then, fresh panic as the cycle restarts.
When my coach, Heather, heard me vent, she dropped a killer quote that stuck with me since: “Kevin, constant change is the new normal.”
She’s right.
Releases land weekly, search interfaces mutate overnight, and the ground under every SEO strategy keeps sliding.
As we cross the midpoint of 2025, I want to freeze-frame what’s happening to search right now – and what it means for you.
Here’s the short version:
Let’s unpack each shift, starting with the calories we’ve been counting all wrong.
Since Google widened AI Overviews (AIOs) in March, one pattern rules them all: impressions up, clicks down.
Image Credit: Kevin Indig
Why the gap?
Two reasons:
The result: visibility inflation without visitors.
2024 was the year of peak traffic.
And looking at how few people clicked on links (a few percent) in the AIO usability study makes me think it’s entirely possible clicks drop to 10% or less of what we’ve been used to in 2024. And that’s ok.
Clicks have always been empty calories anyway. They were useful as a leading indicator for conversions/revenue/pipeline/sales/etc. (But that’s about it. Clicks didn’t mean dollars, and they didn’t mean real business growth.)
Of course, to us SEO folk, losing clicks sounds grim until you look closer at user behavior:
So, yes, raw clicks are vanishing, but the ones that survive are pure protein, not empty calories.
Clicks are collapsing, but the ones that remain are loaded with intent.
That flips SEO’s value prop on its head.
For 20 years, we sold SEO as a performance channel, whether we wanted to or not.
The standard calculation was: Search volume ✕ CTR ✕ CVR = Projected dollars.
When a keyword couldn’t survive that spreadsheet, it died in committee.
Meanwhile, those same executives drop seven figures to get a logo the size of a postage stamp on an F1 car – no attribution model in sight.
Why? Influence.
The belief that persistent visibility bends preference.
SEO is crossing the same Rubicon. In an AIO-and-LLM world, you’re not just fighting for traffic; you’re fighting for mindshare wherever prospects ask questions:
Your brand needs to echo across all of them.
That means new yardsticks (i.e., KPIs, which I laid out in the premium section at the end of the article).
In short, SEO is graduating from direct-response to influence.
Treat it – and budget for it – like any other brand channel that shapes preference long before the buy button.
AI Mode turns a single prompt into dozens of behind-the-scenes queries – a process engineers call “fan-out.”
The same thing is happening at the channel level: Search itself is fanning out, escaping the browser and popping up in every feed, app, and device.
Although SEO pros have been talking about it for years, in 2025, that finally, actually matters – and for three big reasons:
1. LLMs have injected search into every app. Want a cookie recipe breakdown in Microsoft Excel? You can have it. Meta shipped a standalone Meta AI and wove it into WhatsApp, IG, and FB. YouTube and Netflix are testing AI Overviews so you can “search” for the perfect video without ever leaving their walls.1
Translation: discovery no longer begins – or ends – on Google.com. Each walled garden is now its own mini-SERP, and Google has to fight a thousand little AI search engines, not just ChatGPT.
2. People cross-check AI with humans: Our AIO usability study showed a consistent pattern: Users read the AI answer, then hop to Reddit threads, YouTube comments, or Discord chats to see whether real people agree.
Credibility now comes from echoing across both machine answers and human conversations. If you’re invisible on social or community platforms, you’re invisible in the final decision loop.
3. The pie is somehow getting bigger. TikTok, Facebook, Instagram, Threads, Bluesky, YouTube, Google, ChatGPT, Perplexity, Claude, Snapchat – the list keeps growing, and so do their daily active users.
Where’s the extra time coming from? Mostly legacy media: linear TV, radio, even mainstream news sites. Attention is being reallocated, not reinvented.
What it means:
Sparktoro’s channel overview
AI Mode is the “final boss” of search.
Sundar Pichai told Lex Fridman that “the results page is just one possible UI,” and VP of Search Liz Reid called it “a construct.”
In other words, Google’s happy to toss the classic SERP the moment the math works.
Similarweb data shows AI Mode adoption is a bit over 1% – for now (Image Credit: Kevin Indig)
But right now, the math doesn’t.
Similarweb shows AI Mode in barely 1% of queries, by design.
A single AI Mode answer can swallow 20-50 follow-up searches, erasing the ad slots those pages used to carry.
Until Google finds a new way to charge (embedded ads, pay-per-chat, who knows), rollout will stay throttled.
When that business model lands, AI Mode becomes paradise for anyone who understands user intent.
Behind each prompt, Google “fans-out” dozens of micro-queries – price, specs, comparisons, nearby, reviews – and stitches the answers together.
Those micro-queries are the very same long-tails you optimize for today; they’re just fired in parallel and reassembled into a narrative.
How to prep while the gate is still half-closed:
Do the homework now and you’ll be ready when AI Mode graduates from beta to default – at least until the next boss fight, fully agentic search, shows up.
The twist of 2025 is that Google is meeting ChatGPT on its own turf.
AI Mode lifts Google’s results page into the same chat-first UI that OpenAI popularized – proof that Google is willing to “level down” from its ad-optimized SERP if that’s what users expect.
Last year, I shared this graphic for the launch of ChatGPT Search and got lots of questions:
Image Credit: Kevin Indig
Image Credit: Kevin Indig
Bottom line: treat the Google-ChatGPT battle as a live A/B test for the future of search.
Your job is to be visible in both ecosystems until a clear winner emerges – and that may take years.
Image Credit: Kevin Indig
So, where does all of this leave SEO (leaders)?
Less in the weeds, more on the podium.
Your job is no longer to fine-tune a single channel; it’s to keep an entire orchestra in time as search fragments across AI Overviews, chatbots, and social feeds.
No other role sits at the intersection of so much (intent) data – and that gives you license (and responsibility) to conduct.
1. Paid Media
2. Social & Community
3. Product Marketing
4. Content/GTM
Search will get even more agentic.
We could soon optimize not just for people but for the AI helpers who act on their behalf.
That means:
We’re not there yet, but the runway is short.
Shift from tactician to conductor now, and you’ll have the score in hand when the orchestra changes instruments again.
Baton up.
1 YouTube Tests AI Overviews In Search Results; Netflix Tests New AI Search Engine to Recommend Shows, Movies
Featured Image: Paulo Bobita/Search Engine Journal
Lobby group Movement for an Open Web has issued fresh calls for the Justice Department to coordinate its proposed remedies to address Google’s monopolies in the ongoing separate search and ad tech cases.
The DOJ is developing remedy proposals to counter Google’s market power in search and ad tech, both of which were ruled monopolies during the last 12 months, with MOW now calling for conjoined technical oversight of the two cases.
Currently, the remedies in each case are under development and will be overseen by separate technical committees, according to MOW, which is now calling for these to be merged, citing the need for a holistic approach to market correction.
In antitrust cases, a technical committee is a group of independent experts appointed by the court or a regulatory body, such as the DOJ, to oversee compliance with a settlement or remedy, particularly regarding technical aspects of a case.
MOW claimed a holistic strategy is critical due to the complexity and interdependence of Google’s business lines, and that uncoordinated remedies risk missing structural issues that sustain monopoly power.
The group supports existing DOJ proposals but cites Justice Brinkema’s ruling in the ad tech case that Google’s control of AdWords demand fuels its monopoly in ad exchanges. It thus calls for additional steps to empower publishers, including control over inventory auctions, transparency in pricing data, and restrictions on Google’s use of its owned-and-operated properties to gain bidding advantages.
MOW’s Tim Cowen, also chairman of the antitrust practice at Preiskel & Co., argued that there is potential for Google to discriminate in its ad tech practices through technical means, even after divestiture, citing how its purchase of DoubleClick enabled it to leverage its position in the search market to dominate the display advertising market.
“It blocked access to the DoubleClick ID so that third parties would become dependent on it,” he told Digiday, explaining the intricacies by which the online giant was able to dominate the market. “Then what it did was to give itself the first look at bids on the exchange… when that didn’t prove to be profitable enough, it gave itself a last look as well.”
The DOJ proposes forcing Google to sell its Chrome browser, end billions in default‐search payments to handset manufacturers, license its search index and user data to rivals for a decade, and potentially divest Android and enforce a choice‑screen mandate to restore competition
Google countered these breakup demands by outright opposing the forced sale of Chrome and suggesting limited, targeted contract reforms and broad data sharing, or long-term oversight.
Meanwhile, the DOJ’s proposed remedy targets Google’s ad tech monopoly through a three-phase plan: first, mandating real-time data access for rivals via Prebid; second, opening Google’s DFP auction logic to open-source; and third, fully divesting its ad server DFP and AdX under court supervision.
Following the divestiture, Google would be prohibited from operating an ad exchange for 10 years. Additionally, 50% of AdX and DFP net revenues would be placed into escrow to support the publisher transition and independent auction development. Google’s counter-proposals recommended more limited reforms to avoid a breakup, including real-time AdX data access, ending Unified Pricing Rules, and forgoing auction advantages.
At Advertising Week New York last year, industry leaders questioned whether the DOJ’s proposed breakup of Google’s ad tech would meaningfully shift the landscape. Some argue that Google is already one step ahead of regulators, citing its dominance as a deterrent to competition and suggesting that remedies may be too late to matter.
Many are divided on whether a breakup would hurt or ultimately heal the ad tech ecosystem, with some arguing the only effective means of hamstringing Google would be a huge fine. “I think the DOJ is now fighting yesterday’s war. No matter what the result is, the damage is done, and by the time they have the remedy, the environment is going to be so different,” said Justin Choi, CEO of Nativo, on one Advertising Week panel.
MOW’s Cowen further claimed that without adequate, conjoined oversight of the technical remedies, Google can take measures to evade any effective market intervention. “The idea of the remedy is that the divested entity [either AdX, Chrome, or DFP] has no interest in Google,” he said, adding that many contractual remedies – not to mention effective ongoing oversight – are additionally required to have the desired effect.
Justice Amit Mehta, the presiding judge in the search antitrust case, is on course to offer a ruling on remedies in early August. Google may appeal the judgment within 30 days, potentially extending proceedings through 2027.
Meanwhile, the remedies phase of the ad tech antitrust case is scheduled to begin on September 22.
This summer, New Designers returns to London for its 40th anniversary – it’s a milestone that feels as much about celebrating the future as it is about honouring the past. Since 1985, the showcase has acted as a launchpad for some of the UK’s most exciting creative voices, offering an early glimpse into the next generation of designers across fashion, furniture, textiles, illustration, ceramics and more. In a cultural moment increasingly shaped by shifting values, new technologies and changing aesthetics, the class of 2025 is stepping forward with bold ideas and a strong sense of self.
Hosted once again at the Business Design Centre in Islington, the two-week showcase (Week 1: 2–5 July; Week 2: 9–12 July) brings together over 2,500 graduates from across the UK. But more than just an exhibition, New Designers creates a space for connection, visibility and momentum. It’s where studios, recruiters and industry leaders go to spot what’s coming next, but its’s also where emerging designers test their voice, share their perspective and meet their creative peers on a national stage.
Right now, CMOs are navigating a fast-moving environment, marked by economic pressures, new technologies, and shifting consumer expectations.
The pressure to demonstrate impact while adapting to new platforms, regulations, and expectations has never been greater.
For marketing leaders, this means constantly adjusting strategies to stay competitive and relevant.
To prepare for the marketing equivalent of the Olympic high hurdles, the article below outlines the 10 key hurdles that CMOs must overcome in 2025 and beyond.
Economic volatility and tighter marketing budgets are forcing CMOs to do more with less.
Although most are asked to show the return on investment of marketing expenditures, the right metric to use is return on marketing investment (ROMI).
While both are measures of profitability, ROI measures money that is “tied up” in plants and inventories (which are capital expenditures or CAPEX), while ROMI measures money spent on marketing in the current quarter (which are operational expenditures or OPEX).
The formula for calculating ROMI is:
(Incremental Revenue from Marketing × Contribution Margin – Marketing Spend) / Marketing Spend = ROMI
For example, Amazon reportedly paid MrBeast $100 million to produce the first season of his reality show “Beast Games.”
MrBeast says he’s lost “tens of millions” producing the show. But how does Amazon’s CMO, Julia White, calculate the ROMI for “Beast Games,” which launched in November 2024?
Let’s say the estimated lifetime value of an Amazon Prime member is around $2,000, and a scientific wild-ass guess (SWAG) for the paid membership program’s contribution margin is about 12.5%.
So, “Beast Games” needs to generate roughly $2 billion in incremental revenue for Amazon Prime to get a ROMI of 1.5.
Here’s how to calculate that:
[$2 billion × 12.5% – $100 million] / $100 million = 1.5
That means “Beast Games” needs to generate a million new Amazon Prime members for the paid membership program to get $1.50 in profit for every $1.00 it spends on MrBeast.
CMOs should read Kevin Indig’s article, “The First-Ever UX Study Of Google’s AI Overviews: The Data We’ve All Been Waiting For,” which paints the most significant new picture of how people use Google that I’ve seen since Gord Hotchkiss, the former CEO of Enquiro, produced his first search engine user eye tracking study back in 2007.
Indig’s groundbreaking usability study, which was conducted with Eric van Buskirk and his team, analyzed how 70 users interact with Google’s AI Overviews (AIOs), involving nearly 400 AIO encounters. The findings reveal that AIOs significantly reduce outbound clicks: desktop click-through rates (CTR) can fall by two-thirds, and mobile CTR by almost half.
Most users (70%) only read the top third of an AIO, with a median scroll depth of 30%. Trust in AIOs correlates with scroll depth. Younger mobile users (25-34) are more likely to accept AIOs as final answers (50% of queries).
Brand authority is now the primary decision filter, followed by relevance.
When users do click out after viewing an AIO, about a third of that traffic goes to community forums like Reddit and videos on YouTube.
The study concludes that search is shifting from a “click economy” to a “visibility economy,” where being cited high in an AIO is crucial, as users treat AIOs like quickly scanned fact sheets.
CMOs should also watch the IMHO interview with Indig that Search Engine Journal’s Shelley Walsh recorded about his research.
CMOs also face the challenge of addressing changing customer interests throughout their multichannel journeys.
To overcome this high hurdle, a recent SparkToro article said that true audience research needs to go beyond basic demographics or keywords.
This requires delving into what genuinely interests consumers, the specific language they use, their motivations, and potential barriers to action.
Understanding where they spend their time online and which information sources they trust is also crucial.
For example, Jeff Baker and his partners created Beach Commute, a startup aimed at the “location-independent” community.
Their primary challenge was identifying the correct terminology and phrases used by professionals seeking a location-independent lifestyle, since their target audience is still developing and lacks standardized language.
This made it difficult to connect with potential users through traditional keyword research, since search terms were varied and intent was often unclear.
For example, “work and travel” often led to individuals seeking work-exchange programs rather than career-focused remote work.
Beach Commute used SparkToro to gain deeper insights into consumer behavior and search intent.
By comparing potential homepage keyword targets like “become a digital nomad” and “make money while traveling,” SparkToro revealed distinct audience motivations.
The “digital nomad” audience was more interested in aspirational travel and advice, aligning better with Beach Commute’s offerings.
In contrast, the “money and travel” group focused on entrepreneurial “hacks.” This data allowed Beach Commute to refine its keyword strategy and effectively target the right audience.
CMOs are also tasked with strategically integrating AI to enhance marketing effectiveness, drive efficiency, and enable hyper-personalization. But how do their teams balance AI capabilities with human creativity?
For over a quarter-century, the PODS container has served as a mobile advertisement across American streets, acting as a constant reminder of the brand.
In a recent initiative, Tombras, the creative agency for PODS, collaborated with Google Gemini to transform one of its containers into the “World’s Smartest Billboard.”
This innovative billboard was designed to be aware of its surroundings, capable of identifying its precise location, the current time, prevailing traffic conditions, weather patterns, and even subway delays.
Leveraging this data, the smart billboard could generate and display highly specific and relevant messages for each neighborhood it was in, all in real-time.
As part of an ambitious demonstration, the team undertook the challenge of taking this intelligent billboard to every single neighborhood in New York City within a tight 29-hour timeframe.
This feat, considered humanly impossible, was achieved through the combined efforts of human creativity and AI.
The creative team worked closely with Google Gemini to ensure the AI could replicate the company’s distinct tone and content style on a massive scale.
This collaboration resulted in the creation and instant display of over 6,000 hyper-local, real-time ads on the PODS container.
The project highlights the remarkable outcomes that can be achieved when creative professionals, advanced multimodal AI, and a moving company join forces.
CMOs are increasingly expected to drive business growth, necessitating a close alignment of marketing strategies with overall company goals like revenue generation and market expansion.
It requires CMOs to demonstrate marketing’s financial contribution and, as Avinash Kaushik advises, refine their use of dashboards and scorecards.
In an Occam’s Razor article, Kaushik highlights that CMOs often track non-essential metrics, leading to data overload.
To counter this, he proposes categorizing data into key performance indicators (KPIs), diagnostic metrics, and influencing variables. This framework helps focus senior leadership on critical business impacts, particularly profits, while allowing teams to manage tactical optimizations separately.
This strategic approach to data aims to clarify what truly matters for achieving business objectives, distinguishing between strategic measures and in-flight tactical adjustments.
Despite its apparent simplicity, Kaushik notes that many marketing teams struggle with this differentiation, prompting him to outline distinct characteristics for each category across eleven factors.
For example, Hilton and Dentsu Americas collaborated on the “For The Stay” campaign, using video as a central element of their marketing efforts.
A key question they sought to answer, according to Hilton’s Rebecca Panico, was how to effectively tailor creative content to specific audiences.
By doing so, they achieved substantial growth in brand awareness, customer consideration, purchase intent, and booking conversions, demonstrating the effectiveness of their strategy in a changing travel market.
In an increasingly crowded digital space, producing high-quality, engaging, and differentiated content consistently is a major hurdle, especially with limited resources.
With the rise of AI-generated content, the emphasis on authentic, human-crafted storytelling and unique brand messaging becomes even more critical to stand out.
To surmount this hurdle, CMOs should start by reading AI & Creators: The future of Tech and Creativity, which provides an in-depth exploration of the current and future effects of generative AI on creator businesses.
To support this, YouTube conducted its largest global survey to date, examining how creators around the world are integrating Gen AI into their work.
Then, CMOs should read Your Brandcast 2025 recap: Culture, creators, and commerce.
At the event, YouTube celebrated its 20th anniversary, highlighting its evolution as a dominant media platform and “the new TV.”
Brandcast 2025 also emphasized the growing impact of creators on culture and commerce, noting that 81% of U.S. viewers use creator content for product discovery, and YouTube ads deliver a 4.5X higher return on ad spend than other streaming TV.
YouTube also unveiled new advertising innovations for Connected TV (CTV). These include Cultural Moments Sponsorships for major events, and “Peak Points” powered by Google AI to place ads during peak audience engagement.
Additionally, new immersive Masthead ads and Shoppable CTV features aim to drive awareness and action directly from the living room, connecting creators, fans, and brands across all viewing experiences.
In today’s climate of consumer skepticism and the prevalence of cancel culture, maintaining brand trust and authenticity has become increasingly difficult.
CMOs must ensure that brand messaging remains consistent, transparent, and aligned with a company’s core values and behaviors.
For example, Kantar’s May 2025 Monthly Trends Report says transparency, particularly around data usage, can offer a competitive edge in a world marked by extreme disruption and uncertainty.
This volatile environment is not entirely new. For years, critiques of globalized commerce and culture have been gaining momentum from both ends of the political spectrum: the left condemns cultural imperialism, while right-wing populism has grown since the Great Recession.
These long-standing tensions have intensified recently, with inflation, COVID-19, climate change, and war disrupting the marketplace. Tariff threats have added further strain, placing American brands under heightened scrutiny.
Historically, brands functioned within a relatively stable ecosystem of supply chains, digital media, and retail consolidation, largely removed from political turmoil.
Today, however, they find themselves entangled in it, struggling to preserve brand equity and market share.
Kantar research highlights a rise in anti-American sentiment due to tariffs, yet paradoxically shows American brands are stronger and more valuable than ever.
Despite this resilience, future stability is uncertain. The challenge for brands is not merely survival but sustained growth, which is becoming increasingly rare.
To thrive, CMOs must resist the temptation to retreat under pressure and instead focus on consistently adding consumer value – offering more reasons to engage, not fewer.
With the decline of third-party cookies and the strengthening of data privacy regulations like GDPR and CCPA, CMOs face the critical challenge of ethically managing customer data.
This involves prioritizing the collection of first-party and zero-party data, ensuring transparency in data usage, and investing in secure platforms to build and maintain customer trust.
How do CMOs overcome this high hurdle while outrunning their competitors? They should start by reading Google Analytics Adds New Features For Privacy-Era Tracking.
Google has updated Google Analytics to improve data accuracy and help marketers identify issues faster, adapting to evolving privacy rules.
Key enhancements include “Aggregate Identifiers” to prevent misattribution of paid traffic when Google Click Identifiers (GCLID) are unavailable, and “Smart Fallback Methods” using UTM tags as a backup.
CMOs should then read, “Where Are The Missing Data Holes In GA4 That Brands Need?”
This article highlights that Google Analytics 4 (GA4) data, while useful, often misses crucial information about initial user acquisition, like how users first discover a brand.
SEO professionals should use audience research and surveys to understand these “missing bullet holes” and verify their GA4 interpretations.
The shift to hybrid work environments and the rapid evolution of marketing technologies necessitate innovative approaches to talent management.
CMOs face the challenge of attracting, retaining, and developing top marketing talent with the right skills, particularly in areas like AI, data analytics, and digital transformation.
Fostering a formidable team culture and providing continuous learning opportunities are the keys to avoiding tripping over this hurdle.
But CMOs should also read “I’m a LinkedIn Executive. I See the Bottom Rung of the Career Ladder Breaking.”
According to Aneesh Raman, the chief economic opportunity officer at LinkedIn, AI increasingly threatens entry-level jobs, traditionally crucial for young workers to gain experience.
This mirrors past manufacturing declines, now impacting office roles in tech, law, and customer service, where AI automates basic tasks.
Data shows rising unemployment for recent graduates, with Gen Z being particularly pessimistic about their futures.
While AI will also create new jobs, and executives still value fresh perspectives, the loss of entry-level positions can significantly hinder early career development and exacerbate inequality.
To address this, the essay proposes reimagining entry-level work. This includes training workers in AI-relevant skills and redesigning jobs to offer higher-level tasks, leveraging AI as a tool for growth and adaptability rather than mere automation.
Finally, marketing can no longer operate in a silo. Effective CMOs must champion cross-functional collaboration to ensure cohesive strategies and a unified customer experience.
This may be the hardest obstacle to overcome because it requires CMOs to unlearn what they have learned about the marketing department organization.
The most common organizational structure for marketing departments is called “functional” – because it puts distinct functions into different departments. But this creates dysfunctional silos with limited flexibility to adapt quickly or effectively to changes in market demand.
What’s the alternative? CMOs can organize their marketing teams by market segments, target audiences, or groups of people with specific interests, intents, and demographics.
This customer-centric organizational structure ensures that all their marketing teams are focused on putting customer needs and interests first in every interaction with the brand.
It also improves the likelihood that each team will understand their customers’ needs, concerns, and desires, and tailor marketing efforts to deliver value and exceptional experiences.
Now, I realize that most marketers mistakenly believe “reorgs” are bad, but reorganizations are infinitely less terrible than “layoffs.”
I also realize that most agencies dread “reorgs” because these often trigger “agency reviews.” But agencies should focus on delivering value, rather than simply providing services, to stand out and achieve long-term success.
This means moving beyond traditional service models and offering solutions that directly address client business needs and lead to measurable results.
To successfully navigate these 10 key hurdles, CMOs must become master jugglers, balancing technology with creativity, short-term performance with long-term brand building, and data-driven insights with authentic customer connections.
By addressing these critical hurdles, from adapting to AI-powered search to building consumer trust in a privacy-first world, marketing leaders can future-proof their organizations and drive meaningful growth.
Marketing is more complex than ever, but there is plenty of opportunity if you can move quickly, think strategically, and lead cross-functional teams with clarity and purpose.
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Featured Image: Elnur/Shutterstock
Criteo is bringing programmatic ad buying to retail media.
The adtech company is rolling out a change to its platform that allows advertisers to buy retail media display ads programmatically. The change is aimed at making it simpler for advertisers to buy across multiple retail media networks at once.
Auction-based buying could make it easier for retailers to sell leftover ad inventory that isn’t sold through traditional media buying methods like joint business plans, sponsorship deals, or preferred deals that require long-term, negotiated investments. It could also help retailers make more money off their ad slots during peak seasons when ad prices spike due to demand.
“Display advertising is a proven retail media format, but the needs of advertisers and retailers are evolving,” Melanie Zimmerman, general manager of global retail media at Criteo, said in a statement. “Our new auction-based offering is modernizing display technology.”
Criteo said that Costco and Shipt are using the new product.
Criteo’s offering competes with Google, two retail media sources told ADWEEK. The features that Criteo has built into its tech have traditionally been found in Google’s Ad Manager or Ad Exchange, the sources said.
“The way inventory is prioritized on the publisher side is basically a copy-paste of how Google Ad Manager handles inventory reservations,” said one source who has spoken directly with Criteo about the new offering.
Being able to buy Criteo’s inventory programmatically could also allow advertisers to worry less about hitting required investment numbers from joint business plans, the source said.
Joint business plans are yearlong deals between brands and retailers where brands agree to pay for advertising in exchange for selling their products with individual retailers. One of the complaints of joint business plans is that they lock brands into ad commitments that are not guaranteed to drive sales.
Instead of using joint business plans to fund ad dollars, the source suggested that Criteo’s new feature could help brands identify which retailers to spend with based on the retailers where Criteo finds the most sales. That could begin to shift the power dynamic between brands and retailers—putting more power back into the hands of advertisers, with Criteo as the middleman.
Andrew Lipsman, independent retail media consultant, added that Criteo’s product could be a “significant market enabler for retail media—especially with the emergence of second and third-tier RMNs plus the overall growth in upper-funnel ad units onsite.”
Every weekend morning when I’m taking my dog (Boris the Blade) on his morning walk, we are met by the same thing: a group of 20 to 30 predominantly middle-aged men and women running towards us.
And it’s not just one group. As Boris stops and smells the exact same street corner he did just hours ago to decide if it’s worthy of his lifted leg, several of these breathable-material, carbon-plated herds will swoosh by us.
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