They prove minimalist design can have a big impact.
Today’s advertising sphere often revolves around loud design and wacky viral moments, rarely giving us a slice of earnest branding. Cutting through the noise is Ikea’s new campaign, celebrating the intimate moments of life in its understated yet heartfelt ads.
Known for creating some of the best adverts, thanks to its stripped-back yet strong brand aesthetic, Ikea proves that minimalist design can be just as evocative as loud branding. Homely, relatable and genuine, Ikea’s new campaign captures a slice of life atmosphere that stands out in its simplicity.
(Image credit: IKEA Sweden)
Created by Ikea Sweden in collaboration with creative agency Åkestam Holst NoA, the ‘Wherever Life Goes’ campaign positions the brand as a companion through life’s intimate moments. A warm, close-up shot of a kiss is paired with a cheeky yet subtle price tag for the SÄBÖVIK double bed, while a teary-eyed zoom-in simply gestures to the DUNDERGUBBE moving box, positioning Ikea as a key part of life’s narrative.
Spanning film, print, OOH, radio, and socials, the campaign plays on the universal moments of the mundane, transforming them into tender vignettes. “There are many things that are iconic about IKEA, and the price tag is one of them,” says Michal Sitkiewicz, art director, Åkestam Holst NoA. “By letting something as simple as a price tag become a central part of the storytelling, we can capture the moments that lead to change and show how IKEA can support you through them.”
It’s fun — and often accurate — to think of tech companies in pairs. Apple and Microsoft defined the PC market; Microsoft and Intel won it. Google and Meta dominate digital advertising; Apple and Google won mobile. That, however, is not the defining pair of the smartphone era, which ran from the introduction of the iPhone in 2007 to the launch of ChatGPT in 2022; rather, the two most important companies of the last two decades of tech were Apple and Amazon, specifically AWS.
The Apple part is easy: the iPhone market created the smartphone paradigm, from its user interface (touch) to its distribution channel (the App Store), and was richly rewarded with a bit under half of the unit marketshare and a bit under all of the total profits. Google did well to control the rest in terms of the Android operating system, and profit from it all thanks to Google Search, but it was Search that remained their north star; the company’s primary error in the era was the few years they let the tail (Android) wave the dog (Google).
The AWS part is maybe less obvious, but no less critical — and the timing is notable. Amazon created AWS in 2006, just 10 months before the iPhone unveiling, and the paradigm they created was equally critical to the smartphone era. I explained the link in 2020’s The End of the Beginning:
This last point gets at why the cloud and mobile, which are often thought of as two distinct paradigm shifts, are very much connected: the cloud meant applications and data could be accessed from anywhere; mobile made the I/O layer available everywhere. The combination of the two make computing continuous.
What is notable is that the current environment appears to be the logical endpoint of all of these changes: from batch-processing to continuous computing, from a terminal in a different room to a phone in your pocket, from a tape drive to data centres all over the globe. In this view the personal computer/on-premises server era was simply a stepping stone between two ends of a clearly defined range.
AWS was not the only public cloud provider, of course — Azure and Google Cloud Platform were both launched in 2008 — but by virtue of being first they both defined the paradigm and also were the the first choice of the universe of applications that ran on smartphones or, more accurately, ran everywhere.
Smartphone Winners and Losers
If Apple and AWS were the definers — and thus winners — of the smartphone era, then it was Microsoft and Nokia that were the losers. The reasons for their failure were myriad, but there was one common thread: neither could shake off the overhang of having won their previous paradigm; indeed, both failed in part because they deluded themselves into thinking that their previous domination was an advantage.
For Microsoft that previous paradigm was the PC and the Windows platform, which the company thought they could extend to mobile; from 2014’s Microsoft’s Mobile Muddle:
Saying “Microsoft missed mobile” is a bit unfair; Windows Mobile came out way back in 2000, and the whole reason Google bought Android was the fear that Microsoft would dominate mobile the way they dominated the PC era. It turned out, though, that mobile devices, with their focus on touch, simplified interfaces, and ARM foundation, were nothing like PCs. Everyone had to start from scratch, and if starting from scratch, by definition Microsoft didn’t have any sort of built-in advantage. They were simply out-executed.
It took Microsoft years — and a new CEO — to realize their mistake, up and to the point where they put their enterprise productivity dominance at risk; from 2015’s Redmond and Reality:
There’s reality, and there’s Redmond, and if one thing marked the last few years of Steve Ballmer’s tenure as the CEO of Microsoft, it was the sense that those were two distinct locales. In reality, Android (plus AOSP in China) and iOS were carving up the world phone market; in Redmond Ballmer doubled-down on the losing Window Phone bet by buying Nokia. In reality Office was losing relevance because of its absence on the mobile platforms that mattered; in Redmond Ballmer personally delayed Office on iOS until the Windows Modern née Metro version was finished. And in reality, all kinds of startups were taking aim at the Microsoft enterprise stack; in Redmond, Microsoft was determined to own it all, just as they had in the PC era.
It’s fitting that Microsoft and Nokia ended up together; perhaps they were able to jointly go to therapy for success-induced obliviousness of market realities. Nokia dominated the phone market for the decade prior to the iPhone, and even once the iPhone was announced, blithely assumed that they could simply lean on their existing advantages to fend off the Silicon Valley usurper. From 2013’s Blackberry — and Nokia’s — Fundamental Failing:
Nokia dominated all the parts of this stack you don’t see: they had, and in some respects, still have, the best supply chain and distribution network. In addition, they had high quality hardware that served every segment imaginable. Notably absent in these strengths is the OS and Apps. By 2009, BlackBerry OS and Symbian were clearly obsolete, and their app ecosystems, such as they were, were eclipsed by iOS and then Android. The problem, as I alluded to above, is that while the OS was ultimately under the control of BlackBerry and Nokia, respectively, and thus could be fixed, the efficacy of their ecosystem wasn’t, and wouldn’t be…
And so, by far the smartest strategic thing either could have done would have been to accept their weakness — they didn’t have an adequate OS or ecosystem — and focus on their strengths…Nokia should have adopted Android-stock, and used their unmatched supply chain and distribution to do to their competitors, well, exactly what Nokia had been doing to their competitors for the last decade (if you think Samsung is running roughshod over everyone today, in 2007 they could only manage 41 million phones compared to Nokia’s 110 million).
Both BlackBerry and Nokia would have gotten a good OS and thriving ecosystem for free and been able to compete and differentiate themselves on the exact same vectors they had previously. To put it another way, RIM and Nokia had never been successful because of their OS or ecosystem, yet both decided their best response to iOS and Android was to build a new OS! In fact, the strategic superiority of the Android option for RIM and Nokia was even then so obvious that I suspect their core failing was not so much strategic as it was all-too-human: pride. Owning an ecosystem seems much more important than owning services or supply chains, even if building said ecosystem completely devalues what you’re actually good at.
If the first commonality in Microsoft and Nokia’s failure is the assumption that dominance in one paradigm would seamlessly translate into dominance in the next, then the second was in not making the strategically obvious choice — embracing iOS and Android for Windows, and Android for Nokia — for fear of losing control and long-term relevance. What separates the two companies is that Microsoft, under CEO Satya Nadella, rectified their mistake, while Nokia doubled-down with Windows Phone; that is why Microsoft still matters today — more than ever, in fact — while Nokia phones no longer exist.
The two companies that stood in contrast to Microsoft and Nokia were Google and Samsung; while their dominance of the non-iPhone market seems obvious in retrospect, it wasn’t at all pre-ordained. What is impressive about both companies is that they had the opposite of pride: both were quite shameless, in fact. From 2013’s Shameless Samsung:
Every pre-iPhone phone maker is irrelevant, if they even exist, except for Samsung, who is thriving. Samsung the copycat was smart enough to realize they needed to change, and quickly, and so they did.
Or maybe it wasn’t being smart. Maybe it was simply not caring what anyone else thought about them, their strategy, or their inspiration. Most successful companies, including Apple, including Google, seem remarkably capable of ignoring the naysayers and simply doing what is right for their company. In the case of smartphones, why wouldn’t you copy the iPhone? Nokia refused and look where that got them!
We, especially in the West, have a powerful sense of justice and fairness when it comes to product features and being first. Business, though, is not fair, even if it is more just than we care to admit.
Just as Samsung blatantly copied Apple hardware, Android blatantly copied the iOS interface:
Plenty of people mocked Google for this shift, but not me: Apple figured out what worked; it would have been foolish to not copy them.
Cook struck an optimistic tone, noting that Apple is typically late to promising new technologies. “We’ve rarely been first,” the executive told staffers. “There was a PC before the Mac; there was a smartphone before the iPhone; there were many tablets before the iPad; there was an MP3 player before iPod.” But Apple invented the “modern” versions of those product categories, he said. “This is how I feel about AI.”
Andy Jassy:
The first thing I would say is that I think it is so early right now in AI. If you look at what’s really happening in the space, it’s very top heavy. So you have a small number of very large frontier models that are being trained that spend a lot on computing, a couple of which are being trained on top of AWS and others are being trained elsewhere. And then you also have, I would say, a relatively small number of very large-scale generative AI applications.
We Will Serve Actual Use Cases
Tim Cook:
We see AI as one of the most profound technologies of our lifetime. We are embedding it across our devices and platforms and across the company. We are also significantly growing our investments. Apple has always been about taking the most advanced technologies and making them easy to use and accessible for everyone, and that’s at the heart of our AI strategy. With Apple Intelligence, we’re integrating AI features across our platforms in a way that is deeply personal, private, and seamless, right where users need them.
Andy Jassy:
We have a very significant number of enterprises and startups who are running applications on top of AWS’ AI services and but, like the amount of usage and the expansiveness of the use cases and how much people are putting them into production and the number of agents that are going to exist, it’s still just earlier stage than it’s going to be, and so then when you think about what’s going to matter in AI, what are customers going to care about when they’re thinking about what infrastructure use, I think you kind of have to look at the different layers of the stack. And I think…if you look at where the real costs are, they’re going to ultimately be an inference today, so much of the cost in training because customers are really training their models and trying to figure out to get the applications into production.
Our Chips Are Best
Tim Cook:
Apple Silicon is at the heart of all of these experiences, enabling powerful Apple Intelligence features to run directly on device. For more advanced tasks, our servers, also powered by Apple Silicon, deliver even greater capabilities while preserving user privacy through our Private Cloud Compute architecture. We believe our platforms offer the best way for users to experience the full potential of generative AI. Thanks to the exceptional performance of our systems, our users are able to run generative AI models right on their Mac, iPad, and iPhone. We’re excited about the work we’re doing in this space, and it’s incredibly rewarding to see the strong momentum building.
Andy Jassy:
At scale, 80% to 90% of the cost will be an inference because you only train periodically, but you’re spinning out predictions and inferences all the time, and so what they’re going to care a lot about is they’re going to care about the compute and the hardware they’re using. We have a very deep partnership with Nvidia and will for as long as I can foresee, but we saw this movie in the CPU space with Intel, where customers are anchoring for better price performance. And so we built just like in the CPU space, where we built our own custom silicon and building Graviton which is about 40% more price performance than the other leading x86 processors, we’ve done the same thing on the custom silicon side in AI with Trainium and our second version of Trainium2…it’s about 30% and 40% better price performance than the other GPU providers out there right now, and we’re already working on our third version of Trainium as well. So I think a lot of the compute and the inference is going to ultimately be run on top of Trainium2.
We Have the Data
Tim Cook:
We’re making good progress on a more personalized Siri, and we do expect to release the features next year, as we had said earlier. Our focus from an AI point of view is on putting AI features across the platform that are deeply personal, private, and seamlessly integrated, and, of course, we’ve done that with more than 20 Apple Intelligence features so far, from Visual Intelligence to Clean Up to Writing Tools and all the rest.
Andy Jassy:
People aren’t paying as close attention as they will and making sure that those generative AI applications are operating where the rest of their data and infrastructure. Remember, a lot of generative AI inference is just going to be another building block like compute, storage and database. And so people are going to actually want to run those applications close to where the other applications are running, where their data is. There’s just so many more applications and data running in AWS than anywhere else.
Both Apple and Amazon’s arguments are very plausible! To summarize each:
Apple:Large language models are useful, but will be a commodity, and easily accessible on your iPhone; what is the most useful to people, however, is AI that has your private data as context, and only we can provide that. We will provide AI with your data as context at scale and at low cost — both in terms of CapEx and OpEx — by primarily running inference on device. People are also concerned about sharing their personal data with AI companies, so when we need more capabilities we will use our own compute infrastructure, which will run on our own chips, not Nvidia chips.
Amazon:Large language models are useful, but will be a commodity, and widely available on any cloud. What is the most useful to companies, however, is AI that has your enterprise data as context, and more enterprises are on AWS than anywhere else. We will provide AI with a company’s data as context at scale and at low cost — both in terms of CapEx and OpEx — by primarily running inference on our own AI chips, not Nvidia chips.
What is notable about both arguments — and again, this doesn’t mean they are wrong! — is how conveniently they align with how the companies operated in the previous era. Apple powered apps with Apple Silicon on the edge with an emphasis on privacy, and Amazon powered apps in the cloud with its own custom architecture focused first and foremost on low costs.
The AI Paradigm
The risk both companies are taking is the implicit assumption that AI is not a paradigm shift like mobile was. In Apple’s case, they assume that users want an iPhone first, and will ultimately be satisfied with good-enough local AI; in AWS’s case, they assume that AI is just another primitive like compute or storage that enterprises will tack onto their AWS bill. I wrote after last fall’s re:Invent:
The emphasis on “choice” in the presentation, first in terms of regular AWS, and then later in terms of AI, is another way to say that the options are, in the end, mere commodities. Sure, the cutting edge for both inference and especially training will be Nvidia, and AWS will offer Nvidia instances (to the extent they fit in AWS’ network), but AWS’s bet is that a necessary component of generative AI being productized is that models fade in importance. Note this bit from Garman leading up to his Bedrock discussion:
We talked about wanting this set of building blocks that builders could use to invent anything that they could imagine. We also talked about how many of the cases we walked through today, that we’ve redefined how people thought about these as applications change. Now people’s expectations are actually changing for applications again with generative AI, and increasingly my view is generative AI inference is going to be a core building block for every single application. In fact, I think generative AI actually has the potential to transform every single industry, every single company out there, every single workflow out there, every single user experience out there…
This expansive view of generative AI’s importance — notice how Garman put it on the same level as the compute, storage, and database primitives — emphasizes the importance of it becoming a commodity, with commodity-like concerns about price, performance, and flexibility. In other words, exactly what AWS excels at. To put it another way, AWS’s bet is that AI will be important enough that it won’t, in the end, be special at all, which is very much Amazon’s sweet spot.
Go back to that illustration from The End of the Beginning: Apple and Amazon are betting that AI is just another primitive in continuous computing that happens everywhere.
The most optimistic AI scenarios, however, point to something new:
A better word for “Anywhere” is probably autonomous, but I wanted to stick with the “Where” theme; what I’m talking about, however, is agents: AI doing work without any human involvement at all. The potential productivity gains for companies are obvious: there is a massive price umbrella for inference costs if the end result is that you don’t need to employ a human to do the same work. In this world what matters most is performance, not cost, which means that Amazon’s obsession with costs is missing the point; it’s also a world where the company’s lack of a competitive leading edge model makes it harder for them to compete, particularly when there is another company in the ecosystem — Google — that not only has its own custom chip strategy (TPUs), but also is integrating those chips with its competitive leading edge large language model (Gemini).
Still, all of this is a stepping stone toward Cook’s grand vision, which hasn’t changed in a decade. He wants true augmented reality glasses — lightweight spectacles that a customer could wear all day. The AR element will overlay data and images onto real-world views. Cook has made this idea a top priority for the company and is hell-bent on creating an industry-leading product before Meta can. “Tim cares about nothing else,” says someone with knowledge of the matter. “It’s the only thing he’s really spending his time on from a product development standpoint.”
Still, it will take many years for true AR glasses to be ready. A variety of technologies need to be perfected, including extraordinarily high-resolution displays, a high-performance chip and a tiny battery that could offer hours of power each day. Apple also needs to figure out applications that make such a device as compelling as the iPhone. And all this has to be available in large quantities at a price that won’t turn off consumers.
What seems likely to me is that for this product to succeed, Apple will need to figure out generative AI as well; I posited last year that generative AI will undergird future user interfaces in The Gen AI Bridge to the Future. From a section recounting my experience with Meta’s Orion AR glasses:
This, I think, is the future: the exact UI you need — and nothing more — exactly when you need it, and at no time else. This specific example was, of course, programmed deterministically, but you can imagine a future where the glasses are smart enough to generate UI on the fly based on the context of not just your request, but also your broader surroundings and state.
This is where you start to see the bridge: what I am describing is an application of generative AI, specifically to on-demand UI interfaces. It’s also an application that you can imagine being useful on devices that already exist. A watch application, for example, would be much more usable if, instead of trying to navigate by touch like a small iPhone, it could simply show you the exact choices you need to make at a specific moment in time. Again, we get hints of that today through deterministic programming, but the ultimate application will be on-demand via generative AI.
In the very long run this points to a metaverse vision that is much less deterministic than your typical video game, yet much richer than what is generated on social media. Imagine environments that are not drawn by artists but rather created by AI: this not only increases the possibilities, but crucially, decreases the costs.
That may have also sounded fanciful at the time, but it’s already reality: just yesterday Google DeepMind announced Genie 3; from their blog post:
Today we are announcing Genie 3, a general purpose world model that can generate an unprecedented diversity of interactive environments. Given a text prompt, Genie 3 can generate dynamic worlds that you can navigate in real time at 24 frames per second, retaining consistency for a few minutes at a resolution of 720p.
[…] Achieving a high degree of controllability and real-time interactivity in Genie 3 required significant technical breakthroughs. During the auto-regressive generation of each frame, the model has to take into account the previously generated trajectory that grows with time. For example, if the user is revisiting a location after a minute, the model has to refer back to the relevant information from a minute ago. To achieve real-time interactivity, this computation must happen multiple times per second in response to new user inputs as they arrive…
Genie 3’s consistency is an emergent capability. Other methods such as NeRFs and Gaussian Splatting also allow consistent navigable 3D environments, but depend on the provision of an explicit 3D representation. By contrast, worlds generated by Genie 3 are far more dynamic and rich because they’re created frame by frame based on the world description and actions by the user.
We are still far from the metaverse, to be clear, or on-demand interfaces in general, but it’s stunning how much closer we are than a mere three years ago; to that end, betting on current paradigms may make logical sense — particularly if you dominate the current paradigm — but things really are changing with stunning speed. Apple and Amazon’s risk may be much larger than either appreciate.
Google Appreciation
Genie 3 is, as I noted, from Google, and thinking about these paradigm shifts — first the shift to mobile, and now the ongoing one to AI — has made me much more appreciative and respectful of Google. I recounted above how the company did what was necessary — including overhauling Android to mimic iOS — to capture its share of the mobile paradigm; as we approach the three year anniversary of ChatGPT, it’s hard to not be impressed at how the company has gone all-in on relevancy with AI.
This wasn’t a guarantee: two months after ChatGPT, in early 2023, I wrote AI and the Big Five, and expressed my concerns about the company’s potential disruption:
That, though, ought only increase the concern for Google’s management that generative AI may, in the specific context of search, represent a disruptive innovation instead of a sustaining one. Disruptive innovation is, at least in the beginning, not as good as what already exists; that’s why it is easily dismissed by managers who can avoid thinking about the business model challenges by (correctly!) telling themselves that their current product is better. The problem, of course, is that the disruptive product gets better, even as the incumbent’s product becomes ever more bloated and hard to use — and that certainly sounds a lot like Google Search’s current trajectory.
I’m not calling the top for Google; I did that previously and was hilariously wrong. Being wrong, though, is more often than not a matter of timing: yes, Google has its cloud and YouTube’s dominance only seems to be increasing, but the outline of Search’s peak seems clear even if it throws off cash and profits for years.
Meanwhile, I wasn’t worried about Apple and Amazon at all: I saw AI as being a complement for Apple, and predicted that the company would invest heavily in local inference; when it came to Amazon I was concerned that they might suffer from not have an integrated approach a la Google, but predicted that AI would slot in cleanly to their existing cloud business. In other words, exactly what Apple and Amazon’s executives are banking on.
I wonder, however, if there is a version of this analysis that, were it written in 2007, might have looked like this:
Nokia will be fine; once they make a modern OS, their existing manufacturing and distribution advantages will carry the day. Microsoft, meanwhile, will mimic the iPhone UI just like they once did the Mac, and then leverage their app advantage to dominate the lower end of the market. It’s Google, which depends on people clicking on links on a big desktop screen, that is in danger.
I don’t, with the benefit of having actually known myself in 2007, think that would have been my take (and, of course, much of the early years of Stratechery were spent arguing with those who held exactly those types of views). I was, however, a Google skeptic, and I’m humble about that. And, meanwhile, I have that 2023 Article, where, in retrospect, I was quite rooted in the existing paradigm — which favours Apple and Amazon — and sceptical of Google’s ability and willingness to adapt.
Today I feel differently. To go back to the smartphone paradigm, the best way to have analysed what would happen to the market would have been to assume that the winners of the previous paradigm would be fundamentally handicapped in the new one, not despite their previous success, but because of it. Nokia and Microsoft pursued the wrong strategies because they thought they had advantages that ultimately didn’t matter in the face of a new paradigm.
If I take that same analytical approach to AI, and assume that the winners of the previous paradigm will be fundamentally handicapped in the new one, not despite their previous success, but because of it, then I ought to have been alarmed about Apple and Amazon’s prospects from the get-go. I’m not, for the record, ready to declare either of them doomed; I am, however, much more alert to the prospect of them making wrong choices for years, the consequences of which won’t be clear until it’s too late.
And, by the same token, I’m much more appreciative of Google’s amorphous nature and seeming lack of strategy. That makes them hard to analyse — again, I’ve been honest for years about the challenges I find in understanding Mountain View — but the company successfully navigated one paradigm shift, and is doing much better than I originally expected with this one. Larry Page and Sergey Brin famously weren’t particularly interested in business or in running a company; they just wanted to do cool things with computers in a college-like environment like they had at Stanford. That the company, nearly thirty years later, is still doing cool things with computers in a college-like environment may be maddening to analysts like me who want clarity and efficiency; it also may be the key to not just surviving but winning across multiple paradigms.
OpenAI’s latest reported change being considered to ChatGPT is drawing a wide-range of strong reactions from users.
The ever-evolving world of artificial intelligence features frequent updates to tools, often including new models and features. However, the latest chatter surrounding the biggest name in AI is a potential change that would almost certainly spark immense user pushback. While OpenAI has rolled out several updates to ChatGPT and most recently launched their new browser ChatGPT Atlas, the latest reported change being considered has all the makings of a financial decision.
Although streaming giants such as Netflix, Hulu and Amazon Prime Video land in a somewhat different area of the technology landscape, they may soon have something in common with ChatGPT—ads.
OpenAI Reportedly Considering Bold Change to ChatGPT by Integrating Ads
Although nothing has been confirmed yet, The Information reportedly stated that OpenAI is considering integrating advertisements into ChatGPT. The report, as Culture Crave revealed, also says that the company is exploring the possibility of basing the ads shown on ChatGPT on user chat memory.
It’d be a major move, and one that would likely lead to pushback from a large share of ChatGPT users. However, it’s unclear whether users who pay for a higher-tier AI tool would be excluded from seeing advertisements. If that were the case, it would avoid at least some of the general pushback against the possible move.
It sounds as though the idea is still in its early stages at OpenAI, but as we’ve seen in the world of artificial intelligence, things can move quickly. Regardless of whether it happens or not, the responses to the report poured in, and it’s fair to say they didn’t include much positivity.
ChatGPT Users & Others React to OpenAI Possibly Integrating Advertisements
Although the negative comments far outweighed the positive regarding the news, there was a fair mixture of comedy as well. In some cases, the comedic reactions prompted real questions about how OpenAI would roll out these ads.
“Imagine if the AI responded like in ads: ‘Great question! But before I answer, let me tell you about today’s sponsor – NordVPN,’” one user wrote.
Among the several noteworthy responses that poured in, a few key takeaways included:
Opinions that this will hurt the brand
Possibilities of a subscription fee to avoid the advertisements
Frustration over the inability to use many types of technology without ads
Pushback stating that if the ads were integrated into paid ChatGPT subscriptions, some would cancel their accounts
While this is comical to consider, it would also be a legitimate worst-case scenario for users. However, it’s hard to envision OpenAI choosing this path for integrating ads into ChatGPT, a tool that prides itself, at least in part, on speed.
Another user responded jokingly, pointing to ChatGPT monetizing their “late-night rants about cat conspiracy theories.”
“Oh, brilliant! Now ChatGPT can monetize my late-night rants about cat conspiracy theories with perfectly timed cat food ads. Truly living the dream in this brave new ad-infested world!”
The possible move from OpenAI also sparked confusion among users about why they’d even consider it over continuing to build something bigger.
“Why don’t they just focus on building superintelligence? It’s way bigger than ads, lmao, and it’s not like they’ll run out of funding anytime soon,” said one user.
“Because as we all know, putting ads on stuff doesn’t immediately tank anything in lieu of an ad-less version,” replied another user. “After putting ads on it they’ll bring out a small subscription fee to remove them. Make everything worse, charge to restore it.”
Others raised concerns about OpenAI using chat history for the ads.
“Using our chat history for advertisements is absurd. This is essentially the quickest way to discourage people from using ChatGPT,” read another reply.
Regardless of what aspect of the possibility that ads could be integrated into ChatGPT they were most concerned with, it appears that the feeling is mostly a widespread consensus.
With the launch of GA4, Google has put in place its biggest change to analytics in the company’s 21-year history. The new system unifies the measurement of apps and websites and is intended to provide marketers with a far more detailed understanding of their campaigns.
Fifty-five London waxes lyrical on the potential of GA4.
As it is set to replace the older version of Google Analytics, digital marketers should develop a plan now for fully implementing it. Here are six things you need to know about the new system.
1. It is built for the mobile-first era
Google Analytics has been around for 21 years and was built with desktop websites in mind. But in today’s mobile-first environment, the insights we need are different. Apps have been the catalyst to transform how we consume information on mobile by providing brands with controlled content environments. GA4 combines data from the two sources into a single suite. Although this was possible before, GA4 has introduced a new framework to make this far more practical and intuitive. This enables us to glean richer insights with customers behaving very differently across apps and websites.
2. It’s not just about app and web measurement
Google’s new platform was initially named App+Web. However, the new system isn’t just about analysing data from mobile apps and websites in one screen. GA4 will become the new version of Google Analytics. However the new product has different and more advanced capabilities than Universal Analytics. It uses machine learning based automated insights, new report types and improved data sampling behaviour to provide actionable insights. This will enable practitioners to develop more sophisticated and personalised customer experiences and journeys. This will also apply even if they are just focusing on website data.
3. Events are the new building block
The old product was based on the idea that people have ‘sessions’ and ‘page views’. This was behaviour compatible with a web and content-focused approach. GA4 takes a radically different approach, looking at user behaviour through a different lens. It replaces page views and sessions with a building block called an ‘event’. This could refer to a variety of different behaviours. It could still be a ‘page view’ to understand how people consume content. However it could also be people completing a specific series of actions, like a funnel. Therefore, it is more suited to the way modern brands want to engage with their customers. It represents a fundamental change in the framework of how we measure people doing things.
4. It enables more advanced personalisation
The platform can be coupled with other Google products including the Google Marketing Platform, Google Ads and its personalisation platform – Google Optimize. This will enable marketers to glean new machine learning led insights about individual behaviour. Currently, Google Analytics based audiences in Optimize take several minutes to be processed and calculated. The new data model enables this in a matter of seconds. Additionally previously challenging analyses, for example segment overlaps or user journey pathing, can now be built in a matter of minutes thanks to the new Analysis section of the platform. GA4 also means better calculation of audiences and the ability to serve ads to these audiences at a cross-device and cross-platform (web & app) setting. This is of course provided that the advertisers have the required consent on multiple devices.
5. Don’t delete your old analytics yet…
Despite its potential, it is important to work with the right experts to unlock the system’s potential. Part of this is setting up the right parameters. Like with any new system, upgrades are occurring each quarter which are then being refined and improved as result of user feedback. It is critical to manage expectations as to what can be achieved. Although GA4 is a massive step in the right direction, there are some features missing that exist in Universal Analytics. This includes important marketing analytics functions such as multi-channel funnels and data-driven attribution. Therefore you should retain access to the old Universal Analytics and GA4. This will be crucial for year on year reports for a holiday season comparison for example.
6. It presents an improved suite of privacy & consent options
There have been significant changes to privacy regulations and more importantly, the public’s awareness of how their data is used, since the inception of Google Analytics 21 ago. Google is working on a new suite of features to ensure compliance with modern privacy regulations that will be applicable to GA4. This ranges from region-specific audience personalisation settings to their new Consent Mode product. We can expect GA4 to receive continuous improvements on this front.
By engaging with the platform now, digital marketers can get a head start on competitors by truly realising its potential. With GA4 set to become the mainstream Google Analytics platform in 2021 there is no time to waste.
Controversial brands, campaigns or rebrands tend be the ones we remember. We’re all still talking about Cracker Barrel and Jaguar after all. But what happens when the controversy works in a brand’s favour?
What about when a brand does something so bold is ends up skewing public opinion towards it?
Here are eight examples of when it works, chosen by Patrick Dillon from WISE Digital Partners, a digital marketing agency.
01. Nike – Dream Crazy
‘Dream Crazy’ – Colin Kaepernick Nike Ad 2019 – YouTube
American football star Colin Kaepernick taking the knee at an NFL game in protest at police brutality was a landmark political event of the 2010s. And to reflect this growing movement, Nike released Dream Crazy, with the slogan ‘Believe in something, even if it means sacrificing everything’ and Kaepernick as its star.
Because of Kaepernick’s political affiliations, the ad was seen by some as anti-American, and protests soon erupted with the hashtag #JustBurnIt seeing people burn their shoes.
However, this turned out not to be the disaster some predicted, as Nike’s online sales surged by 31 per cent.
“Nike understood that controversy can clarify a brand’s identity,” says Patrick. “They didn’t chase everyone’s approval; instead, they strengthened their bond with those who shared their values.”
In 2015, everyone was talking about this billboard. Not because it was one of the best billboards around, but because of its controversial message ‘Are you beach body ready?’ paired with an image of a woman in a bikini.
The advert was accused of promoting unrealistic beauty standards and ads were vandalised and penalised across England’s capital.
But… the outrage drove awareness, and Protein World reported profits of around £1 million from a £250,000 spend.
“While the message was tone-deaf, the conversation it started dominated headlines,” says Patrick. “Controversy multiplied Protein World’s exposure at a fraction of the cost of traditional advertising.”
Benetton is no stranger to controversial ads but its 2011 Unhate campaign, which showed world leaders kissing (including the Pope) took things to another level. The Vatican condemned it, governments demanded its removal, and some citizens tore down posters.
Benetton refused to apologise, and the campaign ended up winning a Cannes Lions award. The brand’s stance reinforced its identity as a provocateur unafraid to challenge global politics through art.
04. Pot Noodle – Nothing Satisfies like Pot Noodle
Last year, a UK commercial for Pot Noodle caused a wave of disgust to sweep the nation. It featured an exaggerated slurp noise that caused many to cringe/mute their TVs.
People complained and the brand responded with a tongue-in-cheek “apology” campaign and a quieter version of the ad.
“Humour can disarm outrage. Pot Noodle leaned into the criticism rather than retreating, and the controversy boosted engagement massively,” says Patrick.
Burger King isn’t exactly known for making huge political statements, but its Whopper Neutrality advert took on the thorny issue of net neutrality. In the ad, customers were told they needed to pay extra to get their Whopper faster, mimicking what internet slowdowns could look like without regulation.
The concept was divisive but the brand racked up over 4.6 million YouTube views and 127k likes.
“Burger King showed that controversy doesn’t always need to offend; it can challenge,” says Patrick. “It’s a fantastic example of how good advertising can translate a complex policy issue into something everyone can understand.
06. Gillette – The Best Men Can Be
Commercial Ads 2019 – Gillete – The best men can be – YouTube
While some viewed the ad as progressive, others found it patronising.
But in terms of numbers, the ad was a success, racking up more than 30 million views. “Gillette reframed its heritage slogan for a new cultural moment, expanding the brand’s appeal among socially conscious millennials,” says Patrick.
It’s not easy to market a toilet spray, but Poo-Pourri won audiences by embracing blunt humour.
Its viral video featured a well-dressed woman candidly discussing “dropping the motherload.” The brand got over 40 million YouTube views and became a household name overnight.
“Humour, honesty, and the willingness to say what others won’t became the winning formula,” says Patrick. “Poo-Pourri proved that relatability beats refinement when talking about awkward products.”
During heated political debate over immigration, Budweiser aired a Super Bowl ad chronicling its founder’s immigrant journey. Some saw it as a subtle critique of travel bans; others viewed it as a patriotic reminder of the American dream.
The ad went viral with over 21 million views in three days.
“Budweiser reminded Americans that every brand has a story rooted in human ambition; the message resonated because it felt real and sincere, not opportunistic,” says Patrick.
Rosie Hilder is Creative Bloq’s Deputy Editor. After beginning her career in journalism in Argentina – where she worked as Deputy Editor of Time Out Buenos Aires – she moved back to the UK and joined Future Plc in 2016. Since then, she’s worked as Operations Editor on magazines including Computer Arts, 3D World and Paint & Draw and Mac|Life. In 2018, she joined Creative Bloq, where she now assists with the daily management of the site, including growing the site’s reach, getting involved in events, such as judging the Brand Impact Awards, and helping make sure our content serves the reader as best it can.
When James Watt talks about advertising, he sounds less like the founder of billion dollar beer brand BrewDog and more like a man ready to take on a trillion-dollar industry.
“Advertising hasn’t really evolved in a century,” he says. “It’s still this one-to-many model, brands spending huge amounts of money to get exposure and hoping something sticks. But we see between 4,000 and 10,000 ads a day now. The more we see, the less impact they have.”
Watt’s new venture, Social Tip, launched just 14 weeks ago, is his attempt to rewrite that playbook. Instead of paying influencers or pouring more money into digital ads, Social Tip turns everyday customers into brand advocates and pays them cash when they post about the products they genuinely love.
It’s a simple but radical idea. And one that might hint at where the future of advertising is headed.
From Beer To Brand Democracy
After 17 years growing BrewDog into one of the UK’s most recognizable consumer brands, Watt says he wanted to build something that redefines how marketing works.
“I love building businesses,” he says. “But I’m even more passionate about marketing and community. Peer-to-peer influence is where the future of that lives.”
The irony, he adds with a grin, is that his wife is an influencer. “So I’ve launched a company that, if successful, might just put her out of a job.”
Social Tip’s model is disarmingly simple. When a user buys from one of the platform’s 350 partner brands — including Unilever, HelloFresh, MyProtein, and Marks & Spencer — they can share a post about the product on TikTok or Instagram. Social Tip’s algorithm analyses reach, engagement and content quality, then pays users an average of £5.60 ($7.50) per post directly into their account.
Brands, meanwhile, gain a steady stream of authentic user-generated content (UGC) and measurable exposure. “We’re seeing CPMs of about $7,” Watt says. “Traditional influencer campaigns are five times this. So it’s massively more efficient and the money goes back to customers, not platforms.”
Authenticity Over Influence
At the core of Watt’s thesis is a belief that authenticity has become the rarest currency in marketing.
“If you’ve got 200 followers and a private Instagram account, that’s fine,” he says. “If you share something that fits naturally into your life, that’s where the magic happens.”
The platform’s user base has grown to 50,000 in just a few months. Some have hundreds of followers; others have hundreds of thousands. The common denominator is genuine enthusiasm.
His favourite example isn’t a multinational brand but a neighbourhood café. “There’s a small place in my village called Coffee Apothecary,” he says. “They put £200 into their Social Tip account, and suddenly the whole community was posting about them. It works for huge global brands and tiny independents alike.”
The vision, Watt says, is to make having a Social Tip presence as fundamental to a brand as having an Instagram page. “Ten years ago, Instagram was a competitive advantage,” he says. “Now it’s table stakes. I want Social Tip to be the same.”
James Watt, co-founder of BrewDog and founder of Social Tip
A Change In Consumer Trust
Social Tip’s timing is deliberate. Consumers are tuning out traditional ads, and marketers are struggling to keep pace with fragmented attention.
Kantar’s Media Reactions 2024 study found that people trust peer recommendations and word-of-mouth far more than social-media or streaming ads. Meanwhile, Nielsen’s 2024 Annual Marketing Report revealed that while 72 percent of marketers expect higher ad budgets this year, only 38 percent measure their digital and traditional channels together, a clear sign that legacy models aren’t keeping up with behaviour.
“Community is the new media,” Watt says. “People don’t trust ads. They don’t trust influencers. They trust people they know. Social Tip takes that timeless truth and makes it scalable.”
He’s careful, though, to position the company as a complement for traditional marketing. “We’re not the hero in any Social Tip story,” he says. “The hero is the customer and the brand. We’re just the connection.”
Early Results And Expansion Plans
Since its launch, Social Tip has paid out over £150,000 ($201,000) to users and partnered with hundreds of consumer brands. The company recently began testing in the U.S., starting with 10 businesses and 500 users, with plans to scale rapidly in 2025.
Watt admits that building a new model comes with challenges. “Any startup is hard, and disruption never comes easy,” he says. “But the early signs are phenomenal.. real engagement, real ROI, real excitement.”
He also sees the platform as part of a wider movement toward shared value in marketing. “We want to shorten the bond between brands and customers,” he says. “If you love a brand and you talk about it, that brand should share some of its value back with you. That’s the future.”
Expert Take: What This Means For Marketers
As someone who studies the evolution of the creator economy, what strikes me about Social Tip is how it reframes influence as infrastructure, not entertainment. We’ve spent years optimizing for followers and reach; now the real opportunity lies in community credibility and authentic micro-advocacy.
The next wave of marketing innovation will come from building systems that let brand love scale organically. In a fragmented world, trust is the true growth channel.
The Bottom Line
Advertising as we know it is evolving. In a world oversaturated with content and skepticism, the most powerful voices will be the ones with the most authenticity.
As Watt puts it, “If you can make customers feel like partners, not targets, that’s when marketing really works.”
And if Social Tip is right, the future of advertising might belong to regular people, posting about what they love.
This article is based on an interview with James Watt from my podcast, The Business of Creators.
One last debacle for the messiest rebrand of the decade.
The fact that people still refer to Elon Musk‘s social media platform as ‘X, formerly known as Twitter’ over two years later perhaps isn’t a sign of a brilliantly successful rebrand. Back in 2023, we called Twitter’s X-orcism a “masterclass in how to destroy a brand overnight”.
But perhaps one of the main reasons for the bird name sticking around is that the URL, twitter.com never went away. Until now. X has finally announced that is doing away with the original domain – and right now it’s redirecting to X.com. But like every aspect of this cursed rebrand, it hasn’t gone smoothly.
Twitter (left) is finally no more (Image credit: Twitter)
The changing of the URL has proven messy for those using a security key for two-factor authentication, with many finding themselves locked out of their account. In a statement, X asked users to re-enrol their devices – but the tweet (yes, I’m still calling it a tweet) has received hundreds of comments from users complaining that they can no longer access their accounts.
It seems X’s commitment to remaining the decade’s messiest (and slowest) rebrand is unwavering. From constant logo tweaks to algorithm problems, plus the ongoing debacle of giving Verified badges to anyone willing to pay for the privilege, the whole enterprise has given rise to a catalogue of errors.
So while the death of the Twitter URL might seem like the final nail in the coffin for one of the 2010s’ most iconic online brands, knowing the way this rebrand has been playing out, it’ll probably be back tomorrow.
Daniel John is Design Editor at Creative Bloq. He reports on the worlds of design, branding and lifestyle tech, and has covered several industry events including Milan Design Week, OFFF Barcelona and Adobe Max in Los Angeles. He has interviewed leaders and designers at brands including Apple, Microsoft and Adobe. Daniel’s debut book of short stories and poems was published in 2018, and his comedy newsletter is a Substack Bestseller.
Coca-Cola has rolled out its second AI-generated holiday ad campaign, featuring its iconic trucks.
Eagle-eyed viewers have noticed glitchy inconsistencies.
The studio behind the ad said Coke is pioneering AI, “rather than waiting for it to be 100% ready.”
Coca-Cola’s holiday trucks are coming — but thanks to AI, they’re causing some viewers to double-take.
This week, the soda giant unveiled three ads that will form part of its 2025 holiday campaign. One of the ads — an AI-generated remake of its iconic 1995 “Holidays are Coming” spot — has some glitchy inconsistencies.
Look closely, and you’ll see the famous Coca-Cola trucks appear to change shape as they roll through the festive village. The trucks also appear to gain or lose wheels in each scene.
Dino Burbidge, an independent innovation specialist, created this handy graphic to help you follow along:
Coca-Cola’s holiday trucks looked a little different in each scene. Dino Burbidge
Other viewers also noticed other apparent inconsistencies, including a concerning moment at the 50-second mark when a truck appears to be on a collision course with a crowd of onlookers.
“I really miss pre-AI internet,” reads one comment under the YouTube video.
Coca-Cola’s wobbly Christmas trucks highlight one of the biggest shortcomings of generative video models: the tech often struggles to maintain the consistency of characters and objects between multiple shots. Many systems generate video on a frame-by-frame basis without maintaining a strong memory of prior scenes, resulting in temporal drift — although some newer models claim to have solved this problem.
The lack of continuity is often one of the biggest giveaways that a video is inauthentic.
Marketers and the broader advertising industry have quickly adopted AI as a means to expedite production times and reduce costs. However, the industry’s adoption of the technology has also led to concerns about job losses and an overall decline in the quality of advertising. Recent research has found that some consumers have an aversion to AI-generated ads, especially those that feature human faces.
Coca-Cola didn’t respond to Business Insider’s requests for comment.
“There will be people who criticize — we cannot keep everyone 100% happy,” Pratik Thakar, Coca-Cola’s global VP and head of generative AI, said in an interview with The Hollywood Reporter this week. “But if the majority of consumers see it in a positive way, it’s worth going forward.”
In a behind-the-scenes video posted to Coca-Cola’s YouTube channel on Monday, the company said just five AI specialists refined 70,000 video clips to create the ad in 30 days, using tools such as OpenAI’s Sora, Google’s Veo 3, and Luma AI. There were some tweaks in post-production, the video said.
Silverside AI, an AI innovation lab backed by the ad agency Pereira O’Dell, worked with Coca-Cola to produce the 2025 “Holidays are Coming” spot.
“Coca-Cola became a pioneer in this space because, once they recognized AI as the future, they stopped debating whether it’s perfect or not — and instead focused on how to use it in the best, most creative way possible,” PJ Pereira, cofounder of Pereira O’Dell & Silverside AI, told Business Insider in a statement.
“When the world is evolving this fast, we need brands with the kind of leadership Coca-Cola shows, pushing technology and craft forward rather than waiting for it to be 100% ready,” Pereira said. He added that the ad had “already tested incredibly” well.
Never mind the critics — does the ad do its job?
System1, which rates ads on a scale from 1 to 5.9 stars on their potential to drive long-term growth for brands, gave the 2025 “Holidays are Coming” ads the highest possible score: 5.9. The research company asks a panel of consumers across several countries to indicate how they feel about the ad they’re viewing from a list of emotions ranging from contempt and disgust to happiness and surprise.
“While generative AI played a role behind the scenes, what truly shines through is Coca-Cola’s commitment to emotional storytelling and creative consistency,” said Vanessa Chin, System1’s senior vice president of marketing. “It’s a powerful reminder that when a brand understands its audience and honours what works, the results speak for themselves.”
DAIVID, another creative testing platform that measures viewer emotions, said the “Holidays are Coming” ad was slightly less likely (2.1%) to generate positive emotions and more likely to evoke feelings of distrust (2%) than the industry norms. However, it did generate higher-than-average attention and brand recall scores, which a DAIVID spokesperson said was likely because Coca-Cola ads are very distinctive.
Coca-Cola’s 2024 AI-generated holiday campaign also drew a polarizing response. One of the videos — another take on the classic trucks ad — was widely panned online as AI slop, with critics picking up on details like the wheels gliding across the floor instead of spinning and the eerie-looking AI “humans” smiling creepily.
In an interview with Ad Age last year, Thakar said of the 2024 ad that consumers don’t look at AI campaigns in the same way creative directors do. “Consumers were not concerned about AI versus non-AI,” Thakar said.
Burbidge, the innovation specialist who posted online about the faulty wheels on Coca-Cola’s AI trucks, said in an interview with Business Insider that the production issues in Coca-Cola’s campaigns were inexcusable and that the company risks damage to its brand.
“Is this the slippery slope that previously trusted media and production values will go down because ‘consumers don’t care’?” Burbidge said. “Craft, creativity, and quality should hold true. As soon as we let that go, who’s going to fight for it?”
The promised AI revolution in shopping is starting to materialise, with shoppers increasingly trusting agents for personal recommendations ahead of the festive season.
Traffic to retail sites from AI tools is expected to surge fivefold year-over-year, with particular boosts on Cyber Monday and Black Friday, according to Adobe.
“Traditional models of how consumers react with the web are going out the window,” Max Sinclair, Azoma CEO, said.
“Intelligent assistants begin to handle browsing, recommendations and purchasing on behalf of users.”
PayPal launched agentic commerce with ChatGPT, Perplexity, Gemini, and several technology partners last month, while OpenAI launched its ‘Buy it in ChatGPT’ trial in the US in September.
Efficiency and ease of payment are a cornerstone of the shift: Alex Chriss, PayPal’s CEO, said that he wants to “help people go from chat to checkout in just a few taps”.
Ellie Tuck, creative director and partner at FleishmanHillard, a PR agency, had told City AM that AI is “one of the biggest shifts we’re seeing in how brands show up in the world”.
However, despite the popularity of ChatGPT and other Gen AI models, there’s still one key sticking point: traffic has yet to translate into purchases.
Brits ‘not ready’ to hand over full control
AI-driven traffic is still around a quarter less likely to convert into purchases than traditional traffic, but this is easing: The figure was 38 per cent in April and 49 per cent in January.
AI tools are “making it easier than ever” for consumers to discover, research and buy new products and services, but they can “just as easily turn people away”, Carrie Ryan, chief strategy officer at Trustpilot, said.
Crucially, consumers are concerned about data privacy and sharing, as well as the lack of a human touch, she explained.
“Trust is the currency,” she said, adding that user-generated reviews are crucial and that AI is best suited to product summaries, automatic checkout agents and fraud detection.
“Shoppers still want to maintain control,” Nabil Manji, head of FinTech growth at Worldpay, added.
“AI shopping assistants are… changing how we discover and buy the things we love [but] retailers need to be ready to meet shoppers where they are.”
‘The next frontier’ for retail
The rise of AI shopping comes as brand loyalty is eroding and price points become ever-more important to shoppers, making deal-finding and efficiency the ripest area for AI innovation.
Consumers are already more likely to use AI to find deals than for general purchases, with two-thirds of UK shoppers planning to use AI for holiday shopping, according to Shopify.
“The most successful businesses will pair AI-powered personalisation with transparent controls and easy access to human support,” the Shopify report found.
“The message is clear: there is scope for more AI adoption, and brands that balance tech‑enabled personalisation with human service will have the strongest advantage.”
Whether Brits are fully ready or not, AI is already infiltrating every area of retail, with all trends indicating increased adoption.
“Agentic commerce is not a theory anymore,” said Roy Avidor, CEO of Symbio. “It is the most significant change in online retail architecture in two decades, and it can only happen when merchants, AI, and payment data are partnering in a symbiotic manner.”
Roman Stanek, founder and longtime CEO at GoodData, said that agentic commerce is “the next frontier for retailing”.
“That’s a massive shift and it is here today… OpenAI wants to insert itself between brands and customers, and that’s both an existential threat and a once-in-a-generation opportunity. The smartest brands won’t fight it – they’ll build their own agents and ecosystems to stay in control”.
Netflix has done away with the “monthly active users (MAU)” metric, which is widely used across ad-supported streaming, and has switched to capturing viewership as “monthly active viewers (MAV),” which it defines as subscribers watching at least one minute of ads on Netflix per month, multiplied by how many people are watching in a given household. “Our move to viewers means we can give a more comprehensive count of how many people are actually on the couch, enjoying our can’t-miss series, films, games and live events with friends and family,” the company explained in a blog post, via Deadline.
With a new metric comes a new viewership milestone, as Netflix has reported that it now reaches more than 190 million MAVs on its ad-supported tier. Given the metric change, it’s hard to know exactly how big a jump that is from the 94 million MAUs Netflix stated it had back in May, although the streamer did note that MAUs were tied to account profiles and therefore undercounted co-viewing, a factor that the new MAV metric addresses.
Netflix Has Offered an Ad-Tier Since 2022
Despite being initially against advertising, as competition in the streaming market grew, Netflix announced plans for an ad-tier in 2022, which was rolled out that November. With the three-year mark having just passed, Netflix is gearing up for an even bigger 2026, with the company currently testing out a new interactive video ad format in North America that is geared to each subscriber’s individual viewing behaviour. This new format has reportedly been well-received and will be rolled out globally by Q2 2026.
Netflix remains the biggest streaming service in the world, with an estimated 302 million subscribers. Despite facing stiffer competition now than it did during its first decade as a streaming service, Netflix has continued to grow its subscriber base by offering several crowd-pleasing and/or award-winning original series like House of Cards, Stranger Things, The Witcher, and Squid Game. The company has also been able to attract top-tier talent to its platform, such as television powerhouses Shonda Rhimes (Grey’s Anatomy, Bridgerton) and Ryan Murphy (Glee, Monster, Ratched).
Upcoming movies that Netflix subscribers will want to keep an eye out for include the Once Upon a Time in Hollywood sequel The Adventures of Cliff Booth, Greta Gerwig’s Narnia reboot The Magician’s Nephew, and Brad Bird’s long-gestating animated passion project Ray Gunn. On the TV side, subscribers have new seasons of Stranger Things, Virgin River, Outer Banks, and Bridgerton to look forward to, as well as a live-action take on Scooby-Doo, a new adaptation of Little House on the Prairie, and an Assassin’s Creed series.
