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Remember how much fun it was to shop on the internet a decade ago? If you visited the Goop website, Gwyneth Paltrow might introduce you to her favorite $75 candle or $95 vibrator. If you were looking for a lasagne recipe, you could find a good one on Food52along with recommendations for a baking dish hand-selected by former New York Times food editor Amanda Hesser. Watch-lovers flocked to Hodinkee to see what founder Benjamin Clymer thought of the cool new Longines or Omega timepiece (with a handy link to buy it, in case you really liked it). At their peak, around five years ago, all of these media companies landed millions of dollars in venture capital and had valuations well into the nine figures. Legacy media ranging from the New Yorker to Vogue took a page from their book, too, linking to products you could buy directly from the pieces published on their websites. Gwyneth Paltrow and Kerry Washington speak during a live recording of the Goop podcast, September 19, 2019 [Photo: Stefanie Keenan/Getty Images for Goop] But over the last two years, this generation of content-to-commerce pioneers has fizzled out. Goop has gone through multiple rounds of layoffs and its website is a shell of what it used to be. In 2024, Hodinkee was sold at a fraction of its former valuation. And last month, Food52 declared bankruptcy and is headed towards a fire sale. It’s worth asking what happened to these startupsand what comes next, as AI transforms the way we shop online. The rise and fall of Food52 The rise and fall of Food52 offers insight into what went wrong with the content-to-commerce model. Founders Amanda Hesser and Merrill Stubbs had come from the traditional food media. They saw a gap between legacy magazines like Bon Appétit and Food & Wine, which prioritized the perspectives of elite chefs, and amateur food blogs, which were flooding the internet. With Food52, they invited home cooks to submit recipes, which their team would test. The best ones would be featured on the site, alongside beautiful photography. The concept resonated and site traffic grew quickly. Initially, the company generated revenue from advertising and brand partnerships. But in 2013, the site launched a shop that sold kitchenware and artisanal ingredients that Food52 staffers recommended. This approach made sense says Dan Frommer, founder of The New Consumer. One of the biggest problems with shopping online is the overwhelming volume of products available. First generation content-to-commerce startups offered expertise and a point of view, which gave them the authority to recommend products. “They were offering curation, which was a valuable service at the time,” he says. No-Bake Granola Bars from the Food52 Vegan’s cookbook by Gena Hamshaw, ca. 2015. [Photo: Melissa Renwick/Toronto Star/Getty Images] Goop and Hodinkee followed similar trajectories. They began as blogs centered around a particular perspective and aspirational lifestyle, driven by their well-known founders. Over time, they built up enough trust with their readers to sell them products. (Food52 declined to comment on the story. We reached out to Goop and Hodinkee, but neither got back to us by the time of publication.) In 2019 and 2020, investors still believed this might be the future of retail. They pumped millions into their startups to grow their audiences, start new revenue streams like events, and start their own product lines. Food52, for instance, was valued at $300 million in 2021, after an $80 million investment from TCG (which also invested in Hodinkee). But this funding may have inadvertently led to their decline. With the influx of cash, these startups had a mandate to scale, but they all struggled to grow sustainably. By the start of this year, Food52 had declared bankruptcy. America’s Test Kitchen has reportedly agreed to buy it for $6.5 million, of which $3.42 million is Chapter 11 financing. Frommer argues that there were many idiosyncratic reasons why each of these companies failed. Food52, for instance, appeared to have bitten off more than it could chew. In 2019, it launched its own in-house kitchenware line; it also acquired two entirely new companies, the Danish cookware brand Dansk and the lighting brand Schoolhouse. “There was a lot wrong with the business,” Frommer says. “There were failures in strategy and execution.” But taking a step back, it’s clear that there were also broader issues with the content-to-commerce model that affected all of these businesses. What Didn’t Workand What Did Theseearly content-to-commerce platforms accurately identified that consumers were overwhelmed with the avalanche of products available on the internetand they also knew that taste could be monetized. Still, there were flaws with their model. For one thing, consumers often didn’t come to these websites with the intent to shop. They were there to take in the content: the recipes, listicles of clean beauty products, or a conversation with Ed Sheeran about his favorite watches. Only a small proportion of consumers would feel compelled to buy a product. Often, when a publication’s famous founder recommended a product, it would sell better; but over time, as the sites grew to have teams of writers, the sites no longer conveyed the distinct sensibilities of Paltrow, Hesser, or Clymer. Then there were the economics. It is hard to make money by marketing other brand’s products. These sites generated small amounts of revenue by selling products at a markup on their online stores or by making a commission by driving the customer to another brand’s website. All of these companies realized that a more profitable route was to make their own products, which they all did, from Goop’s beauty and fashion lines to Hodinkee’s watch straps and limited edition collaborations with brands like Longines. But this meant building out teams with expertise in designing and sourcing products, which was also a major investment. Finally, there was all the competition. Other media sites quickly realized they, too, could create a new revenue stream by linking to products. And some began doing it much more effectively. In 2016, for instance, the New York Times acquired Wirecutter for $30 million. Unlike Food52, Goop, and Hodinkee, Wirecutter was designed to help consumers at the moment when they were ready to buy a product. New York Magazine built its own product recommendation site called The Strategist, which has a similar model. “Content that really drives commerce is not just ambient recommendations around fun articles,” says Frommer. “It’s really purpose-driven content designed to help the consumer solve a problem. The majority of traffic to Wirecutter and The Strategist happens at the moment of needthey promote their humidifier recommendations when the winter air is dry.” The content-to-commerce model hasn’t disappeared; it has shape shifted. There are now massive players like Wirecutter that dominate the landscape. And at the other end of the spectrum, there are armies of individual content creators who recommend products to their followers on Substack, Instagram, or TikTok. It’s just the middle of the market that has collapsed. But as with everything on the internet, change is constant. And everything we know about how to shop online is about to get transformed by AI, which is already where many people begin their shopping journey. In many ways, AI agents are the ultimate blending of content and commerce: They offers product recommendations, personalized to the user, presented within a conversation. But what’s missing from AI is a unique point of view or sensibilitywhich is what the early content-to-commerce players excelled in. In an AI-driven shopping future, the winners wont be the smartest algorithms. It’ll be the ones that blend data with something that feels like taste.
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E-Commerce
For decades, people with disabilities have relied on service dogs to help them perform daily tasks like opening doors, turning on lights, or alerting caregivers to emergencies. By some estimates, there are 500,000 service dogs in the U.S., but little attention has been paid to the fact that these dogs have been trained to interact with interfaces that are made for humans. A team of researchers from the United Kingdom wants to change that by designing accessible products for, and with dogs. The Open University’s Animal-Computer Interaction Laboratory in the UK was founded in 2011 to help promote the art and science of designing animal-centered systems. Led by Clara Mancini, a professor of animal-computer interaction, the lab studies how animals interact with technology and develops interactive systems designed to improve their wellbeing and support their relationships with humans. [Video: The Open University] The team’s first commercially available product is a specifically-designed button that service dogs can press to help turn on corresponding appliances at home, like a lamp, a kettle, or a fan. The Dogosophy Button took more than ten years to develop and was tested with about 20 dogs from UK charity Dogs for Good. It gives dogs more control over certain aspects of their home, which can make training them easier and further strengthen the bond between a human and their dog. It’s also taught the team a few lessons about how to design for humans. “I am now a better human designer,” says Luisa Ruge, an industrial designer who worked with Mancini and led the design of the button. For now, the Dogosophy Button is only available for purchase in the UK (for about $130). [Photo: The Open University] The challenges of designing for animals Anyone who’s ever designed a product for a human client knows the process relies on a perfect storm of variables like gender, age, background, and personal preferences. But these designers also have one advantage they likely take for granted: they can ask their client what they think at every step of the way. Getting feedback from a dog is much harder and requires an understanding of animal behavior. “Theres a lot of iteration,” says Ruge, “and a huge ethical and reflective component because I can’t be a dog, I don’t [feel] what they feel.” Ruge began her career as an industrial designer, but as she moved up the corporate ladder, she realized she was fascinated with animals. Her interest led her to train as a service dog trainer at Bergin College of Canine Studies in California. “One of the ways to bond is we had to be tied to our dog with a carabiner and leash for 8 days, 24/7,” she recalls. Later, she attended a conference on human behavior change for animal welfare, where she met Mancini and became interested in her lab. Ruge immediately enrolled in a PhD at The Open University, and spent the next three years writing a thesis on designing for the animal user experience and proving out her dog-centered methodology. Ruge followed the five human factors model, a method that helps designers understand the end user’s behavior by breaking down the UX into five factors. The typical list includes physical, cognitive, social, cultural, and emotional factors, but Ruge added a sixthsensoryand then later, a seventh: consent. To understand the exact characteristics and abilities she had to design for, she focused on Labrador Retrievers, Golden Retrievers, as these are the most common breeds for service dogs. Her research led to various correlations that informed the design of the button. For example: since both breeds have long tails, the button should not feature sensors that might accidentaly be activated by it. Since both breeds are predisposed to hip dysplasia and joint problems, the button should also not be designed in a way that requires jumping to activate. And since all dogs see the world in hues of yellow, blue, and brown, the button should be made in one of these colors so it is easy to perceive. [Video: The Open University] When Ruge first got involved, the prototype Mancini had developed was square in shape, and looked a bit like the standard metallic button that people with wheelchairs can press to open a door. Nowafter about 20 iterations and five prototypesthe button is round, convex, and blue. It is textured to prevent a dog’s wet snout from sliding on it, and its push depth is such that a more timid dog shouldn’t have to press hard to activate it. Ruge had to test some of her designs the hard way. The first prototype she ever made took days to develop and the dogs destroyed it “in two seconds,” she recalls with a laugh. But dogs don’t know that a prototype should be handled with care. To them, a work-in-progress product looks no different than a finished product. Animal design as a discipline Designing for dogs humbled Ruge’s assumptions. “It lets you know you’re never 100% right,” she says, adding that the only way to confirm her theories was through extensive testing and observation. It also made her a better designer for humans, because she learned to better spot her biases and assumptions. “Sometimes, I’m assuming you feel a handle like I do, and you don’t,” she says. In the end, though, animal design is where Ruge’s passion lies. Since earning her PhD, she has moved back to her native Colombia and started a design consultancy called Ph-auna (pronounced fauna) where she focuses on animal centeed innovation. She hosts a podcast called Pomodogo, guiding humans to better connect with their dogs, and is now working on an app that gamifies dog training and inspires humans to be better caretakers. “There’s an immense opportunity for animal design to be its own design discipline,” she says. Meanwhile, in the UK, the Dogosophy Button is available to individual customers willing to buy it, but the team is hoping to broaden its scope beyond the home. Mancini, who spearheaded the button project, says they first installed an earlier version of the button to operate the motorized door of a restaurants accessible toilet, but the restaurant ended up shuttering. Then, they tried installing it at a local shopping mall, but the plan fell through due to budget constraints. Still, she plans to continue developing new versions and adapt them for the characteristics of other species too. “It is my interest to try and install the buttons in public buildings,” she says. “I would love for whole cities to be more accessible for dogs and other urban animals.”
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E-Commerce
On my phone, there are already videos of the next moon landing. In one, an astronaut springs off the rung of a ladder, strung out from the lander, before slowly plopping to the surface. He is, alas, still getting accustomed to the weaker gravity. In another, the crew collects a samplea classic lunar expedition activitywhile another person lazily minds the rover. A third video shows an astronaut affixing the American flag to the ground, because this act of patriotism is even better the second time around. The blue oceans of Earth are visible, in the background, and a radio calls out: Artemis crew is on the surface. America is going back to the moon, and NASA is in the final weeks of preparing for the Artemis II mission, which will have astronauts conduct a lunar flyby for the first time in decades. If all goes well, during the next endeavor, Artemis III, theyll finally land on the lunar surface, marking an extraordinary and historical and in some sense, nostalgic, accomplishment. The aforementioned videos are not advance copies, or some vision of the future, though. They were generated with OpenAIs video generation model and are extremely fake. Still, this kind of content is a reminder that the upcoming Artemis missions promise a major epistemic test for the deniers of the original moon landing. This a small but passionate and enduring community who doubt the Apollo moon landing for a host of reasons, including that (they allege) the government lied or (they believe) it is simply physically impossible for humans to go the moon. Now, when NASA returns to the lunar surface, these people will be confronted with far more evidence than from the last time around. The space agency operation will be broadcast, live, and including camera technology and social media platforms that just werent around in the 1960s. But theres also a bigger challenge before us. NASA will be launching its moon return effort in a period of major distrust in American scientific and government institutions, and, amid the proliferation of generative AI, declining confidence in the veracity of digital content. Most observers will be able to sort through the real NASA imagery, and anything fake that might show up. Still, there tends to be a small number of people who doubt these kinds of milestones, especially when a U.S. federal agency is involved. Adding AI to the conspiracy theory cocktail When the moon landing first came in, AI wasn’t a thing. The sophistication of [the landing] didn’t necessarily make us question it, says David Jolley, a professor at the University of Nottingham who studies conspiracy theories. But now, with the power of AI and the power of images that you can create, it certainly offers that different reality if you want to interpret it in that way. Its the trust in those sources that we need to kind of really create. Of course, if you haven’t got trust in our gatekeepers and you don’t trust scientists, well, suddenly you are going to lean into: well, this, is this real? Is this just AI? he continues. The upcoming Artemis missions arent yet a major topic among lunar landing deniers. But there are hints it will attract more attention from conspiracy theorists. During the last Artemis mission, which was unmanned, Reuters had to push back on online posts suggesting the expedition proved that Apollo 11 didnt actually happen. (Skeptics suggested longer Artemis I mission timelines, a product of a change in route, actually cast doubt on the original Apollo timeline). Other online skeptics have already suggested that, with Artemis, NASA is yet again faking a space endeavor. Some people in internet conspiracy communities suggest the upcoming moon missions will be entirely CGI (computer-generated imagery). Generative AI stands to introduce even more confusion, says Ben Colman, the CEO of Reality Defenders, a deep fake detection platform. Generating a believable image of a (fake) moon landing is now something any consumer can do. Any astute physicist will be able to tell you if these videos get star placement or physics wrong, as they are likely to do, he says, but even that is getting better with each model iteration. Conspiracy theories are sticky There are, of course, many reasons why people say they deny reality of the first lunar expeditions. They are canonical, misinterpreted references, like Van Allen belts, a zone of energetic charged particles that surrounds the planet (critics say the belts are too radioactive for manned vehicles to traverse) and the suspicious flag-in-the-wind (theres no wind on the moon!). All of these pointsand the many other points deniers bring uphave been thoroughly debunked. Still, this small community of self-appointed detectives are insistent. Even decades after the missions ended, people are still combing through NASAs videos and images, mining for signs of alternations or other surreptitious editing. To them, an expected shimmer reveals a film operation just beyond the view of the camera. A movement that might not look right is a hint that the world has been duped. Open source intelligence (OSINT) becomes the rabbit hole. Some allege we didn’t go to the moon, perhaps because we were trying to trick the Soviets into thinking that we had superior technology than they did, explains Joseph Uscinski, a political scientist at the University of Miami who also studies conspiratorial beliefs. Some people think we did go but it wasn’t televised. And that footage that we saw was made later in a sound studio. Some people think Stanley Kubrick was in charge of filming the faked Moon Landing footage. For its part, NASA is preparing to point to evidence, should any deepfake allegations come their way. Agency spokesperson Lauren Low tells Fast Company: We expect AI experts will be looking closely at all our images and will be able to verify they are real images taken by real astronauts as part of the Artemis II test flight around the Moon. Moreover, Low added, there will be many ways for people to watch the lunar flyby themselves, including live broadcasts, two 24/7 YouTube streams, a new conference, and views from Orion cameras. In other words, the reality of Artemis will be very hard to deny. Research suggests that conspiracy theories are entertaining, and even serve peoples core psychological needs, like a desire to understand the world or a way of dealing with uncertainty. Finding other people, including on social media, pushing these theories can help normalize them, and make someone feel like theyre part of a broader community. Some people simply dont trust institutions, and evidence that something did, indeed, happen only raises further questions, and suspicions that it didnt. To an extent, politics matters, too; people outside the United States are more likely to deny the moon landing, polls show. In the end, says Uscinski, we should prepare for people who are prone to conspiratorial thinking, or prone to mistrusting institutions, to take a skeptical view of any big news event. This may happen again when the Artemis missions finally launch. “The good news is that belief in conspiracy theories isnt likely to get worse,” he explains. “The bad news is that this conspiratorial thinking has always been this pervasive. People are very good at waving away evidence that tells them things they don’t want to hear, and they’re very good at believing things, either without evidence or with really shitty evidence when it tells them what they do want to believe about the world, Uscinski adds. You don’t need AI or sophisticated technology to provide a justification.
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