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Zephr raises $8M to help news publishers grow subscription revenue
Zephr has raised $8 million in a new funding round led by Bertelsmann Digital Media Investments (owned by media giant Bertelsmann).
The London-headquarted startup’s customers already include publishers like McClatchy, News Corp Australia, Dennis Publishing and PEI Media. CEO James Henderson told me via email that rather than creating “a monolithic product that tries to do a bit of everything,” Zephr is “focused entirely on the experience and journey for the prospect or customer,” driving an average 150% increase in conversion rates and 25% increase in subscription revenue within the first six months.
Henderson added, “By offering the right product, package or message at the right time to the right person, Zephr improves conversion rates, drastically decreases churn and drives new, stable revenue.”
To do this, Zephr largely relies on the publisher’s first-party data about its readers — Henderson said that this data is “by far the most important and powerful type of data that Zephr both uses and generates.” But it also takes advantage of contextual data, such as “time of day, to location, device or consumption patterns.”
He also noted that Zephr is a no-code tool, allowing non-technical members of the marketing, revenue and product teams to use a drag-and-drop editor to create different customer journeys.
Image Credits: Zephr
Asked how the pandemic has affected the startup’s business, Henderson said there were both “positive and negative indicators,” with newsrooms seeing record readership but in some cases also freezing spending.
“As firms prepare for a ‘post-pandemic’ world, we are beginning to see our markets seize the opportunity of all these new potential subscribers and invest in subscription models — and in Zephr.” he said. “In publishing and news media, the old model of dominant advertising revenue is on the way out and we are well-placed to capitalize on that interest.”
The new funding also includes financing from Silicon Valley Bank UK Branch and brings Zephr’s total funding to $11 million. Previous investors include Knight Capital and Nauta Capital.
According to the company’s funding announcement, this money will go toward further product development (with a focus on increased personalization), as well as expansion across the United States, Europe and Asia.
“The recent weakness in the advertising market increased pressure for media companies to diversify revenue streams and aim to introduce or optimize subscription models,” said BDMI Managing Director Urs Cete in a statement. “We recognise Zephr’s excellent technology that empowers publishers to galvanise the online subscription opportunity and create customer journeys that are truly unique.”
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Fantasy startup Esports One raises $4M more
Esports One, a startup bringing the fantasy approach to esports, is announcing that it has raised an additional $4 million in funding.
When I first wrote about Esports One in April, co-founder and COO Sharon Winter described it as the first “all-in-one fantasy platform” in the esports world, allowing you to research players, create fantasy teams and watch games, with an initial focus on the North American and European divisions of League of Legends.
According to the Esports One team, creating this platform required building out a set of data and analytics products, as well as using computer vision technology that can track game activity (and update player stats) without relying on a publisher’s API.
The startup says its user base has been growing by more than 25% month-over-month. It may also have benefited from the pause in professional sports earlier this year, while CEO and co-founder Matt Gunnin told me recently that he also sees fantasy as a way to make video games accessible to a broader audience — he recalled one Esports One user who introduced his sister to League of Legends using the fantasy platform.
“I use the example of growing up and sitting there with my dad, watching a baseball game, he’s telling me everything that’s happening,” Gunnin said. “Now it’s the opposite — parents are sitting and watching their kids.”
Many parents, he suggested, are “never going to pick up a mouse and keyboard and play League of Legends,” but they might play the fantasy version: “That’s an entry point … if we can make it easily accessible to individuals both that are hardcore gamers playing video games and watching League of Legends their entire life, as well as someone who has no idea what’s going on.”
The new funding was led led by XSeed Capital, Eniac Ventures, and Chestnut Street Ventures, bringing Esports One to a total of $7.3 million raised. The company also recently signed a partnership deal with lifestyle company ESL Gaming.
Gunnin said the money will allow the company to grow its Bytes virtual currency, which players use to enter contests and buy customizations — starting next year, players will be able to spend real money to purchase Bytes. In addition, it’s working on native iOS and Android apps (Esports One is currently accessible via desktop and mobile web).
Gunnin and his team also plan to develop fantasy competitions for Rainbow Six: Siege, Rocket League, Valorant and Fortnite.
“As a fairly new player in the esports world, we’ve seen immense determination and grit from Matt, Sharon, and the whole Esports One team to grow into a household name,” said XSeed’s Damon Cronkey in a statement. “I’m excited to be partnering with a company that will deliver new perspectives and features to an evolving industry. We’re eager to see how Esports One grows in 2021.”
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WaveOne aims to make video AI-native and turn streaming upside down
Video has worked the same way for a long, long time. And because of its unique qualities, video has been largely immune to the machine learning explosion upending industry after industry. WaveOne hopes to change that by taking the decades-old paradigm of video codecs and making them AI-powered — while somehow avoiding the pitfalls that would-be codec revolutionizers and “AI-powered” startups often fall into.
The startup has until recently limited itself to showing its results in papers and presentations, but with a recently raised $6.5M seed round, they are ready to move towards testing and deploying their actual product. It’s no niche: video compression may seem a bit in the weeds to some, but there’s no doubt it’s become one of the most important processes of the modern internet.
Here’s how it’s worked pretty much since the old days when digital video first became possible. Developers create a standard algorithm for compressing and decompressing video, a codec, which can easily be distributed and run on common computing platforms. This is stuff like MPEG-2, H.264, and that sort of thing. The hard work of compressing a video can be done by content providers and servers, while the comparatively lighter work of decompressing is done on the end user’s machines.
This approach is quite effective, and improvements to codecs (which allow more efficient compression) have led to the possibility of sites like YouTube. If videos were 10 times bigger, YouTube would never have been able to launch when it did. The other major change was beginning to rely on hardware acceleration of said codecs — your computer or GPU might have an actual chip in it with the codec baked in, ready to perform decompression tasks with far greater speed than an ordinary general-purpose CPU in a phone. Just one problem: when you get a new codec, you need new hardware.
But consider this: many new phones ship with a chip designed for running machine learning models, which like codecs can be accelerated, but unlike them the hardware is not bespoke for the model. So why aren’t we using this ML-optimized chip for video? Well, that’s exactly what WaveOne intends to do.
I should say that I initially spoke with WaveOne’s cofounders, CEO Lubomir Bourdev and CTO Oren Rippel, from a position of significant skepticism despite their impressive backgrounds. We’ve seen codec companies come and go, but the tech industry has coalesced around a handful of formats and standards that are revised in a painfully slow fashion. H.265, for instance, was introduced in 2013, but years afterwards its predecessor, H.264, was only beginning to achieve ubiquity. It’s more like the 3G, 4G, 5G system than version 7, version 7.1, etc. So smaller options, even superior ones that are free and open source, tend to get ground beneath the wheels of the industry-spanning standards.
This track record for codecs, plus the fact that startups like to describe practically everything is “AI-powered,” had me expecting something at best misguided, at worst scammy. But I was more than pleasantly surprised: In fact WaveOne is the kind of thing that seems obvious in retrospect and appears to have a first-mover advantage.
The first thing Rippel and Bourdev made clear was that AI actually has a role to play here. While codecs like H.265 aren’t dumb — they’re very advanced in many ways — they aren’t exactly smart, either. They can tell where to put more bits into encoding color or detail in a general sense, but they can’t, for instance, tell where there’s a face in the shot that should be getting extra love, or a sign or trees that can be done in a special way to save time.
But face and scene detection are practically solved problems in computer vision. Why shouldn’t a video codec understand that there is a face, then dedicate a proportionate amount of resources to it? It’s a perfectly good question. The answer is that the codecs aren’t flexible enough. They don’t take that kind of input. Maybe they will in H.266, whenever that comes out, and a couple years later it’ll be supported on high-end devices.
So how would you do it now? Well, by writing a video compression and decompression algorithm that runs on AI accelerators many phones and computers have or will have very soon, and integrating scene and object detection in it from the get-go. Like Krisp.ai understanding what a voice is and isolating it without hyper-complex spectrum analysis, AI can make determinations like that with visual data incredibly fast and pass that on to the actual video compression part.
Image Credits: WaveOne
Variable and intelligent allocation of data means the compression process can be very efficient without sacrificing image quality. WaveOne claims to reduce the size of files by as much as half, with better gains in more complex scenes. When you’re serving videos hundreds of millions of times (or to a million people at once), even fractions of a percent add up, let alone gains of this size. Bandwidth doesn’t cost as much as it used to, but it still isn’t free.
Understanding the image (or being told) also lets the codec see what kind of content it is; a video call should prioritize faces if possible, of course, but a game streamer may want to prioritize small details, while animation requires yet another approach to minimize artifacts in its large single-color regions. This can all be done on the fly with an AI-powered compression scheme.
There are implications beyond consumer tech as well: A self-driving car, sending video between components or to a central server, could save time and improve video quality by focusing on what the autonomous system designates important — vehicles, pedestrians, animals — and not wasting time and bits on a featureless sky, trees in the distance, and so on.
Content-aware encoding and decoding is probably the most versatile and easy to grasp advantage WaveOne claims to offer, but Bourdev also noted that the method is much more resistant to disruption from bandwidth issues. It’s one of the other failings of traditional video codecs that missing a few bits can throw off the whole operation — that’s why you get frozen frames and glitches. But ML-based decoding can easily make a “best guess” based on whatever bits it has, so when your bandwidth is suddenly restricted you don’t freeze, just get a bit less detailed for the duration.
Example of different codecs compressing the same frame.
These benefits sound great, but as before the question is not “can we improve on the status quo?” (obviously we can) but “can we scale those improvements?”
“The road is littered with failed attempts to create cool new codecs,” admitted Bourdev. “Part of the reason for that is hardware acceleration; even if you came up with the best codec in the world, good luck if you don’t have a hardware accelerator that runs it. You don’t just need better algorithms, you need to be able to run them in a scalable way across a large variety of devices, on the edge and in the cloud.”
That’s why the special AI cores on the latest generation of devices is so important. This is hardware acceleration that can be adapted in milliseconds to a new purpose. And WaveOne happens to have been working for years on video-focused machine learning that will run on those cores, doing the work that H.26X accelerators have been doing for years, but faster and with far more flexibility.
Of course, there’s still the question of “standards.” Is it very likely that anyone is going to sign on to a single company’s proprietary video compression methods? Well, someone’s got to do it! After all, standards don’t come etched on stone tablets. And as Bourdev and Rippel explained, they actually are using standards — just not the way we’ve come to think of them.
Before, a “standard” in video meant adhering to a rigidly defined software method so that your app or device could work with standards-compatible video efficiently and correctly. But that’s not the only kind of standard. Instead of being a soup-to-nuts method, WaveOne is an implementation that adheres to standards on the ML and deployment side.
They’re building the platform to be compatible with all the major ML distribution and development publishers like TensorFlow, ONNX, Apple’s CoreML, and others. Meanwhile the models actually developed for encoding and decoding video will run just like any other accelerated software on edge or cloud devices: deploy it on AWS or Azure, run it locally with ARM or Intel compute modules, and so on.
It feels like WaveOne may be onto something that ticks all the boxes of a major b2b event: it invisibly improves things for customers, runs on existing or upcoming hardware without modification, saves costs immediately (potentially, anyhow) but can be invested in to add value.
Perhaps that’s why they managed to attract such a large seed round: $6.5 million, led by Khosla Ventures, with $1M each from Vela Partners and Incubate Fund, plus $650K from Omega Venture Partners and $350K from Blue Ivy.
Right now WaveOne is sort of in a pre-alpha stage, having demonstrated the technology satisfactorily but not built a full-scale product. The seed round, Rippel said, was to de-risk the technology, and while there’s still lots of R&D yet to be done, they’ve proven that the core offering works — building the infrastructure and API layers comes next and amounts to a totally different phase for the company. Even so, he said, they hope to get testing done and line up a few customers before they raise more money.
The future of the video industry may not look a lot like the last couple decades, and that could be a very good thing. No doubt we’ll be hearing more from WaveOne as it migrates from lab to product.
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New venture firm The-Wolfpack takes a fresh approach to D2C startups
The-Wolfpack’s co-founders, Toh Jin Wei, Tan Kok Chin and Simon Nichols (Image Credit: The-Wolfpack)
The COVID-19 pandemic has hit the consumer, leisure and media companies hard, but a new venture firm called The-Wolfpack is still very upbeat on those sectors. Based in Singapore, the firm was founded by former managing directors at GroupM, one of the world’s largest advertising and media companies, and plans to work very closely with each of its portfolio companies. Its name was chosen because they believe “entrepreneurs thrive best in a wolfpack.”
The-Wolfpack’s debut fund, called the Wolfpack Pioneer VCC, is already fully subscribed at $5 million USD, and will focus on direct-to-consumer companies, with plans to invest in eight to 10 startups. The firm is already looking to raise a second fund, with a target of $20 million SGD (about $14.9 million USD) and above, and will set up another office in Thailand, with plans to expand into Indonesia as well.
The-Wolfpack was founded by Toh Jin Wei and Simon Nichols, who met while working at GroupM, and Tan Kok Chin, a former director at Sunray Woodcraft Construction who has worked on projects with Marina Bay Sands, Raffles Hotel and the Singapore Tourism’s offices.
In addition to providing financial capital, The-Wolfpack wants to build ecosystems around its portfolio companies by connecting them with IP owners, digital marketing experts, content producers and designers who can help create offline experiences. It also plans to invest in startups based on opportunities for them to collaborate or cross-sell with one another.
Toh told TechCrunch that formal planning on The-Wolfpack began at the end of 2019, but he and Nichols started thinking of launching their own business five years ago while working together at GroupM.
“Our perspective on what the industry needed was similar — strategic investors who truly knew how to get behind D2C founders,” Toh said.
The COVID-19 pandemic and its economic impact has hurt spending in The-Wolfpack’s three key sectors (consumer, leisure and media). But it also presents opportunities for innovation as consumer habits shift, Nichols said.
For example, even though consumer spending has dropped, people are still “drawn towards brands that build towards higher-quality engagements,” he said. “There is a real business advantage for D2C brands who’ve recognized this shift and know how to act on it.”
The-Wolfpack hasn’t disclosed its investments yet since deals are still being finalized, but some of the brands its debut fund are interested in include one launched by an Australian makeup artist who wants to scale to Southeast Asia, and an online gaming company whose ecosystem includes original content, gaming teams and studios. The-Wolfpack plans to help them set up a physical studio to create an offline experience, too.
“Typically brands have talked at customers, but it’s become a two-way conversation, and startups who get D2C right have a real potential for exponential growth that’s worth investing in,” said Toh.
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The crowd goes wild for Yiming
There’s no shortage of TikTok coverage in the news today as the app’s fate in the U.S. hangs in the air.
What the press doesn’t always address is how TikTok gets here — how did a Chinese startup seize the lucrative short-video market in the West before Google and Facebook? What did it do differently from its Chinese predecessors who tried global expansion to little avail? Matthew Brennan’s new book “Attention Factory” set out to answer these questions by tracing ByteDance’s trajectory from an underdog despised by Chinese tech workers and investors to the envy of Silicon Valley and the target of the White House.
Matthew has spent years working closely with China’s tech firms, not only analyzing them but also using their products as a curious local, experiences that informed his meticulously researched and entertaining book. Interwoven with captivating anecdotes of TikTok, rare photos of ByteDance’s original team, incisive analysis and telling infographics, “Attention Factory” is an essential read for those looking to understand how ideas in the American and Chinese internet worlds collided, coincided and converged throughout the 2010s.
TikTok is a rare example of a Chinese internet service that has gained worldwide success. Before expanding overseas, ByteDance had already proven the short-video model in China through Douyin, the homegrown version of TikTok.
The excerpt below follows a high-growth period of Douyin, detailing how it gained around 200 million daily active users within a year: a loyal creator community, viral memes, algorithmic recommendation and aggressive ad spending.
Before long, the Chinese startup would replicate that growth playbook in the rest of the world, tweaking it here and there to make it work.
Hundreds of fashionably dressed young people were arriving at 751 D.PARK, an expanse of industrial plants redeveloped into a hip culture venue in northeast Beijing. They were clad in baseball caps, brightly colored dresses, loose-fitting hip-hop style streetwear and limited-edition sneakers. The site had been transformed into something akin to the stage of the talent competition “American Idol,” spanning two floors filled with strobe lighting, high-volume music and trendy backdrops. This was an exclusive party — three hundred top Douyin creators coming together to celebrate the app’s one-year anniversary.
The online stars, billed as the “new generation of internet celebrities,” weren’t there to just socialize and enjoy themselves. Every influencer was aware of the unspoken competition to derive the best content from that night. They were all fighting to achieve a higher level of superstardom and the medium of battle was short video.
The influencers who knew each other gathered in small groups as their assistants tirelessly captured fifteen-second videos of their carefully crafted skits. Loners roamed around the dance floor, absorbed in finding the ideal lighting for their lip-syncing selfie videos. Lesser-known influencers nervously approached more famous ones, proposing to record a dance together to potentially tap into their peers’ following. Loud hip-hop music kept playing in the background as creators hurried to touch up the videos they had just shot. Once the editing was done, they uploaded their works and anxiously waited for the app’s algorithms to judge who would grab more eyeballs.
Dance teams took to the stage to display their skills. The crowd bopped their heads back and forth as rappers attempted to impress with clever lyrics. Later as the hosts were midway through giving out awards, a wave of noise erupted from the back of the crowd interrupting the proceedings.
It was Yiming. Dressed in a black baseball cap and gray T-shirt and accompanied by Lidong. The audience went wild — the CEO had decided to drop in unannounced! Immediately he was bombarded with requests to take pictures and videos. As those around him whooped and cried out wildly, the entrepreneur simply smiled and kept his hands calmly by his side, an awkward 34-year-old engineer type among the hyper fashionable, mostly teenage hip-hop crowd.
Yiming and Lidong appear at a Douyin promotional event marking the app’s first anniversary in Sept 2017.
He already knew from looking at the data, but this was confirmation in the flesh — Douyin had built a robust community, with powerful momentum and was on the verge of doing something special.
The breakout
October 1st marks the beginning of “Golden Week,” a seven-day-long official Chinese national holiday. Periods like these are big opportunities for China’s internet industry. People’s behaviors change for a week; many find more time for entertainment and to try new things.
Over October, Douyin’s daily users doubled from seven to 14 million; two months later, they reached 30 million. Over those three months, the 30-day retention rates jumped from eight to over 20%, the average time spent in the app soared from 20 to 40 minutes. It was as if some magic rocket fuel had suddenly been added, boosting every key metric. What had changed?
The answer was Zhu Wenjia. Zhu Wenjia, hired from Baidu in 2015, was widely considered to be one of the top-three best people in the entire company when it came to algorithm technology. He ran one of ByteDance’s most capable engineering teams and had recently been assigned to work on Douyin. The team’s work harnessing the full power of ByteDance’s content recommendation back end led directly to the astounding October results.
The better the metrics, the more resources ByteDance placed behind the app as it now had good retention and was fast-tracked into becoming a strategically important product. Suddenly support was coming in from all over the company — people, money, user traffic, celebrity endorsements, brand collaborations, and most importantly, full integration and optimization of ByteDance’s powerful recommendation engine. Chinese stars with massive fan bases such as Yang Mi, Lu Han, Kris Wu, and Angelababy opened accounts, joining in publicity campaigns, and a nationwide “Douyin Party” event roadshow was planned. Douyin had become the hottest upcoming app in China.
ByteDance ramped up the investment in all three short-video products, including Douyin. People, resources and advertising budget were all raised, leading an industry insider to comment later: “The sudden rise of Douyin wasn’t without good cause. Yiming threw more money at this than anyone and dared to hunt down and grab the best people.”
Commercialization began with the first three brand ad campaigns paid for by Airbnb, Harbin Beer and Chevrolet. Douyin’s advertising business would soon make rapid progress. ByteDance already had hundreds of sales and marketing staff who would shortly be able to add Douyin’s advertisement inventory to their sales targets.
Yiming revealed in a later interview that the company had made it compulsory for everyone on the management team to make their own Douyin videos with goals to gain a certain number of likes or suffer forfeits such as doing push-ups. It wasn’t good enough to just look at charts and data; management needed to understand short videos from a creator’s perspective also. Yiming had watched Douyin videos for a long time but creating his own was “a big step for me,” he admitted.
Yiming’s personal Douyin account (3277469). Seventeen videos at the time of writing, including clips from his global travels.
‘Oh well … karma’s a bitch’
The video opened to a young woman yawning, dressed in pajamas with messy morning hair. Wearing glasses and with no signs of makeup, she casually lip-syncs the line, “Oh well … karma’s a bitch” and throws a silk scarf into the air. Suddenly loud background music explosively begins. In an instant, she transforms into a glamorous fashion model, almost unrecognizable from a second before. A new meme had taken hold of Douyin.
“Karma’s a bitch” was a new version of the original “Don’t judge me” challenge that had propelled Musical.ly to top the U.S. app store three years earlier. The meme was another breakthrough for Douyin; People loved watching the shocking transformations. Compilations of the meme’s videos started popping up online. In particular, the makeup skills of some women left many men in disbelief. “Karma’s a bitch” left an impact on mainstream culture and gained widespread recognition and publicity, even making waves out into English language global media.
Douyin was also increasingly hypercharging the popularity of catchy pop songs with strong hooks. In late 2017, a track known as the “Ci-li-ci-li song” exploded on Douyin. The song’s catchy energy was undeniably infectious. Yet, it was the novel set of dance moves that had become associated with the track’s hook that turned the music into a meme and dramatically amplified its success.
The track had actually been released back in 2013 by Romanian reggae and dancehall artist Matteo, under the name “Panama.” Four years after its debut, the song’s unexpected and explosive spike in popularity led the singer to hastily organize an Asia tour to capitalize on his track’s sudden fame. A YouTube video shows him meeting Chinese fans at the Hangzhou airport who demonstrate their moves to him in the arrivals hall. With the dance having been created entirely in China, the bewildered artist finds himself in the awkward situation of not knowing how to follow the moves to the song for which he is famous.
Perhaps the most reliable indicator of the platform’s increasing influence on society was how the name, Douyin, had started to enter everyday colloquial vernacular, becoming synonymous with short video. The meaning of “Let’s shoot a Douyin!” needed no explanation.
Make it rain
ByteDance knew they now had a winning formula. Retention was good, word of mouth was excellent, a large, vibrant community of video creators had been fostered. The recommendation engine was doing its job of surfacing the best content. Douyin’s fire was already burning bright; now, it was time to pour gasoline on things and spend, spend, spend.
The holiday week of Chinese New Year is another unique annual opportunity for app promotions. Hundreds of millions travel home to be reunited with their families and find themselves with free time to relax. An entertainment app like Douyin was the perfect way to pass the time; word of mouth spread naturally between family members.
To step up its efforts further, Douyin directly gave out money to users by running a Chinese New Year “lucky money” campaign. Users could collect small cash amounts in special videos by tapping on the “red packet” icons — a digital manifestation of cash-filled envelopes people give to each other during the holiday. ByteDance also went all out, spending wildly, buying adverts and promotions across major online channels to acquire users, spending about 4 million yuan a day (over half a million dollars). The combination of all these effects sent Douyin to the top of the Chinese app store charts. Various reports stated Douyin’s daily users jumped from around 40 to 70 million over the February to March period covering Chinese New Year, with some of the top accounts seeing their follower numbers quadruple.
A chart mapping the progress of Douyin, from zero to 200 million daily active users, during the first two years of operation.
This article is an excerpt from “Attention Factory: The Story of TikTok and China’s ByteDance,” which was written by Matthew Brennan and edited by TechCrunch reporter Rita Liao, who wrote the introduction to this post.
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Netflix’s latest experiment is a TikTok-like feed of funny videos
Netflix already borrowed the concept of short-form video “Stories” from social apps like Snapchat and Instagram for its Previews feature back in 2018. Now, the company is looking to the full-screen vertical video feed, popularized by TikTok, for further inspiration. With its latest experiment, Fast Laughs, Netflix is offering a new feed of short-form comedy clips drawn from its full catalog.
The feed includes clips from both originals and licensed programming, Netflix says. It also includes video clips from the existing Netflix social channel, “Netflix Is A Joke,” which today runs clips, longer videos and other social content across YouTube, Twitter, Facebook and Instagram.
Fast Laughs resembles TikTok in the sense that it’s swiped through vertically, offers full-screen videos and places its engagement buttons on the right side. But it’s not trying to become a place to waste time while being entertained.
Like many of Netflix’s experiments, the goal with the Fast Laughs feed is to help users discover something new to watch.
Instead of liking and commenting on videos, as you would in a social video app, the feed is designed to encourage users to add shows to their Netflix watch list for later viewing. In this sense, it’s serving a similar purpose to Netflix’s “Previews” feature, which helps users discover shows by watching clips and trailers from popular and newly released programming.
As users scroll through the new Fast Laughs feed, they’ll encounter a wide range of comedy clips — like a clip from a Kevin Hart stand-up special or a funny bit from “The Office,” for example. The clips will also range in length anywhere from 15 to 45 seconds.
In addition to adding clips to Netflix’s “My List” feature, users can also react to clips with a laughing emoji button, share the clip with friends across social media, or tap a “More” button to see other titles related to the clip you’re viewing.
The feature was first spotted by social media consultant Matt Navarra, based in the U.K. In his app, Fast Laughs appeared in front of the row of Previews, where it was introduced with text that said “New!”
Netflix confirmed to TechCrunch the experiment had been tested with a small number of users earlier this year, but has recently started rolling out to a wider group this month — including users in the U.K., the U.S. and other select markets.
It’s currently available to a subset of Netflix users with adult profiles or other profiles without parental controls on iOS devices only. However, users don’t need to be opted in to experiments nor do they need to be on a beta version of the Netflix app to see the feature. It’s more of a standard A/B test, Netflix says.
And because it’s a test, users may see slightly different versions of the same feature. The product may also evolve over time, in response to user feedback.
Netflix is hardly the first to “borrow” the TikTok format for its own app. Social media platforms, like Instagram and Snapchat, have also launched their own TikTok rivals in recent months.
But Netflix isn’t a direct competitor with TikTok — except to the extent that any mobile app competes for users’ time and attention, as there are only so many hours in a day.
Instead, the new feed is more of an acknowledgment that the TikTok format of a full-screen vertical video feed with quick engagement buttons on the side is becoming a default style of sorts for presenting entertaining content.
“We’re always looking for new ways to improve the Netflix experience,” a Netflix spokesperson said, confirming the experiment. “A lot of our members love comedy so we thought this would be an exciting new way to help them discover new shows and enjoy classic scenes. We experiment with these types of tests in different countries and for different periods of time — and only make them broadly available if people find them useful,” they added.
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MTV partners with Unrd to create a mobile version of ‘Ghosted: Love Gone Missing’
Mobile storytelling startup Unrd is making its first move into adapting existing intellectual property — specifically “Ghosted: Love Gone Missing,” an MTV reality series about ghosting (the dating practice, not anything supernatural).
Until now, Unrd (pronounced “unread”) has created original crime, horror and romance stories that are told through characters’ phones, through content like text messages, video footage and more.
Starting next week, on November 16, the app will feature a version of “Ghosted” that — unlike the TV show — is scripted, as users explore characters’ text messages, photos and video calls to discover why they’ve been ghosted. They’ll even get to vote on whether the characters should “ghost” or “make up” before they see the stories’ ending (their votes won’t affect the outcome).
MTV Head of Digital Rory Brown told me that this was a “very close collaboration” between MTV and the Unrd team, led by CEO Shib Hussain.
“This is the first time they’ve partnered with an already established IP — but that didn’t scare us at all, to be that first media partner that they worked with,” Brown said. “There was a strong point of view on our side of the house how to keep it true to the existed format, while the Unrd team helped us reimagine it, and our collaboration met in the middle of that Venn diagram.”
Image Credits: Unrd
He also argued that while interactivity can be “a bit of a buzzword in the industry,” Unrd isn’t focusing on “interactivity for interactivity’s sake.” Instead, the aim is to create “a more immersive experience for the user.”
Unrd will feature three stories tied to “Ghosted,” each of them unfolding over six days.
“The key thing that we do different is this notion of real time,” Hussain said. “You can’t just binge it and consume every story in one day. You’ve got to wait with the character for the next message. That’s more immersive, and it also builds that tension and excitement amongst users as well.”
Brown noted that these Unrd stories are launching during a break in the second season of “Ghosted.” The hope is that they’ll keep existing fans engaged while creating new fans as well.
“At MTV, we’re always going to keep looking at ways to test the elasticity of IP,” he said. “I think Unrd is one way to do that. We’re talking to other partners, but Shib and his team have been fantastic to work with and we’d love to keep the relationship going.”
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HBO releases a wellness-focused AR app to promote ‘His Dark Materials’
With the second season of “His Dark Materials” premiering on HBO on November 16, the network has partnered with creative studio Framestore to create a new iOS and Apple Watch app called His Dark Materials: My Daemon.
The free app gives fans of the show (and the Philip Pullman novels on which the show is based) a chance to interact with their very own “daemons” — the magical animal companions that serve as an extension of characters’ souls.
“It’s a really great opportunity to give users and fans of the show the opportunity to have a daemon companion that’s personalized to them,” said Christine Cattano, Framestore’s global head of VR. “And what better way to do that than on your phone, which is a constant companion to us all?”
Users are assigned a daemon after taking a simple quiz consisting of questions like “day or night?” and “above or below?” They can then interact with the daemon by providing basic updates on their current state (like whether they’re feeling focused or distracted). Based on those updates, the daemon will recommend tasks tied to physical and emotional wellness, like going for a walk or a run, or watching a movie.
As users perform more wellness tasks, their daemon becomes happier and healthier. The app also allows users to go on “journeys,” where they perform a series of (again, wellness-focused) tasks that are tied to the activities of characters on the show.
Image Credits: HBO/Framestore
His Dark Materials: My Daemon will learn more about your activities by integrating with Apple Health and Spotify. And it incorporates augmented reality by allowing you to watch animations where you daemon interacts with the world around you. You’ll be able to share your companion interactions on social media, as well.
HBO’s vice president of program marketing Emily Giannusa noted that the original plan was for “large, real world activations.” After all, Framestore didn’t just work on visual effects for the actual “His Dark Materials” show. It also collaborated with HBO to develop “Beyond the Wall,” a virtual reality experience tied to “Game of Thrones,” as well as the Magic Leap GoT experience called “The Dead Must Die,” which were both available via installations in flagship AT&T stores. (AT&T owns HBO’s parent company WarnerMedia.)
But given the pandemic and the need for social distancing, HBO and Framestore knew they had to take a different approach, so Giannusa said they came up with something that could “delight [fans] while they’re at home” — and that should reach a much larger audience in the process.
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Uzabase sells Quartz to the site’s CEO and staff
Quartz is going private, with co-founder and CEO Zach Seward buying the business news site from its current owner Uzabase.
In his post announcing the deal, Seward described the move as a management buyout that will also see Editor in Chief Katherine Bell and the rest of the Quartz staff taking equity in the new company.
“Most of the time, I hope, Quartz’s finances and our corporate parentage are irrelevant, as long as we’re doing our job well,” he wrote. “But this is an important moment in the life of our company, and we want to share it with all of you, whose readership and enthusiasm for Quartz have carried us successfully through the past eight years.”
Seward suggested that while Uzabase’s ownership was “helpful,” the company is “better off right now as a startup, freer to chart our own path.” And as a startup, it’s looking to raise outside funding.
The Wall Street Journal, which broke the news that Uzabase wanted to sell the property, also reported that Uzabase CEO Yusuke Umeda (pictured above) has made a personal loan to support the site.
Quartz was founded in 2012 by Atlantic Media, then acquired by Uzabase (a Japanese financial data and media company) for $86 million in 2018.
The company has struggled to make the business side work in recent years, reporting a loss of $18.4 million on revenue of $26.4 million in 2019, and cutting about 80 staff positions earlier this year.
In an assessment of the site’s troubles published in June, Digiday’s Steven Perlberg noted Quartz has been restructuring around its subscription business, but he suggested that it’s been caught in digital media’s “mushy middle”: “Not quite niche enough to be essential to a small group of readers, but not quite big enough to compete at scale.”
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Riverside.fm launches its video podcasting platform
Riverside.fm is a new startup with an easy-to-use platform for recording professional-quality video podcasts.
In fact, although the company only recently came out of stealth, it already has a number of high-profile customers, including TechCrunch’s parent company (Verizon Media) and Hillary Clinton, who’s using Riverside.fm to record her new podcast “You and Me Both with Hillary Clinton.”
“Just imagine, we needed a recording platform that could help us make a podcast during a pandemic, and, boy, did they step up,” Clinton said in a statement.
The startup was founded by brothers Nadav and Gideon Keyson — Nadav, who serves as CEO (Gideon is CTO), explained that they first created a platform where politicians could participate in video debates, but then realized there was a more promising business model for a broader podcasting tool.
In addition to officially launching, Riverside.fm is announcing that it has raised $2.5 million in seed funding led by Oren Zeev .
Gideon gave me a quick demo of the platform, showing me that it’s a fairly straightforward recording experience — the host just shares a link with the guests, no software installation necessary. There are plenty of other browser-based podcasting tools (for example, Zencastr recently expanded beyond audio with video support), but the Keysons suggested that they’ve spent a lot of time solving common technical issues for podcasters.
For one thing, each participants’ audio and video is recorded as a separate track on their device, so that a bad internet connection won’t affect recording quality. The recording is uploaded during the session, so you don’t have to have a long wait for files to upload. And there are automatic backups, in case someone’s browser or computer freezes.
“Stability … is so important,” Nadav said. “[Otherwise,] you could spend half a year to get a certain guest and then you lose their recording.”
Despite its simplicity, Riverside.fm supports 4K video and uncompressed WAV audio. It also includes an interface where podcast producers can monitor each guest’s equipment and adjust audio levels.
“We do really make it easy for the beginner and faster for the professionals,” Nadav said.
Gideon added that Riverside.fm isn’t interested in getting involved in the podcast distribution, but instead focuses on being a reliable production platform, as well as providing cross-platform analytics.
“We don’t want to start competing with Spotify and YouTube,” he said — in fact, Spotify is already a Riverside.fm customer.
The brothers also suggested that even if you’re not interested in creating a full-fledged video podcast, Riverside.fm is still the right choice for recording audio. Plus, you could still use the video recordings to create promotional clips for YouTube and social media.
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