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Tag Archives: streaming services

In the streaming era, data on a show’s viewership and popularity is harder to come by. It’s no longer as simple as setting up a Nielsen box to get data on a show being watched across TVs, phones, tablets and the web. One company solving this problem for content owners, broadcasters and streamers alike is Whip Media Group, parent company to the TV and movie tracking app TV Time. The company announced today it has raised $50 million in Series D funding to continue to grow its business.

The round was led by asset management firm Eminence Capital and includes participation from Raine Ventures. To date, Whip Media Group has raised $115 million from Raine Ventures, Eminence, IVP and others.

Whip Media Group has a varied history. TV Time began as WhipClip, a source for a legal collection of GIFs from favorite shows. But following the company’s acquisition of French startup TVShow Time in December 2016, it pivoted to become a social TV community. The TV Time app allows users to track their favorite shows by marking episodes as watched, as well as join in the show’s community on the app where users discuss the episode; share photos, screencaps, and memes; take polls; and more. Its recommendations feature also helps users find more things to watch.

The company rebranded as Whip Media Group to reflect that it’s now home to a handful of businesses, including the TV Time app, as well as TheTVDB, an entertainment database for TV and movies and, more recently, the content value management platform, Mediamorph.

Though consumers only interact with the TV Time app, those engagements help fuel Whip Media Group’s larger business.

Today, the TV Time app has anywhere between 800,000 and a million active users per day. And 50% of users contribute some sort of data — for example, following a show, creating content, liking another user’s post, reviewing an episode, commenting and so on. To date, TV Time has tracked more than 15 billion episodes.

Initially, TV Time was using this data to develop a new type of ratings system for the cord-cutting era. But TV Time learned that a show’s ratings don’t matter to video-on-demand services that don’t sell advertising. Instead, what TV Time could provide was emotional data on how users responded to shows.

“By collecting [this data] we can build these models to not only say what people are watching, but also start to predict what they’re going to watch next,” says Whip Media Group CEO Richard Rosenblatt.

In addition, the engagement data can help streamers find out things they never could before — like which moment in an episode had huge spikes of user interest, i.e. “the most memed moment.” This data can help them to better market the show as well as help them think about the show’s direction for future seasons.

Now, with the acquisition of Mediamorph, Whip Media Group can also help to value content. This allows buyers and sellers to make determinations about where to sell shows and for how much.

This data is highly valuable to Whip Media Group’s clients, which include more than 50 of the biggest names in entertainment — like Disney, Warner Bros., Hulu, NBCU, Paramount, Sony, Lionsgate, BBC, HBO, AT&T, T-Mobile, Liberty Global, Discovery and United Talent Agency. (There are other large, household names in streaming that also use the company’s data, but can’t be disclosed due to NDAs.)

When a content owner sells a show to a modern-day streaming service, they often have no way of knowing how it performs.

Whip Media Group, starting at the end of Q1, will be able to start making predictions about where a particular piece of content available for sale should go, says Rosenblatt.

“We will be able to roll out, starting in the first quarter, an ‘engagement score,’ where [content owners will] actually be able to look at how one piece of content engages a certain demographic or a certain geography differently than another piece of content,” Rosenblatt explains. “If you think about how ad networks got started 20 years ago — and you were trying to match the right consumer with the right ad, and all that mattered was if they clicked. Nothing else mattered. Google won because they had the best data, the best models…that’s what we want to do,” he continues.

“We want to put the right piece of content on the right platform, in the right country, to the right demographic. And we don’t think that there’s anyone else in this position like we are — that has all of that between Mediamorph and TV Time,” he says.

This data is more important than ever in an era where core classics are selling for as much as half a billion (like the “Seinfeld” sale to Netflix or “Friends” to HBO Max) or even more (like the billion-plus-dollar deal for “Big Bang Theory,” which also went to HBO Max.)

More broadly, global online television episode and movie revenues will reach $159 billion in 2024; more than double the $68 billion recorded in 2018, according to Research and Markets.

Whip Media Group’s new round of funding is being used, in part, to help pay for the Mediamorph acquisition, which was a combination of cash and stock. But the majority is being used to grow the business, including by expanding the company’s sales and data teams and accelerating product development.

The company has already hired 20 people so far and expects to hire 50 by year-end, mostly on the data and engineering sides.

“Whip Media Group is building software and data solutions that will transform the way content is being bought and sold throughout the global entertainment ecosystem,” said Ricky Sandler, chief executive officer of Eminence Capital, in a statement. “We believe in their vision and their exceptional leadership and technology teams and are excited to partner with them as they rapidly expand their business.”

Read more: https://techcrunch.com/2020/01/29/whip-media-group-parent-to-tv-show-tracking-app-tv-time-raises-50m/

Backed by over $200 million in VC funding, Kobalt is changing the way the music industry does business and putting more money into musicians’ pockets in the process.

In Part I of this series, I walked through the company’s founding story and its overall structure. There are two core theses that Kobalt bet on: 1) that the shift to digital music could transform the way royalties are tracked and paid, and 2) that music streaming will empower a growing middle class of DIY musicians who find success across countless niches.

How a Swedish saxophonist built Kobalt, the world’s next music unicorn

This article focuses on the complex way royalties flow through the industry and how Kobalt is restructuring that process (while Part III will focus on music’s middle class). The music industry runs on copyright administration and royalty collections. If the system breaks — if people lose track of where songs are being played and who is owed how much in royalties — everything halts.

Kobalt is as much a compliance tech company as it is a music company: it has built a quasi “operating system” to more accurately and quickly handle this using software and a centralized approach to collections, upending a broken, inefficient system so everything can run more smoothly and predictably on top of it. The big question is whether it can maintain its initial lead in doing this, however.

The business of a song

GettyImages

Image via Getty Images / Mykyta Dolmatov

Read more: https://techcrunch.com/2019/09/11/how-kobalt-is-simplifying-the-killer-complexities-of-the-music-industry/

New machine learning technologies, user interfaces and automated content creation techniques are going to expand the personalization of storytelling beyond algorithmically generated news feeds and content recommendation.

The next wave will be software-generated narratives that are tailored to the tastes and sentiments of a consumer.

Concretely, it means that your digital footprint, personal preferences and context unlock alternative features in the content itself, be it a news article, live video or a hit series on your streaming service.

The title contains different experiences for different people.

Netflix is experimenting with different episode orders for ‘Love, Death & Robots’

From smart recommendations to smarter content

When you use Youtube, Facebook, Google, Amazon, Twitter, Netflix or Spotify, algorithms select what gets recommended to you. The current mainstream services and their user interfaces and recommendation engines have been optimized to serve you content you might be interested in.

Your data, other people’s data, content-related data and machine learning methods are used to match people and content, thus improving the relevance of content recommendations and efficiency of content distribution.

However, so far the content experience itself has mostly been similar to everyone. If the same news article, live video or TV series episode gets recommended to you and me, we both read and watch the same thing, experiencing the same content.

That’s about to change. Soon we’ll be seeing new forms of smart content, in which user interface, machine learning technologies and content itself are combined in a seamless manner to create a personalized content experience.

What is smart content?

Smart content means that content experience itself is affected by who is seeing, watching, reading or listening to content. The content itself changes based on who you are.

We are already seeing the first forerunners in this space. TikTok’s whole content experience is driven by very short videos, audiovisual content sequences if you will, ordered and woven together by algorithms. Every user sees a different, personalized, “whole” based on her viewing history and user profile.

At the same time, Netflix has recently started testing new forms of interactive content (TV series episodes, e.g. Black Mirror: Bandersnatch) in which user’s own choices affect directly the content experience, including dialogue and storyline. And more is on its way. With Love, Death & Robots series, Netflix is experimenting with episode order within a series, serving the episodes in different order for different users.

Netflix is pursuing more interactive content, including, maybe, a rom-com

Some earlier predecessors of interactive audio-visual content include sports event streaming, in which the user can decide which particular stream she follows and how she interacts with the live content, for example rewinding the stream and spotting the key moments based on her own interest.

Simultaneously, we’re seeing how machine learning technologies can be used to create photo-like images of imaginary people, creatures and places. Current systems can recreate and alter entire videos, for example by changing the style, scenery, lighting, environment or central character’s face. Additionally, AI solutions are able to generate music in different genres.

Now, imagine, that TikTok’s individual short videos would be automatically personalized by the effects chosen by an AI system, and thus the whole video would be customized for you. Or that the choices in the Netflix’s interactive content affecting the plot twists, dialogue and even soundtrack, were made automatically by algorithms based on your profile.

Personalized smart content is coming to news as well. Automated systems, using today’s state-of-the-art NLP technologies, can generate long pieces of concise, comprehensible and even inventive textual content at scale. At present, media houses use automated content creation systems, or “robot journalists”, to create news material varying from complete articles to audio-visual clips and visualizations. Through content atomization (breaking content into small modular chunks of information) and machine learning, content production can be increased massively to support smart content creation.

Say that a news article you read or listen to is about a specific political topic that is unfamiliar to you. When comparing the same article with your friend, your version of the story might use different concepts and offer a different angle than your friend’s who’s really deep into politics. A beginner’s smart content news experience would differ from the experience of a topic enthusiast.

Content itself will become a software-like fluid and personalized experience, where your digital footprint and preferences affect not just how the content is recommended and served to you, but what the content actually contains.

Automated storytelling?

How is it possible to create smart content that contains different experiences for different people?

Content needs to be thought and treated as an iterative and configurable process rather than a ready-made static whole that is finished when it has been published in the distribution pipeline.

Importantly, the core building blocks of the content experience change: smart content consists of atomized modular elements that can be modified, updated, remixed, replaced, omitted and activated based on varying rules. In addition, content modules that have been made in the past, can be reused if applicable. Content is designed and developed more like a software.

Currently a significant amount of human effort and computing resources are used to prepare content for machine-powered content distribution and recommendation systems, varying from smart news apps to on-demand streaming services. With smart content, the content creation and its preparation for publication and distribution channels wouldn’t be separate processes. Instead, metadata and other invisible features that describe and define the content are an integral part of the content creation process from the very beginning.

Turning Donald Glover into Jay Gatsby

With smart content, the narrative or image itself becomes an integral part of an iterative feedback loop, in which the user’s actions, emotions and other signals as well as the visible and invisible features of the content itself affect the whole content consumption cycle from the content creation and recommendation to the content experience. With smart content features, a news article or a movie activates different elements of the content for different people.

It’s very likely that smart content for entertainment purposes will have different features and functions than news media content. Moreover, people expect frictionless and effortless content experience and thus smart content experience differs from games. Smart content doesn’t necessarily require direct actions from the user. If the person wants, the content personalization happens proactively and automatically, without explicit user interaction.

Creating smart content requires both human curation and machine intelligence. Humans focus on things that require creativity and deep analysis while AI systems generate, assemble and iterate the content that becomes dynamic and adaptive just like software.

Sustainable smart content

Smart content has different configurations and representations for different users, user interfaces, devices, languages and environments. The same piece of content contains elements that can be accessed through voice user interface or presented in augmented reality applications. Or the whole content expands into a fully immersive virtual reality experience.

In the same way as with the personalized user interfaces and smart devices, smart content can be used for good and bad. It can be used to enlighten and empower, as well as to trick and mislead. Thus it’s critical, that human-centered approach and sustainable values are built in the very core of smart content creation. Personalization needs to be transparent and the user needs to be able to choose if she wants the content to be personalized or not. And of course, not all content will be smart in the same way, if at all.

If used in a sustainable manner, smart content can break filter bubbles and echo chambers as it can be used to make a wide variety of information more accessible for diverse audiences. Through personalization, challenging topics can be presented to people according to their abilities and preferences, regardless of their background or level of education. For example a beginner’s version of vaccination content or digital media literacy article uses gamification elements, and the more experienced user gets directly a thorough fact-packed account of the recent developments and research results.

Smart content is also aligned with the efforts against today’s information operations such as fake news and its different forms such as “deep fakes” (http://www.niemanlab.org/2018/11/how-the-wall-street-journal-is-preparing-its-journalists-to-detect-deepfakes). If the content is like software, a legit software runs on your devices and interfaces without a problem. On the other hand, even the machine-generated realistic-looking but suspicious content, like deep fake, can be detected and filtered out based on its signature and other machine readable qualities.


Smart content is the ultimate combination of user experience design, AI technologies and storytelling.

News media should be among the first to start experimenting with smart content. When the intelligent content starts eating the world, one should be creating ones own intelligent content.

The first players that master the smart content, will be among tomorrow’s reigning digital giants. And that’s one of the main reasons why today’s tech titans are going seriously into the content game. Smart content is coming.

Read more: https://techcrunch.com/2019/04/13/get-ready-for-a-new-era-of-personalized-entertainment/

The scales are about to tip in favor of streaming music becoming the number one driver of global recorded music revenues — a shift that appears to be on track for sometime this year. According to a new industry report, global recorded music revenues jumped 9.7 percent in 2018 to reach $19.1 billion — up from $17.4 billion in 2017. Streaming music revenues, in particular, now account for nearly half (47 percent) of global revenue, thanks to a sizable 32.9 percent jump in paid streaming last year. This brought streaming revenues to $8.9 million in 2018, and puts them on track for a further jump in 2019.

This is the fourth consecutive year of growth for the global music market, and the highest rate of growth since IFPI — the music industry trade group behind the new report — first started tracking the market in 1997.

Paid streaming accounted for the majority of streaming’s contribution to revenues, with a 37 percent share of the market versus ad-supported streaming’s 10 percent share.

At year-end, there were 255 million users of paid subscription streaming accounts, the report found.

Meanwhile, physical disks dropped 10.1 percent over the past year, to account for 24.7 percent of revenues. Within that segment, vinyl is still growing — it posted its 13th consecutive year of growth, to reach a 3.6 share of the market. But it couldn’t make up for the fact that physical format revenue, overall, still declined.

As consumers drop physical disks, they continue to turn to digital.

Digital revenues grew by 21.1 percent in 2018 to reach $11.2 billion — which represents the first time they’ve crossed the $10 billion mark, the report noted. Within this category, streaming grew by 34 percent to reach $8.9 billion (~$7 billion was paid subscription streaming), while downloads declined 21.2 percent to 7.7 percent of the market.

In 38 markets, digital makes up more than half of revenues, the report said.

Revenues from performance rights and synchronization revenue (the use of music in TV, movies, games and ads), represented a 14 percent and 2.3 percent share of the total music market, respectively.

North America, in particular, posted another year of double-digit revenue growth with a 14 percent jump, with strong streaming growth (33.4 percent) offsetting the physical revenue declines (-22 percent).

Asia and Australia overtook Europe to become the second largest global region for revenues with 11.7 percent growth. And Latin America was the fastest growing region, with 16.8 percent growth.

In order, the top markets by revenue were: the U.S., Japan, the U.K., Germany, France, South Korea, China, Australia, Canada and Brazil.

Read more: https://techcrunch.com/2019/04/02/streaming-accounted-for-nearly-half-of-music-revenues-worldwide-in-2018/

A new version of “The Twilight Zone,” hosted and executive produced by “Get Out” director Jordan Peele, is set to premiere on CBS All Access on April 1.

CBS aired a teaser during the Super Bowl, but it didn’t include any actual footage. So this is the first time we’re getting a real taste of what the show will be like.

This trailer is still pretty fast-paced, not going in-depth on any of the stories. Basically, it’s a montage of famous people — including Kumail Nanjiani, John Cho, Sanaa Lathan, Adam Scott, Allison Tolman and Steven Yeun — looking scared or alarmed, accompanied by that oh-so-recognizable theme music.

CBS All Access hasn’t had as many splashy content announcements as some of the other new (or yet-to-launch) streaming services, but with “Twilight Zone” and an entire lineup of Star Trek spin-offs, it could become a real destination for science fiction fans.

Peele, meanwhile, has been pretty busy. He’s got a new movie (“Us”) set for release in March, and “Weird City,” a series he co-created, just launched on YouTube Premium.

Read more: https://techcrunch.com/2019/02/21/cbs-all-access-twilight-zone-trailer/