Tag Archives: advertising

Article Roundup and CBS-YouTube Data

A number of interesting articles across the net, CBS|YouTube numbers for the past week, and some upcoming surprises.

First off, the articles:

The Fuzzy Math of Big Media’s Digital Revenue – at AdAge.

It seems like every major player expects to make US$500 Million from digital ad revenues, even though everyone defines digital differently. Good read to get an idea of who’s playing where.

Is Mining Virtual Gold Exploitative? – at MTV Overdrive

This is one of those mind-blowing news segments straight out of some Sci-Fi book. Imagine hordes of Chinese adolescents working twelve-hour shifts mining gold… virtual gold, that is. The gold in question exists only inside the virtual worlds of World of Warcraft (WoW) and is sold through international brokers to wealthier players who lack the time (or skill) to obtain it on their own. On a similar vein (pun fully intended) a recent press release announced Anshe Chung had become Second Life’s first virtual millionaire. Don’t you just love this?

Will Paying for User Video Pay Off? – at GigaOM

A nice round-up of Internet video companies that pay their users for uploaded content.

YouTube vs TV – at Mashable
Apparently, internet video websites are stealing users away from regular television (according to a BBC report – not that I trust the BBC a whole lot, anyway). But this seems reasonable – after all, time spent watching internet video is time spent away from the TV.

Why the Verizon/YouTube deal doesn’t matter – at CinemaTech
A simple explanation of why this YouTube/Verizon deal is not important… mainly, it’s too restrictive (which is exactly the opposite of why YouTube was such a success in the first place).

And now the good stuff:

All the coding/learning time paid off and I now have one week’s worth of CBS|YouTube data which I’ll be reporting on this week.

Total Views for CBS videos on YouTube between midnight November 21 and midnight November 28 were: 6,849,294.

Most Total Daily Views were on Wednesday, November 22nd (1,333,848) and Least Total Daily Views were today, Tuesday, November 28th (410,094).

Most Daily Views for any particular show were on Wednesday, November 23rd: 309,188 viewers watched Michael Richards (“Kramer”) Apologize.

Please note that since I do not have direct control over YouTube’s servers, these numbers may be off by a couple of late-night viewers. Nothing serious, in any case.

Stay tuned for graphics and additional data.

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A Recap of Recent Articles

Yesterday’s article – Analyzing the CBS YouTube Stats – proved to be very popular, more than doubling the number of visitors and sending page views through the roof.

So, to welcome all the new blog readers, a short recap of our latest posts is in order.

Remember that you can subscribe by email to the blog if you want to receive new articles on your inbox. Simply click here to subscribe. No spam, just the latest article.

On to the recap…

Analyzing the YouTube Stats attempts to shed some light on the recent press release from CBS regarding their first month on YouTube. Using their Top-15 videos and comparing to a more recent Top-15, we can analyze the viewership volume of newer videos and determine their viral growth.

Google Does Video Graphs critiques Google Video’s latest feature, view stats for your videos, and shows where there’s room for improvement.

Blast From the Past – Multidimensional Data Analysis presents a graph I came up with years ago, while doing rating’s analysis for a TV network. If you’re a fan of Edward Tufte, this one’s for you.

The Advertiser’s Dilemma is about optimizing ad purchases in the Internet video age. When videos go viral overnight, and go cold almost as fast, how to you place your ads to maximize exposure while minimizing cost?

An Informal Chat with Second Life Creator Philip Rosedale – random musings from the recent Forbes MEET Forum (held at the Beverly Hills Hotel in Los Angeles).

Rethinking Ratings analyzes current television rating methods and why they’re inappropriate for the Internet video industry. Suggestions for improvement.

Where are the Editors is where I ramble about the need for trustworthy editors in an era of endless information. This was a recurrent theme at the Forbes MEET Forum (even though this article was posted before the conference).

Hacking at Apple Stores is a short piece about the copious amounts of personal information people leave behind on the computers on display at Apple Stores.

Why Google Should Buy YouTube – posted before the actual purchase, this articles presents a number of reasons why buying YouTube would add enormous value to Google… and why the US$1.65 Billion they eventually paid for it might actually be a bargain.

Case Study: NBC’s Heroes details the good and the bad about how NBC is taking advantage of Digital Media Integration with their new hit series.

The Paris Hilton School of Blogging is a humorous look at name-dropping in blogs and its advertising value.

Google Media – an in-depth analysis of the way Google will change the way you experience music, television and media in general. Includes interface mock-ups.

Well, there you go… Now you have something to read over Thanksgiving.

Have fun and come back soon!

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Google Does Video Graphs

Well, it seems someone at Google is listening. Things can only get better.

I was checking out the videos at The WorldTV Internet Charts and clicked on one of the Google Videos. After watching the video I noticed that, just below the star ratings, it said “All time views: 712,721 »“. So you know I had to click on the little chevron symbol to see what lay beneath these numbers.

And Voilà!

Google Video Graphs

There they were… historic audience graphs for the last week, and a table showing the All time Views & Rank, as well as Yesterday’s Views & Rank, including how many were via email or embedded in blogs.

Hey, it’s not the Google TV Dashboard I wrote about, but it’s a start.

As a video producer or advertiser, I’d also like to know how many people watched the entire video and how long did the rest of the viewers watch. These graphs would look something like this (we could call it the “saddle-graph“):

Saddle Chart of View Completion

The name, of course, comes from the saddle shape of the graph. I haven’t seen one of these but I think it’s safe to say that while many viewers would stop watching a video at the beginning, those that kept watching would tend to stay until the end, given the time they had already invested in the video. That’s why you get the peak at 100%. In television, you tend to see graphs like these for shows that tell a story (and thus capture the viewer), while for other types of content you see more irregular graphs.

The Reports page for your uploaded videos still only shows a simple table with Page Views & Downloads. You can choose the time frame for the reports but that’s about all you get.

Page Views & Downloads at Google Video Advanced Reports

And the numbers you do get, don’t necessarily match the ones on the Video page. For example, my two videos of the Atlanta Aquarium show 1315 & 2873 Page Views on the Advanced Report page, but if I go to the actual link and watch the video, I see 1330 & 2957 respective All Time Views. Not exactly dependable, but I’m sure they will eventually get it right.

There’s more information at the Google Video Blog, including a great new way to add comments that link to exact points on a video (so if you think the funny bits begin after the first three-and-a-half boring minutes, you can link straight to them).

Want more articles related to this post? Check these out:

The Advertiser’s Dilemma

Rethinking Ratings

Why Google Should Buy YouTube

Google Media

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Two Interesting Articles from Advertising Age

Advertising Age has a couple of interesting articles today:

Ad Age Digital

User-Generated Video Gets Its Own TV Channel

According to this article, Fame TV is a new channel dedicated entirely to consumer-generated videos, airing on the BskyB satellite network in the UK and Ireland. Users can upload their videos for a $3 fee -there’s also a deal with Revver for content- and these will be aired using an innovative format: nine boxes will be on the screen at all times, each one showing a different video. Each box has a code so that viewers can vote via SMS for their favorite show. In the case of Revver videos, Revver will pay a percentage of the SMS revenues to each video creator.

I’m assuming that videos getting lots of SMS votes, will be aired more often to create even more revenue. Judging from the success of shows like “America’s Funniest Videos,” the success of the idea seems guaranteed. It’ll make for a great time-waster and sure beats channel surfing.

It will initially lack advertising, though a good idea would be to run advertising in the center box (an even better idea would be to user-generated advertising, a la CurrentTV’s V-CAM (Viewer Created Ad Messages)).

Locally, this would be a great idea for networks to fill an hour or two of late night infomercial infested air time.

and the other article is:

Ad Age Media Works
Why TV Needs Commercial Ratings — Now

CBS‘ Chief Research Officer, David F. Poltrack, explains in great detail why it’d be smart for the television networks to measure ratings by the number of people watching commercials instead of the number of people watching the shows.

While this may sound counterintuitive at first, he gives a detailed explanation oh what’s happening with DVRs. Viewers are increasingly using DVRs to watch TV shows at their convenience. As I’ve previously mentioned here, network competition is moot when you can record both competing shows and watch them both at a later time.

When viewers have a DVR, more of them watch the shows after the fact than live. And about 40% of these viewers actually watch the commercials. Well, according to Poltrack, these eyeballs are not being counted, since the current system relies on live viewings (because advertisers automatically assume that DVR owners will fast-forward through their expensive commercials).

With the proper measuring system in place, viewers who watch the ads will be accounted for, while those who skip them won’t. Sounds fair to me, but go read the whole article… recommended.

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The Advertiser’s Dilemma

The typical life of an internet video goes somewhat like this: someone uploads the video to a video sharing website (YouTube, Google Video, Metacafe, Dailymotion, your pick) and sends links to his friends telling them to watch the video. One of them thinks it’s funny and passes it around. Some other guy finds it on the website, writes a comment and shares it with his contact list. If the video is really funny, sometimes (not always) it will explode and become an internet hit (like the Star Wars kid or Pinky the Cat). Millions will watch it and pass it around. And eventually it’ll become old and die a natural death (sometimes to be resurrected further down the line).

As an advertiser, you’d want to identify these runaway hits before they become a success (thus minimizing the number of eyeballs lost to your message). As a content producer, you want to convince advertisers to buy space on your video, before you lose the advertising value of all those eyeballs.

So, how do you maximize your return on advertising on web videos?

Traditionally, we could say advertisers have it easy (though I’m aware how hard ad buying really is). Television networks have been around for a long time, have time tested products, experienced programmers deciding what gets on the air and when, and a captive audience. They also have a company (AGB Nielsen) that measures all these shows down to the minute, reporting on the age, sex, location and income level of the viewers.

The internet, however, presents a whole new set of unknowns. Most content delivery websites have no control over their content producers nor do they know who these producers are. There’s no experienced programmer deciding what gets showcased (CurrentTV does, but they have a different business model and approach to web video); instead, other users rate the videos according to their personal tastes (and with a little work this system can be gamed very easily). Finally, there’s no real measuring going on (I’ve written about this particular issue here, here and here). Most websites simply tell you which video has been viewed the most, or ranked the highest (again, with highly suspect numbers). And what they know about their users is usually limited to their email address, what they’ve published, viewed or ranked and maybe an IP address that can suggest where they connect from (which used properly can be a very useful variables).

As an advertiser, you’d want to optimize your purchases (as opposed to buying ads on every conceivable video and hope one of them becomes an internet sensation). But by the time you can tell a video is a runaway hit, you’ve not only probably lost the majority of your potential audience (sort of like entering a pyramid scheme at the bottom), but you’ll also have to pay a premium to advertise on that now world famous video.

We need tools that can track the spread velocity of a video, their viralness, so to speak. We also need to define new demographic variables, based not only on age / sex / location / income but more importantly on interests and social connectivity. When you have 14-yr olds playing online games against 30-yr olds, age and sex are no longer as relevant as what interests these people share.

Of course you can simply blanket every uploaded video with your advertising, but would you rather be that ad on every lousy home video, or that cool ad on the hilariously popular video-du-jour?

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An Informal Chat with Second Life Creator Philip Rosedale

The first Forbes MEET Conference was a blast. The panels were great and the people attending were even better. The conference is more than worth the price of admission for the networking opportunities alone.

On day one I had the good fortune of sharing a lunch table with Chad Hurley and Chris Maxcy of YouTube, Neil Kleinman, Dean of the College of Media and Communication at UArts, Janet De Vries (Director of the President’s Office at UArts) and Philip Rosedale, the creator of Second Life.

Neil is doing some wonderful stuff over at UArts, including getting the College of Media Communications online and the students interested in all that the new media technologies have to offer. It would be great to see art students presenting their creations in a Second Life exhibit or theatre majors opening their shows on Second Life‘s version of Broadway.

Second Life, for those unfamiliar with it, is -to quote their website- “a 3-D virtual world entirely built and owned by its residents.” You travel to Second Life’s world by downloading a small program from their website and registering your “avatar” or virtual representation. Once inside the game, you decide whether you want to be male, female or something entirely different, like a bug. Choose your clothing, change your looks… anything you want. You can also buy land to build a house on (or a cabin, high-rise or space station). Set-up a clothing store and sell your shirts to other Second Life residents. Anything is possible here…

Many companies (Sun, Pontiac) have set-up shop inside Second Life, several residents are making good money buying and selling stuff (houses, cars, condos), and even Reuters has sent one of its reporters full time into Second Life – which I find mind-boglingly wonderful.

I don’t really have all that free time at the moment, even if I could build a lucrative business inside Second Life. So I asked Phil when will I be able to send my Second Life avatar to do work for me and report back at the end of the day. Phil laughed… this simply isn’t possible, yet. But, wouldn’t that be great? I guess that, eventually, avatars will be programmable to follow certain scripts and maybe even interact on their own with other avatars. Maybe then I could create for-hire armies (ok, or gophers) inside Second Life and rent their services out for a nice sum.

On a more serious note, Phil did mention that great things are coming to Second Life’s audio/video functions, including 3-D audio, which would allow you to determine where a sound is coming from (much like you do in games like Counter-Strike).

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San Francisco Updates

Just a quick update from San Francisco.

Tomorrow is my last day in San Francisco. In just a couple of days I’ve really gotten a nice feel for this town and really like it. There’s so much happening in the tech front… you could actually say they’re building the future here. Classes, conferences, companies… you name it, it’s here.

I went to the Exploratorium today and had a wonderful time. It’s great to see such a big museum built expressly to awaken the children’s imagination, curiosity and aspirations. And it’s not just for kids…

And now on to more blog related stuff…

The Forbes MEET 2006 conference was great. The panel format they used is simply outstanding and lends itself to very insightful conversations among the participants. The Forbes editors did a very good job of guiding the conversation and keeping things on track. I’m really glad there were zero powerpoint presentations (which usually end up being self-serving company ads). I’ll be posting details and observations of each panel as soon as I get back home.

Apparently, Comedy Central has asked YouTube to remove all of their material from their servers. Interesting. No talk yet of a Comedy Central YouTube Channel, a la CBS, although they are already selling their content on Google Video.

To wrap things up, it seems Google’s AdSense audio version is almost ready for release, which should give a nice boost to the podcast industry.

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Rethinking Ratings

Summary: An analysis of current television ratings methods, why they’re inappropriate for the timeless internet and digital video recorder era, and suggestions for improving them.

Traditional television ratings reports let TV executives and analysts study the behavior of a particular show or series, displaying the number of viewers each show had, broken down by demographic targets. This allows the television industry to determine which show won a particular time slot (e.g., Friday 9pm to 10pm), how it performed among a particular demographic (e.g., Males 18-34yrs) and how it has evolved (in the case of serials) over time (e.g., Are there more or less people watching it).

But what happens when viewers can watch any show at any time? When viewers don’t have to choose one show over another on a rival network? What happens when you can’t tell for sure who your viewers are?

The internet and TiVos give the viewer unprecedented freedom over when, where and what to watch. Soon it won’t be possible to tell for sure how many people are watching any given show, using traditional ratings tools such as AGB/Nielsen‘s Peoplemeters. Programming executives won’t have to worry about what the rival networks are showing at the same time as their new hit show. And ratings analysts won’t be able to track a new series’ behavior by simply looking at how each episode did on its air date.

Two hit shows going head-to-head on rival networks? Not a problem: watch one and record the other for later viewing (or get it from the Net). Missed last week’s premiere episode? No problem there either: watch it online, download it off bit torrent or pay for it on iTunes. Some of this you can easily track, but some you can’t.

Analysts will need to track each episode over time and then track the series as a whole. A VERY SIMPLIFIED graphic might look something like this, with a running total for each episode over the time of the series:

VERY simple ratings graphic

Any viewer can watch any episode from its air date to the end of the series (and beyond). This allows viewers to catch-up after the series has started or to catch any episode they may have missed. Of course, the whole concept of missing an episode disappears in the TiVo/Internet model. But in addition to tracking how many times a particular episode was watched or downloaded, you should also be tracking what’s happening with the rest of the show’s internet presence. Are viewers reading the characters’ blogs? Are they discussing the show in the forums? Are they setting up fan websites? Linking to the Myspace profiles? Uploading mashups of show clips? Not only must you track the show’s behavior over time and over several distribution methods, but you must also track and measure the user experience surrounding the show.

And finally, how do you solve the demographic problem: if you don’t know who your viewers are, how do you target them? The answer is both simple and complex. I believe that traditional demographic targets are on the way out. Social networks and special interest groups are the new targets… and these are much easier to track via the Internet than the old ones. You may not be able to tell whether a particular viewer is male or female, young or old, wealthy or not, but you can tell what news s/he reads, what games s/he plays and which people s/he hangs out with (to a certain degree, of course). One minor detail… you can’t (or shouldn’t) add apples and oranges. Traditional television ratings data categorizes viewers by demographic targets such as age, sex, location and income (because someone takes the time to visit each household in the sample and verify this information). And whereas traditional ratings analysis has always relied on a sample set of data subjects, internet traffic and behavior analysis has always examined the whole dataset. Eventually it shouldn’t be too hard to homogenize both sets of data, either by linking traditional television viewers to their online behaviors, or simply by expanding their interviews to include enough data to categorize them.

Currently, Google and YouTube limit their video data to a traditional web-traffic analysis mindset: most viewed, most recent, most subscribed. Coming from an Internet world, they fail to see the need (or maybe even the possibility) of better, more detailed reports (Yes, it could also be that they keep these reports hidden from the outside world).

As for me, I’d love to know how the most watched videos on YouTube evolved over time. Have they peaked? Are they growing? Who watches them? How about a Google Finance like chart, linking views to blog/news mentions? Which video has been linked-to the most (this one is actually on YouTube)? Which videos have been dugg and how many diggs did they get? Actually… I’d just love to work there and get it done myself!

Off to the MEET 2006 Forbes Conference

I’m off to Forbes’ MEET 2006 Conference (tomorrow and Wednesday at the Beverly Hills Hotel). The conference theme is:

Reaping Riches in the Media and Entertainment Revolution.

Check out the conference website for the agenda and list of speakers. I’m not sure what the blogging policy will be, but I’ll certainly try to post live if allowed.

After the conference I’ll be visiting San Francisco for a couple of days.

Leave a comment if you’re going…

CBS Launches YouTube Channel

CBS, one of the US leading television networks, has launched a YouTube channel. So far the content is limited to short clips from late night television, sports highlights, program promos and news items.

CBS Launches YouTube ChannelI’m not particularly impressed with the available content (no full length shows yet) but I really like the fact that CBS has taken this initiative. Late-night clips were already showing up on YouTube, so why not offer them straight from the source?

As of this writing, CBS’s YouTube channel has about one thousand subscribers and 33,000 views. As more -and better- content from traditional networks goes online, it’ll be interesting to see how they compare with user generated content. Will they reach the 37 million views attributed to smosh or surpass lonelygirl15‘s fifty thousand subscribers?

It’s great to see the traditional networks embrace their fears and venture online. CBS already has content distribution deals with iTunes (Lost is sold on iTunes for US$1.99 per episode), but I’m guessing they’ll release their shows for free on YouTube under a Google advertising supported model.

Interesting times, indeed.