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BuzzFeed Hires Mondelez Marketing Executive - WSJ - Wall Street Journal - 10 Dec 2016 02:11


[[html]]By Steven Perlberg and Alexandra Bruell Dec. 7, 2016 5:07 p.m. ET <br><br>BuzzFeed has tapped a top marketing executive from snack food giant Mondelez days after the digital media companys chief marketing officer announced his departure. <br><br>Laura Henderson, global head of content and media monetization at Mondelez, will join BuzzFeed as senior vice president of marketing, a newly created role, according to a company memo reviewed by The Wall Street Journal.<br><br>Former BuzzFeed CMO Frank Cooper recently left the company after 18 months and joined New York asset manager BlackRock. Like Mr. Cooper, Ms. Henderson will report to BuzzFeed President Greg Coleman.<br><br>Ms. Hendersons background in snack-food marketing will likely serve her well at BuzzFeed, whose Tasty food channel has seen huge growth thanks to BuzzFeeds digital video efforts on Facebook.<br><br>At its NewFront presentation for advertisers in May, BuzzFeed made Tasty a central part of its pitch to marketers. <br><br>For her part, Ms. Henderson was among the Mondelez executives behind the companys recent decision to push more into investing in its own content properties, like a Stride Gum-branded skydiving event that aired on Fox. Mondelez, which owns brands like Triscuit crackers and Oreo cookies, has also worked with BuzzFeed on sponsored work.<br><br>She has worked with us on their new content strategy which has touched everything from integrations of Tasty and its global franchises to the co-creation of new content areas across their brands, Mr. Coleman said in the memo.<br><br>Ms. Hendersons appointment comes at an important moment for BuzzFeed. Like many other digital media startups, it has attracted significant capital from investors and must deliver on high expectations by beating out a slew of competitors for digital ad dollars. The company was among the first digital media outlets to make a big bet on fashioning sponsored content for brands ranging from Purina to General Electric.<br><br>In recent months, BuzzFeed and other digital companies have been stepping up their video efforts in search of newer revenue streams, pouring resources into creating more video content for their editorial channels and on behalf of brands. <br><br>The company recently raised $200 million from Comcasts NBCUniversal, which doubled the TV giants stake. That deal gave BuzzFeed a post-money valuation of about $1.7 billion, meaning its valuation was essentially unchanged from NBCUs first investment last year, according to people familiar with the matter.<br><br>Mondelez has been making changes of its own. The company recently tapped Kraft Heinz Co.s Bob Rupczynski as vice president and head of global media and digital following the departure of senior media executive Bonin Bough, according to Ad Age. <br><br>Write to Steven Perlberg at moc.jsw|greblrep.nevets#moc.jsw|greblrep.nevets and Alexandra Bruell at moc.jsw|lleurb.ardnaxela#moc.jsw|lleurb.ardnaxela <br><br>[[/html]] - Comments: 0

John Rood To Head Marketing For Disney Channels As Richard Loomis Exits - Deadline - 21 Sep 2016 02:33


[[html]]Longtime Disney marketing exec John Rood is returning to the company as SVP Marketing, Disney Channels Worldwide. He replacesRichard Loomis, who is stepping down and will leavenext month to pursue other ventures. Roods appointment is effective immediately.<br><br><img class=" wp-image-1201500558" src=";h=172" alt="Disney Channel Logo 2015_edited-1" width="223" height="172"/><br><br>Rood, who has been consulting exclusively with Disney Channels Worldwide for the past 10 months, will be responsible for on-channel promotion and off-channel marketing for the Disney Channel, Disney XD and Disney Junior portfolio.Hewill also oversee creative marketing support for the Disney Media Sales and Marketing team.<br><br><img class="wp-image-1201700759" src=";h=135" alt="Disney XD logo featured" width="207" height="135"/><br><br>Disney XD<br><br>Under Loomis, the Disney Channel Marketing team receivedEmmy Awards, PromaxBDA Awards, CTAM Mark Awards and Telly Awards. He joined Disney Channels in 2007 and was promoted to SVP and Chief Marketing Officer in 2012.<br><br>Richard has made enormous contributions to Disney Channels Worldwide during his tenure, said Disney Channels Worldwide president and Chief Creative Officer Gary Marsh. As an important and highly respected member of my senior team, his leadership, creativity and strategic expertise have been invaluable to me.<br><br>Said Loomis, From High School Musical 2and Descendantsto the launch of Disney XD and Disney Junior, its been an amazing ride covering a lot of ground in the U.S. and all around the world, and for that I feel very proud. I also feel that its the right time to explore the next chapter that awaits me and between now and the next four weeks, will transition with my good friend and successor John Rood who will have the support of a truly outstanding marketing and creative team.<br><br>Rood, who most recently served as EVP DC Entertainment,was with The Walt Disney Company from 2000-2010, most recently as SVP Marketing, ABC Family from 2004-10. Before that, he served as served as VP, Marketing, Disney ABC Television Group and was responsible for driving the brand strategy and marketing campaigns for Disney Channel, Toon Disney and SOAPNet. He also led the re-branding projects for Disney Channel and Jetix/Fox Kids Channels worldwide.<br><br>John Rood is a maker and a builder, with a rare combination of creative and strategic leadership skills and an innate understanding of the Disney brand, said Marsh, to whom Rood reports. He has a unique capacity to transform how large teams address viewers evolving needs in a complex, multi-platform portfolio.<br><br>[[/html]] - Comments: 0

Artificial intelligence is changing SEO faster than you think - TechCrunch - 01 Jul 2016 05:23


[[html]]<img src="" class=""/><br><br>By now everyone has heard of Googles RankBrain, the new artificial intelligence machine learning algorithm that is supposed to be the latest and greatest from Mountain View, Calif. What many of you might not realize, however, is just how fast the SEO industry is changing because of it. In this article, Ill take you through some clear examples of how some of the old rules of SEO no longer apply, and what steps you can take to stay ahead of the curve in order to continue to provide successful SEO campaigns for your businesses.<br><br>So what is artificial intelligence?<br><br>There are generally three different classifications of artificial intelligence:<br><br>Artificial Narrow Intelligence (ANI): This is like AI for one particular thing (e.g. beating the world champion in chess).Artificial General Intelligence (AGI): This is when the AI can performall things. Once an AI can perform like a human, we consider it AGI.Artificial Superintelligence (ASI): AI on a much higher level for all things (e.g. beyond the capabilities of a single human).<br><br>When we talk about the context of Googles RankBrain, and the machine learning algorithms that are currently running on Google, we are talking about Artificial Narrow Intelligence (ANI).<br><br>Actually, ANI has been around for some time. Ever wonder how those SPAM filters work in your email? Yep, thats ANI. Here are some of my favorite ANI programs: Google Translate, IBMs Watson, that cool feature on Amazon that tells you products that are recommended for you, self-driving cars and, yes, our beloved Googles RankBrain.<br><br>Within ANI, there are many different approaches. As Pedro Domingos clearly lays out in his book The Master Algorithm,data scientists trying to achieve the perfect AI can be grouped into five tribes today:<br><br>SymbolistsConnectionistsEvolutionariesBayesiansAnalogizers<br><br>Googles RankBrain is in the camp of the Connectionists. Connectionists believe that all our knowledge is encoded in the connections between neurons in our brain. And RankBrains particular strategy is whatexperts in the field call a back propagation technique,rebranded as deep learning.<br><br>Connectionists claim this strategy is capable of learning anything from raw data, and therefore is also capable of ultimately automating all knowledge discovery. Google apparently believes this, too. On January 26th, 2014, Google announcedit had agreed to acquire DeepMind Technologies, which was, essentially, a back propagation shop.<br><br>So when we talk about RankBrain, we now can tell peopleit is comprised of one particular technique (back propagation or deep learning) on ANI. Now that we have that out of the way, just how much is this field progressing? And, more importantly, how is it changing the business of SEO?<br><br>The exponential growth of technology (and AI)<br><br>Tim Urban from explains the growth of technology better than anyone in his article The AI Revolution: The Road to Superintelligence.<br><br>Here is what technological progress looks like, when you look back at history:<br><br><img class="aligncenter size-full wp-image-1329606" src=";h=464" alt="1" width="651" height="464"/><br><br>But, as Urban points out, in reality, you cant see whats to your right (the future). So here is how it actually feels when you are standing there:<br><br><img class="aligncenter size-full wp-image-1329607" src=";h=546" alt="2" width="767" height="546"/><br><br>What this chart showsis that when humans try to predict the future, they always underestimate. This is because they are looking to the left of this graph, instead of to the right.<br><br>However, the reality is, human progress takes place at a faster and faster rate as time goes on. Ray Kurzweil calls this the Law of Accelerating Returns. The scientific reasoning behind his original theory is that more advanced societies have the ability to progress at a faster rate than less advanced societies becausetheyre more advanced. Of course, the same can be applied to artificial intelligence and the growth rate we are seeing now with advanced technology.<br><br>We see this with computing resources right now. Here is a visualization that gives you the perspective of just how fast things can changebecause ofthis Law of Accelerating Returns:<br><br><img class="aligncenter size-full wp-image-1329608" src=";h=548" alt="3" width="975" height="548"/><br><br>As you can clearly see, and as we all can intuitively feel, the growth of advanced processing and computers has benefited from this Law of Accelerating Returns. Here is another shocking revelation: At some point, the processing power for an economical computer will surpass that of not only a single human, but for all humans combined.<br><br><img class="aligncenter size-full wp-image-1329609" src=";h=832" alt="4" width="975" height="832"/><br><br>In fact, it now appears that we will be able to achieve Artificial General Intelligence (AGI) some time around 2025. Technology is clearly expanding at a faster and faster pace, and, by many accounts, most of us will be caught off guard.<br><br>The rise of superintelligence<br><br>As I have explained above, Googles RankBrain is just one form ofANI, which means that, while it can perform things better than a human in one specific area, it is just that: a relatively weak form of artificial intelligence.<br><br>But we may be blindsided by how fast this weak intelligence might easily turn into something with whichwe have no idea how to deal.<br><br><img class="aligncenter size-full wp-image-1329610" src=";h=767" alt="5" width="975" height="767"/><br><br>Here, you can clearly see that Googles RankBrain, while super intelligent on one particular task, is still in the general context of things, fairly unintelligent on the intelligence scale.<br><br>But what happens when we apply the same Law of Accelerating Returns to artificial intelligence? Tim Urban walks us through the thought experiment:<br><br>so as A.I. zooms upward in intelligence toward us, well see it as simply becoming smarter, for an animal. Then, when it hits the lowest capacity of humanity Nick Bostrom uses the term the village idiot well be like, Oh wow, its like a dumb human. Cute! The only thing is, in the grand spectrum of intelligence, all humans, from the village idiot to Einstein, are within a very small range so just after hitting village idiot level and being declared to be AGI, itll suddenly be smarter than Einstein and we wont know what hit us.<br><br><img class="aligncenter size-full wp-image-1329611" src=";h=796" alt="6" width="975" height="796"/><br><br>So what does this mean for the business of SEO and the artificial intelligence that is upon us?<br><br>SEO has changed forever<br><br>Before we get into predicting the future, lets take inventory on how RankBrain has already changed SEO. I sat down with Carnegie Mellon alumnus and friend Scott Stouffer, now CTO and co-founder of Market Brew, a company that provides search engine models for Fortune 500 SEO teams. As a search engineer himself, Stouffer had a unique perspective over the past decade that most professionals in that industry dont get to see. Here are some of his tips for the SEO industry when it comes to Googles new emphasis on artificial intelligence.<br><br>Todays regression analysis is seriously flawed<br><br>This is the biggest current fallacy of our industry. There have been many prognosticators every time Googles rankings shift in a big way. Usually, without fail, a few data scientists and CTOs from well-known companies in our industry will claimthey have a reason! for the latest Google Dance. The typical analysis consists of perusing through months of ranking data leading up to the event, then seeing how the rankings shifted across all websites of different types.<br><br>With todays approach to regression analysis, these data scientists point to a specific type of website that has been affected (positively or negatively) and conclude with high certainty that Googles latest algorithmic shift was attributed to a specific type of algorithm (content or backlink, et al.) that these websites shared.<br><br>However, that isnt how Google works anymore. Googles RankBrain, a machine learning or deep learning approach, works very differently.<br><br>Within Google, there are a number of core algorithms that exist. It is RankBrains job to learn what mixture of these core algorithms is best applied to each type of search results. For instance, in certain search results, RankBrain might learn that the most important signal is the META Title.<br><br>Adding more significance to the META Title matching algorithm might lead to a better searcher experience. But in another search result, this very same signal might have a horrible correlation with a good searcher experience. So in that other vertical, another algorithm, maybe PageRank, might be promoted more.<br><br><img class="aligncenter size-full wp-image-1329612" src=";h=234" alt="7" width="975" height="234"/><br><br>This means that, in each search result, Google has a completely different mix of algorithms. You can now see why doing regression analysis over every site, without having the context of the search result that it is in, is supremely flawed.<br><br>For these reasons, todays regression analysis must be done by each specific search result. Stouffer recently wrote about a search modeling approach where the Google algorithmic shifts can be measured. First, you can take a snapshot of what the search engine model was calibrated to in the past for a specific keyword search. Then, re-calibrate it after a shift in rankings has been detected, revealing the delta between the two search engine model settings. Using this approach, during certain ranking shifts, you can see which particular algorithm is being promoted or demoted in its weighting.<br><br>When humans try to predict the future, they always underestimate.<br><br>Having this knowledge, we can then focus on improving that particular part of SEO for sites for those unique search results. But that same approach will not (and cannot) hold for other search results. This is because RankBrain is operating on the search result (or keyword) level. It is literally customizing the algorithms for each search result.<br><br>Stay niche to avoid misclassification<br><br>What Google also realized is that they could teach their new deep learning system, RankBrain, what good sites look like, and what bad sites look like. Similar to how they weight algorithms differently for each search result, they also realized that each vertical had different examples of good and bad sites. This is undoubtedly because different verticals have different CRMs, different templates and different structures of data altogether.<br><br>When RankBrain operates, it is essentially learning what the correct settings are for each environment. As you might have guessed by now, these settings are completely dependent on the vertical on whichit is operating. So, for instance, in the health industry, Google knows that a site like is a reputable site that they would like to have near the top of their searchable index. Anything that looks like the structure of WebMDs site will be associated with the good camp. Similarly, any site that looks like the structure of a known spammy site in the health vertical will be associated with the bad camp.<br><br>As RankBrain works to group good and bad sites together, using its deep learning capabilities, what happens if you have a site that has many different industries all rolled up into one?<br><br><img class="aligncenter size-full wp-image-1329613" src=";h=423" alt="8" width="975" height="423"/><br><br>First, we have to discuss a bit more detail on how exactly this deep learning works. Before grouping together sites into a good and bad bucket, RankBrain must first determine what each sites classification is. Sites like and WebMD.comare pretty easy. While there are many different sub-categories on each site, the general category is very straightforward. These types of sites are easily classifiable.<br><br>But what about sites that have many different categories? A good example of these types of sites are the How-To sites. Sites that typically have many broad categories of information. In these instances, the deep learning process breaks down. Which training data does Google use on these sites? The answer is: It can be seemingly random. It may choose one category or another. Forwell-known sites, like Wikipedia, Google can opt-out of this classification process altogether, to ensure that the deep learning process doesnt undercut their existing search experience (aka too big to fail).<br><br>The field of SEO will continue to become extremely technical.<br><br>But for lesser-known entities, what will happen? The answer is, Who knows? Presumably, this machine learning process has an automated way of classifying each site before attempting to compare it to other sites. Lets say a How-To site looks just like WebMDs site. Great, right?<br><br>Well, if the classification process thinks this site is about shoes, then it is going to be comparing the site to Nikes site structure, not WebMDs. It just might turn out that their site structure looks a lot like a spammy shoe site, as opposed to a reputable WebMD site, in which case the overly generalized site could easily be flagged as SPAM. If the How-To site had separate domains, then it would be easy to make each genre look like the best of that industry. Stay niche.<br><br>These backlinks smell fishy<br><br>Lets take a look at how this affects backlinks. Based on the classification procedure above, it is more important than ever to stickwithin your linking neighborhood, as RankBrain will know if something is different from similar backlink profiles in your vertical.<br><br>Lets take the same example as above. Say a company has a site about shoes. We know that RankBrains deep learning process will attempt to compare each aspect of this site with the best and worst sites of the shoe industry. So, naturally, the backlink profile of this site will be compared to the backlink profiles of these best and worst sites.<br><br>Lets also say that a typical reputable shoe site has backlinks from the following neighborhoods:<br><br>SportsHealthFashion<br><br>Now lets say that the companys SEO team decides to start pursuing backlinks from allthese neighborhoods,plus a new neighborhood from one of the CEOs previous connections to the auto industry. They are smart about it as well: They construct a cross-marketing free shoe offer for all new leases page that is created on the auto site, which then links to their new type of shoe. Totally relevant, right?<br><br>Well, RankBrain is going to see this and notice that this backlink profile looks a lot different than the typical reputable shoe site. Worse yet, it finds that a bunch of spammy shoe sites also have a backlink profile from auto sites. Uh oh.<br><br>And just like that, without even knowing what is the correct backlink profile, RankBrain has sniffed out what is good and what is bad for its search engine results. The new shoe site is flagged, and their organic traffic takes a nosedive.<br><br>The future of SEO and artificial intelligence<br><br>As we can see from the previous discussion on the Law of Accelerating Returns, RankBrain and other forms of artificial intelligence will at some point surpass the human brain. And at this point, nobody knows where this technology will lead us.<br><br>Some things are certain, though:<br><br>Each competitive keyword environment will need to be examined on its own;Most sites will need to stay niche to avoid misclassification; andEach site should mimic the structure and composition of their respective top sites in that niche.<br><br>In some ways, the deep learning methodology makes things simpler for SEOs. Knowing that RankBrain and similar technologies are almost on par with a human, the rule of law is clear: There are no more loopholes.<br><br>In other ways, things are a bit harder. The field of SEO will continue to become extremely technical. Analytics and big data are the order of the day, and any SEO that isnt familiar with these approaches has a lot of catching up to do. Those of you whohave these skills can look forward to a big payday.<br><br>Featured Image: Maya2008/Shutterstock[[/html]] - Comments: 0

Day in the life: How UK watchdog ASA polices 30000 advertising complaints a year - Digiday - 09 Apr 2016 07:27


[[html]]Policing online advertising in the U.K. is becoming an increasingly complex affair. Around 60 people out of the 110Advertising Standards Authority (ASA) staff wade through a sea of around 30,000 complaints a year related to about 20,000 different ads both TV and online.<br><br>Last year, the ASA ruled that over 4,500 ads must be changed, or were banned outright, the most infamous being betting company Paddy Powers national press ad in 2014, which offered incentives to bet on the outcome of Oscar Pistorius murder trial. The ad received 5,525 complaints and was banned after the ASA deemed it caused serious offence by trivializing the issues surrounding a murder trial, the death of a woman and disability.<br><br>ASA communications manager Matthew Wilson has an eye on all facets of the companys output. He works closely with the public affairs and complaints teams to help ensure the ASA stays on top of its ever-growing remit.<br><br>Advertisement<br><br>Digiday asked Wilson to share a journal of what he does on a typical day. Heres what he does, slightly edited for clarity:<br><br>8:15 a.m.: I endure the daily delight of contorting into imaginative shapes amongst the throng of commuters on the Central Line before arriving at our offices in Holborn. First things first, a brew.Ive checked emails on my work phone before getting in (bad habit), so hopefully there arent too many surprises in the inbox.<br><br>8:30 a.m.: My immediate task is to check for any ASA mentions in national and regional U.K. media. I package it up and circulate amongst senior-level colleagues. I also assess whether anything in the press cuttings poses a reputational risk. If it does, Ill flag it internally and decide on next steps. That might mean dropping a journalist a quick line to introduce myself, correcting any misconceptions and outlining our position or penning a Dear Sir letter in rebuttal.<br><br>9 a.m.: I scan a live calendar that we use to map out upcoming project work, key policy announcements, events and stakeholder engagement activity. It helps us coordinate the work of other teams and to schedule in where a piece of work needs communications input and support. There are some significant upcoming policy announcements and consultation launches, so quite a bit of my time is devoted to putting together media and PR plans to help promote this.<br><br>9:15 a.m: I feed into the work of teammates. The communications team is a close-knit unit of 10, with expertise in different area research, marketing, events, public affairs and we work closely on team objectives. The overlap between public affairs and press is considerable, and we work closely on policy announcements that are of interest to political and media opinion formers.<br><br>10:30 a.m.: I complete and send a briefing note to our chief executive, Guy Parker, for a forthcoming media interview with The Independent, in which hell speak about the progress made in thefive years since our online remit was extended to cover marketing claims on companies own websites and in social media under their control.<br><br>11 a.m.: I dip into our social media channels to see whos saying what about or to us and whether or not we need to engage or respond. Or just to scan if there are any interesting developments in adland that might be relevant to us, or if complaints about a particular campaign are starting to bubble up in the Twittersphere (we dont actually accept complaints via our feed) and that I need to flag internally.<br><br>11:30 a.m.: I catch up with my colleagues in our sister organization, the Committee of Advertising Practice (CAP). It writes the advertising codes that we administer. Its copy advice team offers expert advice to non-broadcast advertisers on how to create ad campaigns that stick to the rules. Their manager, David Hollis provides me with content for the latest e-newsletter, Insight, and I sign-off on it before we send it to thousands of marketing professionals to keep them up to speed with regulatory and policy developments.<br><br>12 p.m.: CAP is due to launch a full public consultation on introducing new rules around the advertising of food and soft drinks that are high in fat, salt and sugar. Im developing a communications plan to publicize this announcement. Theres already a lot of interest amongst national media, trade press as well as politicians about the substance of the proposals, so its crucial we have a clear and coherent strategy in place.<br><br>1 p.m.: Like clockwork. Lunch. Sacrosanct. News sites, sport pages and YouTube.<br><br>2 p.m.: Aside from our proactive PR, theres the daily task of handling and responding to incoming media enquiries. Im the first port of call for journalists who want to know about our work and policies.<br><br>Every Wednesday, we publish the outcome of our formal investigations which put on the public record whether an ad that we received complaints about broke the rules. Our decisions often prompt widespread and high-profile media coverage. So I pull together that information for journalists.<br><br>3 p.m.: We receive over 30,000 complaints a year about 20,000 or so ads. Around 90 percent arrive via our online complaints form, but we also accept them via telephone, letter and email. Not every complaint we receive will prompt an investigation. But every case is assessed by our complaint and investigations teams, who establish whether there appear to be problems under the rules and what action, if any, to take.<br><br>Given the busy mailbox, its important I work closely with our operations support manager, Tony Betham-Rogers. We have a meeting to assess incoming complaints and whether anything controversial is in the offing that might spark media interest.While the volume of complaints we receive is afactor in helping us judge whether something has caused serious or widespread offense, we cant, and we shouldnt, be hostage to complaint numbers: We have direct experience of online petitions driving thousands of complaints to us overnight as conversations in social media help mobilize and coordinate protests about various ad campaigns.<br><br>4 p.m.: Given the host of high-profile projects were working on food consultation, payday loans ad review, electronic cigarette ad restrictions, broadband pricing I need to keep tabs on how the policies around these topics are developing. I meet with our regulatory policy manager, Malcolm Philips, who coordinates the team that looksafter the nuts and bolts of the rules. Theyre cerebral types, and I nod sagely as Malcolm dispenses pearls of wisdom about how obscure bits of legislation will impact on the ad codes and our work.<br><br>5 p.m.: Starting early means the added bonus, if Im lucky, of heading off early. But as ever, I have my work phone on so will keep checking emails and handling the occasional out-of-office call from journalists.<br><br>[[/html]] - Comments: 0

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