Real-time programmatic buying optimizer Rocket Fuel this morning reported record revenue of $107 million for 2012, a 238% increase over 2011, and outpacing most programmatic marketplace growth estimates by a wide margin. The company attributed the rapid expansion to improvements in its core artificial intelligence, machine learning and robotic media trading systems, and the fact that existing customers have been expanding the amount of buying they place through Rocket Fuel’s systems, because they work so well. In fact, while Rocket Fuel did add an impressive number of new advertisers in 2012, its 93% growth in new customers trails its overall growth rate by a margin of more than two-to-one. But don’t worry about machines taking over the business anytime soon. If Rocket Fuel’s own growth is any indication, the type of technology they have been developing actually increases the need for human talent -- albeit not in the manual media trading part of the business. During 2012, Rocket Fuel increased its human resources 126% to 289 employees, including even more rocket scientists, but also sales, marketing and support teams. Much of that expansion, and a good chunk of Rocket Fuel’s revenue growth, came from its expansion into Europe. Rocket Fuel added six offices in 2012, including Amsterdam, Atlanta, Hamburg, Raleigh-Durham, Toronto, Washington DC, and now has offices in 15 cities worldwide. Rocket Fuel also entered the emerging Japanese programmatic buying market, aligning with that nation’s largest digital marketing company, cyber communications inc. (cci), a wholly-owned subsidiary of Dentsu. Under the terms of the strategic alliance, cci runs its digital ad management service, “PerformanceX Management,” on top of Rocket Fuel’s platform, offering full-service brand and direct response campaigns to clients. On the eve of this morning’s announcement, RTM Daily spoke with Founder and CEO George John to find out exactly what’s fueling Rocket Fuel’s growth. RTM Daily: What were the main drivers behind your 2012 success? George John: Well, the product just works well. Part of what we love, and what we love to hate about the advertising business, is the different phases of partnering with an advertiser or an agency, that are rational or irrational. We always know that it will be hard to get in their door, because there’s so many other people trying to get in there too, but once we’re in, it’s kind of beautiful and rationale things start to take over, because we perform. And if you’re always at the top of what performs for them, they’ll keep allocating more budget toward that. Most of our revenues -- about 84% of revenue in 2012 -- were from advertisers that were at least in their second quarter of spending with us. What we have seen is that between the first and fifth quarters of working with us, advertisers are spending 2.6 times what they spent in the first quarter. Some of that revenue came from some new things were were doing, including our work with Facebook and their FBX exchange, but for the most part, it was organic. Even without the Facebook campaign work, 90% of the revenue growth was from existing customers. RTM: So your product is so good it sells itself? But what did you do to improve your product in the past year that helped it sell itself? John: If you were to look at our core product, it was about a year ago that we pulled away the last bit of daily human oversight and attention that used ot be required. A little over a year ago, we would run a performance campaign by a target rate or a cost-per-action, and we would instruct our models to buy over a certain threshold of quality, and we would have to check in on it daily to see if we were meeting or exceeding that threshold. Well, it’s been a little more than about a ear since we got away from that too, and said, “Can’t we just have the computer do it?” What we discovered is, that when you map it into a machine environment, you’re no longer constrained by a human viewpoint, and you can get much more granular than a person can. Now it’s flying on autopilot and we get to relax and look out the window while the machines do all the work and the humans are focusing on superior analytics. RTM: Explain what you mean by “superior analytics.” What are people doing now that the machines are doing their own quality control on themselves? John: We think of those superior analytics as experiments -- people making adjustments and trying different scenarios until they prove themselves. And that's when we let it autopilot. There’s not a requirement for a human to be around in the beginning. All the machine needs to know is the budget, the goal and the performance target we need to hit. But the humans are sort of the upside, really. RTM: Do different humans, you know, clients, have different upsides? John: What we see, is direct response advertisers are pretty rationale. We we love the fact that they just look at their DART reports, or whatever reports they are using, and we’re the best ones delivering for them, so they just keep upping their their budgets every quarter. Brand advertisers are different. They may be doing a new product launch campaign with us, and that’s where we see brand advertisers come and go with their spend, depending on what they are focusing on at that time. Sometimes it is difficult for them to translate their brand objectives into specific thing that we can make happen online. There’s the rating point style campaign that can be measured online. Or there’s some kind of brand consideration metric that can be measured via surveys or engagement actions on their site. Once we have that, we just let the machines run. RTM: If the machines are so good, why don’t you just let your machies sell your product for you? John: I keep threatening to create a robot that will sell the pants off our sales team. But selling is still a very human process. When we launched in Europe in 2011, it took time to sell it, and it wasn’t really until 2012 that we got critical mass there. I’m an engineer, but I was also a sales rep, and I understand the value of both sides of the business. When I was an engineer, I didn’t think we should pay our sales people that much, because if the product is so good, it should sell itself. When I was in sales, I felt our product is so good, we just need more people to go out and sell it. RTM: With all your focus on machines, robots and AI, what’s the biggest challenge you have selling your product? John: Well, as I said, last year we removed the last requirement for any human intervention. AI was the most significant part of that, in my view. But we still need to humanize that for our customers. Otherwise, it’s just a black box. Some of them come back to us and say, “We’re happy with our performance, but we don’t really know how it’s doing it. So last year, in the first quarter, we created an early version of our Insights Booster, which basically creates a nice infographic on the campaign explaining the audience segments that are working well. It has a persona tool that helps describe what audience is working well by selecting images of different personas from a library of thousands of pictures coded by variables representing those personas. It’s a way of putting a face behind the performance aspects of the campaign. That’s one way we are humanizing what we do. When you’re dealing with AI and machine learning, it’s not always that obvious what is the best way to explain to customers what you are doing that is working well.
Online video ad buying platform TubeMogul this morning unveiled a deal with audience data management firm Lotame that will enable TubeMogul’s customers to utilize “pre-packaged audience segments” from Lotame to help them target online video audience buys.The deal will enable advertisers and agencies using TubeMogul to access up to 140 Lotame audience segments, along with the exact sites and geographic regions where an ad will run.Customers of Lotame’s Crowd Control DMP will also be able to share custom audience segments directly into their TubeMogul accounts so they can easily target these video audiences based on their own audience segments. “Brands are skeptical of audience data for legitimate reasons, but Lotame took the right approach building around lifting branding metrics,” TubeMogul CEO and Co-founder Brett Wilson states. “Marketers can test the results for themselves.”
Is real-time advertising finally coming to traditional TV?Sony Corp's Gracenote, the music and video recognition technology company, has struck a deal with Invidi, a major addressable advertising technology company, that "can identify what TV programs and commercials viewers are watching in real time and determine which commercials should play next."The companies say Gracenote's recognition technology, combined with Invidi's advertising system, can allow advertisers to select certain households and individual audience demographics and dynamically insert commercials to reach a specific audience.Bruce Anderson, chief technology officer of Invidi, stated: "We believe Gracenote's technology combined with Invidi is a big leap forward in inserting real linear content that is most relevant to the end view."Invidi has been involved in a bunch of addressable advertising tests with cable and satellite TV operators over the last several years. In 2010, Starcom MediaVest Group and Comcast Corp. worked on 60,000 home tests in Baltimore using Invidi technology. Invidi has also started up addressable ad efforts with DirecTV for local ad insertion, as well as Dish Network.Invidi has some major media agency backing, such as Group M.Separately, Gracenote also announced that it struck a deal with DG, an ad management and distribution platform, to create advertising efforts for smart TVs and second-screen devices, including TV ads that can be synchronized with phones and tablets through audio and video fingerprinting. "Watching TV photo from Shutterstock"
The real-time media-trading marketplace continues to expand, this time into the online and mobile streaming audio advertising sector, with a new exchange enabling programmatic buys of streaming audio audiences. The exchange, dubbed a2x, claims to the the first in the industry to enable advertisers to programmatically target online and mobile audio inventory in real-time.“Marketers are increasingly relying on ad exchanges and real-time bidding to reach their target audiences in an effective manner,” stated Mike Agovino, COO Triton Digital, which unveiled a2x this morning.The automated exchange utilizes data from eXelate to target ads at streaming audio audiences based on a variety of signals including purchase intent, demographics and other relevant behaviors.
eBay on Wednesday reported mobile transaction volume on its platform more than doubled in 2012 to $13 billion, while mobile payments handled by its PayPal unit tripled to $14 billion. The mobile gains helped the e-commerce giant increase revenue 18% in the fourth quarter to $4 billion. It posted earnings of $927 million, or 70 cents a share, beating analysts’ expectations by a penny. eBay has been one of the biggest players in mobile commerce in recent years as more of its users complete transactions through its mobile properties. "Mobile continues to rewrite the commerce playbook, and we continue to be a mobile commerce and payments leader," stated eBay president and CEO John Donahoe in its earnings release. He added that he expects mobile payments through PayPal to surpass $20 billion this year. eBay only keeps a fraction of the billions in mobile purchases and payments transacted on its platforms. eMarketer projects U.S. m-commerce sales, across smartphones, tablets and other mobile devices, will reach $38.4 billion this year. A Forrester forecast released today projects U.S. mobile payments--spanning in-store payments, remittances and m-commerce--will grow 48% annually from $18.2 billion in 2013 to $90 billion by 2017.
Many people have been harping on Facebook Graph Search since the announcement yesterday -- including some on these very virtual pages. But it seems to me that people aren’t stepping back to look at the big picture. Graph Search is, in a way, making the human network within Facebook tangible to users. Contrary to what MediaPost’s Joe Mandese wrote yesterday, regarding how this function is “adding more noise and distraction,” my feeling is that it will actually do the opposite. Graph Search empowers users to cut through the noise to find content that is actually interesting and useful to them. Graph Search is a way for people to capitalize upon the volumes of personal data readily available to them to make their life easier by strengthening the digital connection between friends. For example: You’re planning for a trip to Costa Rica and you’re looking for recommendations on where to go. Why post a status asking for recommendations to only get one or two comments from people who happen to see your post when you could just search “Friends who have pictures taken in Costa Rica” and browse through albums full of photos for ideas? In a similar sense, Graph Search enables people to grow their personal and professional network. Many Facebook users would agree with the fact that the majority of their “friends” on Facebook are people they haven’t talked to in years, or perhaps very little in the past at all. Graph Search branches that distance between friends, and pulls out common threads of interests, places, etc. Relocating to a new city and don’t know anyone there? Well, maybe you do. With Graph Search you could find long-lost friends or schoolmates who might be living or have lived in your new city. As for “the dark web” aspect of social searching, I’ll say again that this is Facebook shining a light through an otherwise black hole. What may currently be a mess of “inane” posts will be transformed into a treasure chest of information and content sharing. You won’t have to wade through your timeline to find specific information -- you’ll be able to search for it and look through content that is relevant to your needs. Lastly, I should add the fact that Facebook is smart. Very smart. They may not always do things people agree with right away (remember the commotion when Timeline rolled out to the public?), but every move they make is a step toward a better user experience. I believe Graph Search is just the beginning of search advancements we will begin to see across social media as a whole. It’s unknown now, but in a few years Graph Search will likely become another one of those “how did I live without this” tools.
The world of auction-based media is a fascinating space with rich detail into data and numbers. In fact, the details of the numbers and speed behind programmatic media buying are so rich that it’s easy to lose the sense of scale. By looking at real-time bidding (RTB) numbers from other perspectives, marketers will have a better idea of scale and the depth of ad technology we are dealing with in today’s marketplace. Let’s start by looking at AppNexus’ publicly stated 800K QPS. The definition of QPS is queries per second, which generally means the number of auctions that take place in one second. AppNexus sees 50 to 70 billion auctions per day. To put this in a simple perspective, this number (50 to 70 billion) is similar to the number of nerves in a single brain. We can also compare AppNexus to the stock market. AppNexus trades more in 41 minutes than Nasdaq (average is about two billion trades shares per day). Another scalable infrastructure to look at is Facebook. With 900 million users, the Facebook Exchange represents a huge opportunity for scale and reach within the auction marketplace. Simply put, if Facebook were a country, it would be the third-largest in the world -- just behind China with its population of 1.3 billion. In RTB, scale also means having the power to process data at rapid speed. From the time a request comes in, each bidder has 100 milliseconds to respond. In that time, a bidder has to locate the user the impression is for, determine the value of an impression by this user of one or more campaigns, and finally place the bid and record all the needed information. What this means is that each bidder request operates between three and four times faster than the blink of an eye, and about half as fast as the time it take for the human brain to recognize a face. Talk about speed! When you look at RTB numbers compared to tangible stats, you can begin to understand where we stand as an industry. Parks Associates recently reported that RTB technology will support roughly 50% of the display ad volume in North America in five years. In addition, by 2015, eMarketer predicts that RTB will account for 25% of display ad spending. The fact is that RTB's growth, scale and speed have accelerated rapidly, especially when you consider that it was introduced just after 2001.We have already come a long way, and this industry will only continue to become more scalable as better infrastructure is produced and key lessons from the world of programmatic media buying are refined.
Effective or not. Overhyped or not. Well executed, targeted, integrated…or not. The arguments over mobile ad effectiveness will no doubt be all the rage in 2013. But there is little doubt that money is flowing into the ecosystem along with some degree of optimism. According to the Q4 2012 report on activity across 30 billion ad impressions, in its app ad exchange of 12,000 apps on over 40 DSPs, MoPub reports that eCPMs for the quarter were up 50%. With a high of $1.12 for iOS and $.81 for Android in December, MoPub saw ads on Apple platforms rise 66% and on Android rise 54%. The good news for the industry and for publishers is that the spike appears to be holding, with a relatively small dropoff of eCPMs after the holiday. iOS peaked at $1.25 in the last two weeks of December, but drew back only to $1.07 in the first week of January. Click-through rates actually went up after the holiday. The iPad continues to be the gift that keeps giving, with eCPMs reaching $1.40 in December, up 49% in the quarter. Android tablets also rose, but from a much lower starting point to $.99 (up 69%). iPads are in highest demand among all devices, attracting more bids per impression on average (5.3) than iPhone (5.0), Android (4.6) and Android tablets (4.2). the iPad is proving out the premium pricing with far and away the highest average click-through rates of any platform (2.2% in the first week of January) compared to 1.5% for iPhone, 1.1% for Android, and .9% for Android tablets. Social networking was the category most in demand among advertisers, with 6.9 bids per auction on average, compared to 5.6 for sports and games. The push for rich media this past year has had mixed results, according to this sample at least. While MRAID units (the IAB-defined standard) showed a considerable spike in eCPMs in December for a 1.6x premium over non-MRAID ads ($1.16 vs. $.83) the click-throughs on the ads were only 1.3% or 1.2x the 1.1% of nonMRAID ads. One might argue that the richer media tended toward brand messaging that did not include calls to action and so weren’t prompting the clicks in the first place. But MoPub’s finding suggest that we need to look more closely at the formats and how consumers are responding to them. While the trajectory is favorable in this report, the role of RTB and data driven exchanges in the mobile space remains unclear. Dollar CPMs may seem rosy compared to earlier metrics, but it is difficult to see how this pricing supports a robust publishing ecosystem, especially for major media providers. But as Magna’s Brian Monahan points out in his recent forecast of programmatic trading on mobile systems (an annual growth rate of 25% versus 30.6% for all of mobile), there are considerable hurdles to bigger investment. Targeting on mobile remains problematic for a number of factors. Tracking cannot take place easily between mobile browser and app, even when cookies are present, and most often they are not. And in the multi-screen habits of contemporary users tracking those users across PC and device is going to be critical. But Monahan raised one point that really did stand out for me -- brand safety. He writes in the report: “In exchange buying, a critical safeguard for brand appropriate environments is provided by ad safety vendors. In the Web they rely on web crawlers and macros delivered with their tags by the ad server to extract information on the content and the ad placement. These techniques are not yet sufficiently robust to extract the required brand safety information from mobile apps.” Media buyer reticence continues. One trend this report does underscore is advertiser embrace of the tablet, however. Driven both by its creative palette and its propensity to covert, these larger screens are going to be the ad agency darlings this year. Deloitte predicts that this will be the last year the industry combines tablet ad spend and smartphone ad spend into a single and increasingly confusing “mobile” category. I agree. They are two very different platforms. But even in ad serving and creative, the confusion is evident to the user. I still get smartphone-scaled banners on my iPad as well as mobile ads that have been ‘optimized’ for the larger screen simply by blowing up low-res creative to fuzzy and ugly proportions. Landing pages can’t decide whether to treat me as a phone or a tablet -- so that in many cases, especially with network and exchange inventory, the seams are evident. The advertising experience across both smartphone and tablets continues to feel like a patchwork and barely intelligent system that struggles to fit your device. How is it supposed to know your purchase intent?