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<title>Lies, Damned Lies...</title>
<link>http://www.liesdamnedlies.com/</link>
<description>The unpredictable world of online marketing &amp; web analytics</description>
<language>en-US</language>
<lastBuildDate>Tue, 01 May 2012 13:44:33 -0700</lastBuildDate>
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<title>Google launches cloud-based BigQuery service</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/vLC4BkeUYBY/google-launches-cloud-based-bigquery-service.html</link>
<guid isPermaLink="false">http://www.liesdamnedlies.com/2012/05/google-launches-cloud-based-bigquery-service.html</guid>

<content:encoded><![CDATA[Some interesting news today: Google has fully launched the cloud-based BigQuery service that it first previewed last November. From the website: Google BigQuery is a web service that lets you do interactive analysis of massive datasets—up to billions of rows. Scalable and easy to use, BigQuery lets developers and businesses tap into powerful data analytics on demand. The BigQuery service is built on the back of Google’s enormous investments in data infrastructure and exposes some of the clever tools the company has built for internal use to an internal audience. It’s designed to help with ad hoc queries against unstructured data – kind of Hadoop in the cloud with a front-end querying service attached. In this regard it shares some similarities with the Hadoop on Azure service from my illustrious employers. The interesting question with all these cloud-based Big Data services (a list of some of which you can find here, and here) is the acceptability to customers of loading significant amounts of data to the cloud, and dealing with the privacy and security questions that arise as a result. But it is interesting to contrast the significant complexity that attends any conversation about in-house or on-premise big data with...<br/>
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<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Tue, 01 May 2012 13:44:33 -0700</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2012/05/google-launches-cloud-based-bigquery-service.html</feedburner:origLink></item>
<item>
<title>Returning to the fold</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/NaMtvJy9NjU/returning-to-the-fold.html</link>
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<content:encoded><![CDATA[Five years ago, my worldly possessions gathered together in a knotted handkerchief on the end of a stick, I set off from the shire of Web Analytics to seek my fortune among the bright lights of online advertising. I didn’t exactly become Lord Mayor of London, but the move has been a good one for me, especially in the last three years, when I’ve been learning all sorts of interesting things about how to measure and analyze the monetization of Microsoft’s online properties like MSN and Bing through advertising. Now, however, the great wheel of fate turns again, and I find myself returning to the web analytics fold, with a new role within Microsoft’s Online Services Division focusing on consumer behavior analytics for Bing and MSN (we tend to call this work “Business and Customer Intelligence”, or BICI for short). Coincidentally I was able to mark this move this week with my first visit to an eMetrics conference in almost three years. I was at eMetrics to present a kind of potted summary of some of what I’ve learned in the last three years about the challenges of providing data and analysis around display ad monetization. To my regular blog...<br/>
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<category>Industry</category>
<category>Web analytics</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Thu, 08 Mar 2012 15:57:59 -0800</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2012/03/returning-to-the-fold.html</feedburner:origLink></item>
<item>
<title>Big (Hairy) Data</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/tcPyCQwe9Jg/big-hairy-data.html</link>
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<content:encoded><![CDATA[My eye was caught the other day by a question posed to the “Big Data, Low Latency” group on LinkedIn. The question was as follows: “I've customer looking for low latency data injection to hadoop . Customer wants to inject 1million records per/sec. Can someone guide me which tools or technology can be used for this kind of data injection to hadoop.” The question itself is interesting, given its assumption that Hadoop is part of the answer – Hadoop really is the new black in data storage & management these days – but the answers were even more interesting. Among the eleven or so people who responded to the question, there was almost no consensus. No single product (or even shortlist of products) emerged, but more importantly, the actual interpretation of the question (or what the question was getting at) differed widely, spinning off a moderately impassioned debate about the true meaning of “latency”, the merits of solid-state storage vs HD storage, and whether to clean/dedupe the data at load-time,or once the data is in Hadoop. I wouldn’t class myself as a Hadoop expert (I’m more of a Cosmos guy), much less a data storage architect, so I may be...<br/>
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<category>Big Data</category>
<category>Industry</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Tue, 07 Feb 2012 23:08:30 -0800</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2012/02/big-hairy-data.html</feedburner:origLink></item>
<item>
<title>Building the Perfect Display Ad Performance Dashboard, Part II &amp;ndash; metrics</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/Wjwd2RJKj-Q/building-the-perfect-display-ad-performance-dashboard-part-ii-metrics.html</link>
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<content:encoded><![CDATA[Welcome to the second installment in my Building the Perfect Display Ad Performance Dashboard series (Note to self: pick a shorter title for the next series). In the first installment, we looked at an overarching framework for thinking about ad monetization performance, comprised of a set of key measures and dimensions. In this post, we’ll drill into the first of these – the measures that you need to be looking at to understand your business. How much, for how much? As we discussed in the previous post, analysis of an online ad business needs to focus on the following: How much inventory was available to sell (the Supply) How much inventory was actually sold (the Volume Sold) How much the inventory was actually sold for (the Rate) Of these, it’s the last two – the volume sold and the rate at which that volume was sold – where the buck (literally) really stops, since these two combine to deliver that magic substance, Revenue. So in this post we’ll focus on volume sold, rate and revenue as the core building-blocks of your dashboard’s metrics. Volume, rate and revenue are inextricably linked via a fairly basic mathematical relationship: Revenue = Rate x...<br/>
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<category>Adserving</category>
<category>Building the perfect Display Ad Performance Dashboard</category>
<category>Dashboards</category>
<category>Display Advertising</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Mon, 19 Dec 2011 17:25:57 -0800</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2011/12/building-the-perfect-display-ad-performance-dashboard-part-ii-metrics.html</feedburner:origLink></item>
<item>
<title>Should Wikipedia accept advertising?</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/1y75mXkMhEw/should-wikipedia-accept-advertising.html</link>
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<content:encoded><![CDATA[It’s that time of year again. The nights are drawing in, snow is starting to fall in the mountains, our minds turn to thoughts of turkey and Christmas pudding, and familiar faces appear: Santa, Len and Bruno, and of course, Jimmy Wales. If you are a user of Wikipedia (which, if you’re a user of the Internet, you almost certainly are), you’ll likely be familiar with Jimmy Wales, the founder of Wikipedia and head of the Wikimedia Foundation, the non-profit which runs the site. Each year Jimmy personally fronts a campaign to raise funds to cover the cost of running Wikipedia, which this year will amount to around $29m. The most visible part of this campaign is the giant banner featuring Jimmy Wales’s face which appears at the top of every Wikipedia article at this time of year. This year the banner has caused some hilarity as the position of the picture of Jimmy just above the article title has provided endless comic potential (as above), but every year it becomes increasingly wearisome to have Jimmy’s mug staring out at you for around three months. Would it not be easier for all concerned if Wikipedia just carried some advertising? Jimmy...<br/>
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<category>Branding &amp; Advertising</category>
<category>Display Advertising</category>
<category>Industry</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Mon, 21 Nov 2011 12:55:36 -0800</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2011/11/should-wikipedia-accept-advertising.html</feedburner:origLink></item>
<item>
<title>Building the Perfect Display Ad Performance Dashboard, Part I &amp;ndash; creating a measurement framework</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/oX5YzCVUh-w/building-the-perfect-display-ad-performance-dashboard-part-imetrics.html</link>
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<content:encoded><![CDATA[There is no shortage of pontification available about how to measure your online marketing campaigns: how to integrate social media measurement, landing page optimization, ensuring your site has the right feng shui to deliver optimal conversions, etc. But there is very little writing about the other side of the coin: if you’re the one selling the advertising, on your site, or blog, or whatever, how do you understand and then maximize the revenue that your site earns? As I’ve covered previously in my Online Advertising 101 series, publishers have a number of tools and techniques available to manage the price that their online ad inventory is sold for. But the use of those tools is guided by data and metrics. And it’s the generation and analysis of this data that is the focus of this series of posts. In this series, I’ll unpack the key data components that you will need to pull together to create a dashboard that will give you meaningful, actionable information about how your site is generating money – or monetizing, to use the jargon. We’ll start by taking a high-level look at a framework for analyzing a site’s (or network’s) monetization performance. In subsequent posts,...<br/>
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<category>Building the perfect Display Ad Performance Dashboard</category>
<category>Business Intelligence</category>
<category>Display Advertising</category>
<category>Online marketing</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Wed, 09 Nov 2011 05:44:00 -0800</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2011/11/building-the-perfect-display-ad-performance-dashboard-part-imetrics.html</feedburner:origLink></item>
<item>
<title>Wading into the Google Secure Search fray</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/HSXAYU7Dl-s/wading-into-the-google-secure-search-fray.html</link>
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<content:encoded><![CDATA[There’s been quite the hullabaloo since Google announced last week that it was going to send signed-in users to Google Secure Search by default. Back when Google first announced Secure Search in May, there was some commentary about how it would reduce the amount of data available to web analytics tools. This is because browsers do not make page referrer information available in the HTTP header or in the page Document Object Model (accessible via JavaScript) when a user clicks a link from an SSL-secured page through to a non-secure page. This in turn means that a web analytics tool pointed at the destination site is unable to see the referring URLs for any SSL-secured pages that visitors arrived from. This is all desired behavior, of course, because if you’ve been doing something super-secret on a secure website, you don’t want to suddenly pass info about what you’ve been doing to any old non-secure site when you click an off-site link (though shame on the web developer who places sensitive information in the URL of a site, even if the URL is encrypted). At the time, the web analytics industry’s concerns were mitigated by the expectation that relatively few users...<br/>
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<category>Google</category>
<category>Search</category>
<category>Web analytics</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Mon, 24 Oct 2011 14:49:46 -0700</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2011/10/wading-into-the-google-secure-search-fray.html</feedburner:origLink></item>
<item>
<title>Nicely executed retargeting opt-out (for a change)</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/F2GEMWrEzPM/nicely-executed-retargeting-opt-out-for-a-change.html</link>
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<content:encoded><![CDATA[Retargeting (sometimes called remessaging or remarketing) has taken off in a big way, recently – Google introduced the feature into AdWords earlier this year, and a host of other players are in the game. Consequently, the interwebs now abound with commentary on the rather spooky nature of the technology, with people being “followed around” the Internet by ads for things they were either searching for, or were looking at on e-commerce websites. It is true that most retargeting implementations are a bit clunky, and I have been on the receiving end of plenty of them myself. Their most irritating aspect seems to be that the time window for perceived relevance of the retargeted ads seem to be ridiculously long. It’s somehow almost more irritating to be deluged by ads for that miscellaneous widget site that you once visited a few weeks ago (even though you have since satisfied your need for widgets elsewhere) than it is to be served non-targeted (or more broadly targeted) ads. Such ads are made more bearable by a robust opt-out capability; many ad networks have adopted the IAB’s self-regulatory program, which calls for the advertiser to make it possible to opt out of these kinds...<br/>
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<category>Online marketing</category>
<category>Targeting</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Mon, 17 Oct 2011 17:34:31 -0700</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2011/10/nicely-executed-retargeting-opt-out-for-a-change.html</feedburner:origLink></item>
<item>
<title>Online Advertising Business 101, Part VII: Demand-side Platforms (DSPs)</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/-74e-26qM2U/online-advertising-business-101-part-vii-demand-side-platforms-dsps.html</link>
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<content:encoded><![CDATA[It turns out, alarmingly, that it’s been over a year since my last Online Advertising Business 101 post. And a year is an awfully long time in the world of online advertising. Long enough, in fact, for an entirely new kind of company to emerge and become the next big thing. I’m talking, of course, about Demand-side Platforms. You’ve heard of them, I trust? No? Then read on. DSPs, RTBs, oh my As it should happen, my last post in this series was on the subject of Ad Exchanges – a new kind of participant in the advertising value chain that acts as an intermediary between ad networks, allowing them to exchange inventory to make up for shortfalls in supply and demand among their own publishers and advertisers, and also allowing other scale players (e.g. big advertisers like eBay, or a big agency) to buy inventory dynamically across a number of different networks. All those folks had to do was implement some technology to interact with the exchange, and place bids in real-time (on of the key characteristics of an ad exchange being that it can auction inventory in real-time). It turns out that that last glib sentence conceals an...<br/>
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<category>Ad industry 101</category>

<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Mon, 07 Jun 2010 09:17:47 -0700</pubDate>

<feedburner:origLink>http://www.liesdamnedlies.com/2010/06/online-advertising-business-101-part-vii-demand-side-platforms-dsps.html</feedburner:origLink></item>
<item>
<title>Wanna work for me?</title>
<link>http://feedproxy.google.com/~r/LiesDamnedLies/~3/EBp5T5Eak68/wanna-work-for-me.html</link>
<guid isPermaLink="false">http://www.liesdamnedlies.com/2010/03/wanna-work-for-me.html</guid>

<content:encoded><![CDATA[Have a passion for data? Think yourself something of a BI/analytics guru? Does your heart sing whenever you see a well-turned chart (and your toes curl whenever you see something like this)? Looking for a new gig worthy of your exceptional talents? If so, then I might just have the perfect opportunity for you. I’m looking for someone to head up the planning & product management for a big chunk of the internal BI & reporting systems that I manage here at Microsoft – systems which help hundreds of people cross Microsoft’s Online Services Division to make smart decisions about how to run our gigantic display advertising network.Only downside of the role is that you have to work for me. I’m looking for someone who loves the numbers and has the flair, creativity and communications skills to make other people love them too, who’s comfortable working the politics of a big ol’ behemoth like Microsoft, but who likes to move quickly and, as I like to put it, “get sh*t done”. In this role, you’ll wrangle gigantic, disparate data sets and juggle the competing demands of field sales, Finance and monetization specialists as you toil to deliver the definitive view...<br/>
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<dc:creator>ian_d_thomas</dc:creator>
<pubDate>Mon, 15 Mar 2010 18:43:46 -0700</pubDate>

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