scale

the American phone subsidy model is a RAZR way of thinking in an iPhone world

Source: http://www.engadget.com/2010/02/23/editorial-the-american-phone-subsidy-model-is-a-razr-way-of-thi/

The concept is simple enough — pay more, get more. So it has gone (historically, anyway) with phone subsidies in this part of the world, a system that has served us admirably for well over a decade. It made sense, and although it was never spelled out at the customer service counter quite as clearly as any of us would’ve liked, it was fairly straightforward to understand: you bought a phone on a multi-dimensional sliding scale of attractiveness, functionality, and novelty. By and large, there was a pricing scale that matched up with it one-to-one. You understood that if you wanted a color external display, a megapixel camera, or MP3 playback, you’d pay a few more dollars, and you also understood that you could knock a couple hundred dollars off of that number by signing up to a two-year contract. In exchange for a guaranteed revenue stream, your carrier’s willing to throw you a few bucks off a handset — a square deal, all things considered. So why’s the FCC in a tizzy, and how can we make it better?

Continue reading Editorial: the American phone subsidy model is a RAZR way of thinking in an iPhone world

Editorial: the American phone subsidy model is a RAZR way of thinking in an iPhone world originally appeared on Engadget on Tue, 23 Feb 2010 20:00:00 EST. Please see our terms for use of feeds.

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Wednesday, February 24th, 2010 Uncategorized No Comments

Inside Google’s Secret Search Algorithm

Source: http://feeds.gawker.com/~r/gizmodo/full/~3/zzkIcilnJp4/inside-googles-secret-search-algorithm

Wired’s Steven Levy takes us inside the “algorithm that rules the web“—Google’s search algorithm, of course—and if you use Google, it’s kind of a must-read. PageRank? That’s so 1997.

It’s known that Google constantly updates the algorithm, with 550 improvements this year—to deliver smarter results and weed out the crap—but there are a few major updates in its history that have significantly altered Google’s search, distilled in a helpful chart in the Wired piece. For instance, in 2001, they completely rewrote the algorithm; in 2003, they added local connectivity analysis; in 2005, results got personal; and most recently, they’ve added in real-time search for Twitter and blog posts.

The sum of everything Google’s worked on—the quest to understand what you mean, not what you say—can be boiled down to this:

This is the hard-won realization from inside the Google search engine, culled from the data generated by billions of searches: a rock is a rock. It’s also a stone, and it could be a boulder. Spell it “rokc” and it’s still a rock. But put “little” in front of it and it’s the capital of Arkansas. Which is not an ark. Unless Noah is around. “The holy grail of search is to understand what the user wants,” Singhal says. “Then you are not matching words; you are actually trying to match meaning.”

Oh, and by the way, you’re a guinea pig every time you search for something, if you hadn’t guessed as much already. Google engineer Patrick Riley tells Levy, “On most Google queries, you’re actually in multiple control or experimental groups simultaneously.” It lets them constantly experiment on a smaller scale—even if they’re only conducting a particular experiment on .001 percent of queries, that’s a lot of data.

Be sure to check out the whole piece, it’s ridiculously fascinating, and borders on self-knowledge, given how much we all use Google (sorry, Bing). [Wired, Sweet graphic by Wired's Mauricio Alejo]

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Tuesday, February 23rd, 2010 Uncategorized No Comments

Aardvark Publishes A Research Paper Offering Unprecedented Insights Into Social Search

Source: http://feedproxy.google.com/~r/Techcrunch/~3/IMDRrISRf-8/

In 1998, Larry Page and Sergey Brin published a paper[PDF] titled Anatomy of a Large-Scale Hypertextual Search Engine, in which they outlined the core technology behind Google and the theory behind PageRank. Now, twelve years after that paper was published, the team behind social search engine Aardvark has drafted its own research paper that looks at the social side of search. Dubbed Anatomy of a Large-Scale Social Search Engine, the paper has just been accepted to WWW2010, the same conference where the classic Google paper was published.

Aardvark will be posting the paper in its entirety on its official blog at 9 AM PST, and they gave us the chance to take a sneak peek at it. It’s an interesting read to say the least, outlining some of the fundamental principles that could turn Aardvark and other social search engines into powerful complements to Google and its ilk. The paper likens Aardvark to a ‘Village’ search model, where answers come from the people in your social network; Google is part of ‘Library’ search, where the answers lie in already-written texts. The paper is well worth reading in its entirety (and most of it is pretty accessible), but here are some key points:

  • On traditional search engines like Google, the ‘long-tail’ of information can be acquired with the use of very thorough crawlers. With Aardvark, a breadth of knowledge is totally reliant on how many knowledgeable users are on the service. This leads Aardvark to conclude that “the strategy for increasing the knowledge base of Aardvark crucially involves creating a good experience for users so that they remain active and are inclined to invite their friends”. This will likely be one of Aardvark’s greatest challenges.
  • Beyond asking you about the topics you’re most familiar with, Aardvark will actually look at your past blog posts, existing online profiles, and tweets to identify what topics you know about.
  • If you seem to know about a topic and your friends do too, the system assumes you’re more knowledgeable than if you were the only one in a group of friends to know about that topic.
  • Aardvark concludes that while the amount of trust users place in information on engines like Google is related to a source website’s authority, the amount they trust a source on Aardvark is based on intimacy, and how they’re connected to the person giving them information
  • Some parts of the search process are actually easier for Aardvark’s technology than they are for traditional search engines. On Google, when you type in a query, the engine has to pair you up with exact websites that hold the answer to your query. On Aardvark, it only has to pair you with a person who knows about the topic — it doesn’t have to worry about actually finding the answer, and can be more flexible with how the query is worded.
  • As of October 2009, Aardvark had 90,361 users, of whom 55.9% had created content (asked or answered a question). The site’s average query volume was 3,167.2 questions per day, with the median active user asking 3.1 questions per month. Interestingly, mobile users are more active than desktop users. The Aardvark team attributes this to users wanting quick, short answers on their phones without having to dig for anything. They also think people are more used to using more natural language patterns on their phones.
  • The average query length was 18.6 words (median of 13) versus 2.2-2.9 words on a standard search engine.  Some of this difference comes from the more natural language people use (with words like “a”, “the”, and “if”).  It’s also because people tend to add more context to their queries, with the knowledge that it will be read by a human and will likely lead to a better answer.
  • 98.1% of questions asked on Aardvark were unique, compared with between 57 and 63% on traditional search engines.
  • 87.7% of questions submitted were answered, and nearly 60% of them were answered within 10 minutes.  The median answering time was 6 minutes and 37 seconds, with the average question receiving two answers.  70.4% of answers were deemed to be ‘good’, with 14.1% as ‘OK’ and 15.5% were rated as bad.
  • 86.7% of Aardvark users had been asked by Aardvark to answer a question, of whom 70% actually looked at the question and 38% could answer.  50% of all members had answered a question (including 75% of all users who had ever actually interacted with the site), though 20% of users accounted for 85% of answers.
Information provided by CrunchBase


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Tuesday, February 2nd, 2010 Uncategorized No Comments

Net Promoter Score (NPS) – A Metrics “Sacred Cow” That Should be Slaughtered?

My main issues with the Net Promoter Score (NPS) is that it doesn’t tell me anything new, is based on flawed math, the number cannot stand alone, and is not actionable (does not tell marketers what to go do).

Read More about Net Promoter Score Challenges

Thanks for all the retweets!

ZebraBites@adamferrier Another one for the NPS collection; http://www.clickz.com/3635696 (via @jhenning and @acfou)

acfouIt’s an “it is what it is” metric (which isn’t actionable) – #netpromoterscore #netpromoter #NPS - http://bit.ly/6EYyc

spiralsThought provoking Net Promoter article http://www.clickz.com/3635696 -Good idea to use search as an indicator of customer satisfaction

VirtualMRRT @berniemalinoff: RT @JHenning @acfou: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3

seangibRT @glenngabe: What’s Wrong With the Net Promoter Score http://bit.ly/84Jh2P via @acfou on ClickZ – some interesting comments as usual w …

glenngabeWhat’s Wrong With the Net Promoter Score http://bit.ly/84Jh2P via @acfou on ClickZ – some interesting comments as usual w/Dr. Fou. :)

MetriclyWhat’s Wrong With the Net Promoter Score - http://bit.ly/8U3VVD

christinet6dOh snap… RT @lizapost What’s the value of the Net Promoter score? According to @acfou, not much. ‘http://bit.ly/6EYyc

lizapostWhat’s the value of the Net Promoter score? According to @acfou, not much. ‘What’s Wrong With the Net Promoter Score’http://bit.ly/6EYyc

berniemalinoffRT @JHenning @acfou: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3 || healthy debate pros/cons of #NPS

contactjrFrom @acfou: What’s wrong with the Net Promoter Score? http://bit.ly/17ahJC

Noakesi@holycow RT @jonnylongden: RT @rj_berg: Great article on some of the problems with Net Promoter Score (NPS) http://bit.ly/2h5jot#measure

acfouNet Promoter Score (NPS) like brand sentiment scores are oversimplified averages that are not actionable - http://bit.ly/6EYyc

ju2ltdRT @jonnylongden: RT @rj_berg: Great article on some of the problems with Net Promoter Score (NPS) http://bit.ly/2h5jot #measure

jonnylongdenRT @rj_berg: Great article on some of the problems with Net Promoter Score (NPS) http://bit.ly/2h5jot #measure #retail – why use this?

Adtraction_RAJ_What’s Wrong With the Net Promoter Score http://bit.ly/17ahJC (mmm)

KarmaMediaLabs#NetPromoterScore not all it’s cracked up to be? Decide for yourself: http://bit.ly/17ahJC

EricheadRT @rj_berg: Great article on some of the problems with Net Promoter Score (NPS) http://bit.ly/2h5jot #measure #retail – why use this?

PeteHealyNet Promoter Score = useless; replace w/ search volume. Augustine Fou @acfou http://www.clickz.com/3635696 Your thoughts? #in

helena_chariRT @mrnews: #NPS ‘tells you the obvious, isn’t predictive, doesn’t answer the “So what?” question.’ http://bit.ly/1DqmgD (via @DavidPenn

makingcjcAn it is what it is” metric…debate on the Net Promoter score. http://www.clickz.com/3635696

DannyGavinRT @EstherSteinfeld Interesting read: “What’s Wrong with the Net Promoter Score?” @acfou says, “So many things.”http://bit.ly/1ojkfk

ZaliciousRT @kevinertell: This is an excellent article on ClickZ: What’s Wrong With the Net Promoter Score http://www.clickz.com/3635696

hellosmalldogArticle about NPS is interesting – thanks to @mjayliebs for CCing us! We’re reading it now. (via @acfou, @wimrampen)http://tr.im/Fgv3

bigmacherRT @kevinertell: This is an excellent article on ClickZ: What’s Wrong With the Net Promoter Score http://www.clickz.com/3635696

DavashRT @rj_berg: Gr8 article: problems w/Net Promoter Score (#NPS) (http://bit.ly/2h5jot ) #measure [A grad of stats 101 could see all of this]

BobbleHeadGuruRT @rj_berg: Gr8 article: problems w/Net Promoter Score (#NPS) (http://bit.ly/2h5jot ) #measure [A grad of stats 101 could see all of this]

EstherSteinfeldInteresting read: “What’s Wrong with the Net Promoter Score?” @acfou says, “So many things.” http://bit.ly/1ojkfk

kevinertellThis is an excellent article on ClickZ: What’s Wrong With the Net Promoter Score http://www.clickz.com/3635696

rj_bergGreat article on some of the problems with Net Promoter Score (NPS) http://bit.ly/2h5jot #measure #retail

mjayliebsRT @wimrampen: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3 (cc @hellosmalldog)

jestodcWhat’s Wrong With the Net Promoter Score http://www.clickz.com/3635696

jonathanmendez“NPS is what I call an “it is what it is” metric — it tells you the obvious” http://bit.ly/6EYyc

mrnews#NPS ‘tells you the obvious, isn’t predictive, doesn’t answer the “So what?” question.’ http://bit.ly/1DqmgD (via @DavidPenn1@jhenning)

DavidPenn1RT @jhenning RT @acfou: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3 Maybe we need to take it less literally?

wimrampenRT @JHenning: RT @acfou: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3

NicoPeruzziPhDRT @JHenning: RT @acfou: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3 – the emperor has no clothes…

JHenningRT @acfou: Net Promoter Score (NPS) is synonymous with “useless” http://tr.im/Fgv3 Builds on my criticisms with some of his own.

acfouNet Promoter Score (NPS) is synonymous with “useless” (is based on bad math, is not actionable) – what say you? http://bit.ly/6EYyc

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Friday, November 20th, 2009 Uncategorized No Comments

Map of IP addresses around the world used to commit Click-Fraud

Source: http://feeds.gawker.com/~r/gizmodo/full/~3/QE1Gthuy4_k/3-million-in-click-fraud-over-two-weeks-just-the-beginning

A recently disbanded click fraud ring in China racked up $3 million worth of clicks in two weeks. $3 million that we’re aware of. Just how detectable is this whole business of racking up fraudulent ad revenue clicks?

That intricate mess of lines above represents a portion of DormRing1, the click fraud bunch that was caught in China. The lines show the relationship of some of the IP addresses involved in the fraud and how they are connected to some fraudulent ad clicks. The whole network actually “involved 200,000 different IP addresses and racked up more than $3 million worth of fraudulent clicks across 2,000 advertisers in a two-week period.” Impressive and scary at the same time.

The trouble is that no one really knows how much ad revenue DormRing1 collected before they were caught. Click-fraud monitoring services such as Anchor Intelligence, the ones behind this catch, are evolving to keep up with the scale on which these rings are operating. It’s still difficult to judge just how well they’re doing as they’re having to infiltrate forums and gain the trust of the perpetrators in a manner reminiscent of drug busts. But as the criminals are getting more elaborate, the investigations are too.

That good news aside, do me a favor: after you read this post, comment, and all that jazz, refresh the page a few times and—Ah…I mean, heh…just kidding. [Tech Crunch]


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Friday, October 9th, 2009 Uncategorized No Comments