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Current Reading in Data Mining

Wednesday, March 10th, 2010 by Sandro Saitta

I’m currently reading two interesting books about analytics and data mining. I will review these two books in the near future. Meanwhile, here is a few information about these books:

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Liking: The Penultimate Question

Tuesday, March 9th, 2010 by JeffreyHenning

In the paper “Measuring Customer Satisfaction and Loyalty: Improving the ‘Net-Promoter’ Score” (Schneider, Berent, Thomas, Krosnick, 2008), the authors skillfully deconstruct and invalidate The Ultimate Question (see NPS Criticisms & Best Practices). They conclude:

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Together we build the future of our industry! Watch the movies & discuss…

Monday, March 8th, 2010 by Tom De Ruyck

On the most recent BAQMaR Conference, I launched the ’10 challenges’ that our industry will need to overcome in the coming years. That day, interviews with the speakers of the Conference and some of the attendees were conducted. These videos provide us with first answers to the questions asked. But we want to go further, we want to include all of you into this discussion about the future of our profession. Take a look at the videos and join the discussion on our LinkedIn Group!

The discussions will serve as input for in-depth interviews with industry leaders and a survey among marketing researchers around the globe.

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Funny Fridays: GroupThink – Episode 2

Friday, March 5th, 2010 by Tom De Ruyck

Firm It Up


I’m sorry but representative samples are 100% unattainable

Thursday, March 4th, 2010 by Annie Pettit

Statistics are just numbers. 1 + 2 is always 3 even if the 2 was written in a disgusting colour. People, on the other hand, have crappy days all the time. It could be because a lunch was packed without cookies or because horrible tragedy has struck.

So why does it matter? Because crappy days mean someone:

  • doesn’t answer a phone survey
  • lies on their taxes
  • makes a mistake on the census survey
  • accidentally skips page 2 on a paper survey
  • drips sarcasm all over their facebook page

You recognize these. We call them data quality issues.

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