Supercrunchers
Chapter 1 Who’s doing your thinking for you?
Questions

1. Identify from Chapter 1 a quantitative application discussed by the author that you were already familiar with.
• Brigs Myers
• eHarmony, I was already familiar with eHarmony utilizing a statistical regression in order to match people “accurately”. I found the discussion about same sex couples not being matched on eHarmony interesting, and am excited that this chapter disucsses how regressions about preference, behavior, affect/ improve predictions as is that information that is most valuable to marketers.
• Job applicants
• Contintental Airlines
• UPS
• Harrah’s and the “pain point”- Didn’t know about this, the data on the card was genius and understanding again behaviors and reactions of consumers is very valuable, I really enjoyed this example.
• Hertz and gas left in tank
• Cingular and anytime minutes
• Best Buy and extended warranty claims
• Farecast--Prediction of airfares
• Google personalized search
• Page rank – I already knew about this one as well and found it really interesting, because recently there has been chatter of an “algorithim” update where pages actually have lost rank or been increased—previously google had a penguin update, and now potentially panda.
2. Which quantitative application discussed by the author surprised you?
UPS’s application of the algorithm to predict when a customer is likely to switch to another shipping company surprised me. I never thought or realized how algorithms use the “matchmaking” technique not to just give consumer personalized messages and better reach them, in the acquisition phase, but more importantly help in the retention phase. I didn’t think about the application to loyalty, and for us as marketers’ solves/ is key and useful to keep a consumer from switching and strengthening retention and brand loyalty.