Occam's Razor

SEPTEMBER 15, 2011

There is one difference between winners and losers when it comes to web analytics. Winners, well before they think data or tool, have a well structured Digital Marketing & Measurement Model. Losers don't. This article guides you in understanding the value of the Digital Marketing & Measurement Model (notice the repeated emphasis on Marketing, not just Measurement), and how to create one for yourself.

Measurement 166

Measurement Marketing Modeling Key Performance Indicator 166

Edwin Chen

SEPTEMBER 6, 2011

tl;dr See this movie visualization for a case study on how a post propagates through Quora. How does information spread through a network? Much of Quora’s appeal, after all, lies in its social graph – and when you’ve got a network of users, all broadcasting their activities to their neighbors, information can cascade in multiple ways.

Machine Learning 52

Machine Learning Broadcasting Visualization Data mining 52

Nutanix

SEPTEMBER 13, 2011

Back from our first vmworld on the heels of our launch on 8/16, here are some lessons we learned and a highlights video of our experience.

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Occam's Razor

SEPTEMBER 19, 2011

With a plethora of digital media channels at our disposal and new ones on the way every day(!), how do you prioritize your efforts? How do you figure out which channels to invest in more and which to kill? How do you figure out if you are spending more money reaching the exact same current or prospective customers multiple times? How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple medi

Measurement 120

Measurement Advertising Testing Marketing 120

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Optimization

Edwin Chen

SEPTEMBER 29, 2011

What types of students go to which schools? There are, of course, the classic stereotypes: MIT has the hacker engineers. Stanford has the laid-back, social folks. Harvard has the prestigious leaders of the world. Berkeley has the activist hippies. Caltech has the hardcore science nerds. But how well do these perceptions match reality? What are students at Stanford, Harvard, MIT, Caltech, and Berkeley really interested in?

Finance 81

Finance Interactive Machine Learning Advertising 81