Occam's Razor

JULY 6, 2016

Analysts, honestly, make the world go round when it comes to any successful business – yes, data is that important. As you might expect from any role, they also make a handful of important mistakes. I've written about the biggest mistake web analysts make. Today's post is an adjacent mistake: The cardinal sin of spending too much time with data and in reports!

Testing 86

Testing Marketing Experimentation Cost-Benefit 86

Rita Sallam

JULY 22, 2016

There are pivot moments in life and in business where you just know – everything is about to change. Remember the first time you used the internet, email, a Mac, an ipod, iphone or ipad, or wore Reeboks? OK, I’m dating myself, but before Reeboks, we actually did what we is now call aerobics or cardio classes in bare feet on wood dance floors in ballet studios with leg warmers!

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Jenny Sussin

JULY 12, 2016

I’m smack dab in the middle of Pokemon Go ‘s target demographic. I’ve seen some funny memes online where a big scary van has graffiti’ed “Rare Pokemon Inside” on it with the caption, “How to kidnap a 28 year old in 2016,” and I can tell you, that is accurate. I’m sitting at my desk in the office and there is a Squirtle near by and every ounce of me wants to leave this chair and go find him.

Technology 40

Technology IT 40

The Unofficial Google Data Science Blog

JULY 31, 2016

By JEAN STEINER Randomized A/B experiments are the gold standard for estimating causal effects. The analysis can be straightforward, especially when it's safe to assume that individual observations of an outcome measure are independent. However, this is not always the case. When observations are not independent, an analysis that assumes independence can lead us to believe that effects are significant when they actually aren't.

Experimentation 42

Experimentation Testing Measurement Metrics 42

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

Experimentation