Data Science

Data Science is the mix of computer science, user experience, and statistics. The aim of data science should be: to make things better by influencing people and things to make better decisions, by making people and things more aware of better alternatives, based on better algorithms and more relevant data. Language kept intentionally vague to [...]

Oct

28

How consumers use mobile for shopping

How consumers are using mobile to shop IRL (In Real Life) is of paramount interest now that mobile has finally arrived. A few figures to run through. The first, below, describes what consumers report they want from mobile phone applications, for the holidays, in August 2011. A common behavior, well known to clicks-and-bricks retailers, is [...]

Oct

27

Web Analytics Wednesday – October 26 – Wellington

Web Analytics Wednesday is tonight at The Wellington, in downtown Toronto’s analytics alley. It’s generously supported by AT Internet. There are some 40 people – representing among the best of the best, who will be in attendance. It’s a great opportunity for web analysts, social analysts, marketing scientists, data scientists, hackers, developers, and usability professionals [...]

Oct

26

Data and Usability

Not all data is usable on its own. The vast majority of it isn’t in its raw form. Its coal. It has potential. But on its own, it has limited uses. Algorithms are the modern day equivalent to machinery. Fire (combustion) is really just statistical analysis – a violent process that generates waste in the [...]

Oct

24

eMetrics New York 2011

I’ll be at eMetrics next week. I hope you will be too. It’ll be great to be back in New York. There are a few people that I’m looking forward to seeing: John Lovett on social media, Melinda Driscoll on web analytics, Shari Cleary on media, Joseph Stanhope on mobile, Alex Langshur on government. And [...]

Oct

16

Our Mobile Planet – Select statistics for International Smartphone Penetration

Have you seen this site, put out by Google for their “Our Mobile Planet” study? It’s an excellent way to present data in a very accessible, very explorable way. I found it inspiring. The call to action is “create your chart now”. A very good, honest, call to action. The technology adoption S-curve can be [...]

Oct

10

Moneyball and Analytics

The plot of Moneyball is fairly well known among analytics folks. It’s a relatable example of how to  compete on analytics. Many statisticians love baseball. It’s a natural extension. And it’s been written to death about in the pop-analytics literature. It’s good stuff. It’s a nice case study. John Lovett predicts that Moneyball will put [...]

Oct

02