Commentary on the proposed telescreens

You may have read something about the Samsung 7500 and 8000 series televisions, the ones with a camera installed in them, over the past few days. The tl;dr summary: “For Samsung’s 7500 and 8000 series TVs, all you have to do is say “Hi, TV,” when you walk into a room for the TV to [...]

Jan

15

Find Hidden Patterns in Big Data – A Commentary on MINE, Reshef et al (2011)

You may have read something about ‘Detecting Novel Associations in Large Data Sets’, a paper appearing in Science, 334, 1518 (2011) by David N. Reshef et al.. You can check out the software here. This is an initial commentary and an explanation about what it’s all about. The Longer You Look, The More Likely Error [...]

Dec

18

How to predict how many visits a website will receive on a given day

Predictive analytics is somewhat mysterious. So, let’s shed some light on it. (Note that I’m simplifying this quite a bit to be accessible.) The first step in predictive analytics is to understand what you’re predicting. We’ll call this the Y variable. In this instance, ‘how many visits from Boston can I expect on a given [...]

Nov

16

Siri and Search

Gary Morgenthaler had a few interesting statements to make: “Therefore, when Siri was an independent company, its plan was to map these domains deeply and seamlessly to automate transactions for its users within them. For example, “Buy that Steve Jobs biography book and send it to my dad”; “Send a dozen yellow roses to my [...]

Nov

09

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

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