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 then there’s Michael Healy, Patrick Glinski, and me. I’m presenting with Michael Healy on sentiment. Michael Healy is among the best thinkers in this space and is just great. There have been a few very recent breakthroughs in sentiment analysis over the summer (and as recently as last week), and I’m looking forward to explaining how to treat the measure. I understand a core problem[…]
Author: Christopher Berry
We’re living in the most measured era in history. Are you the beneficiary of any of the data you’re generating? You optimize what you measure. One of the most data intensive self-improvement projects I undertook was in 2005. I recorded everything I ate and every exercise I did. And did I ever optimize – to the point where my joints couldn’t keep up with the muscle and bone growth. It was a massive amount of work to record all that detail, the weights of various things and then to cross reference with the USDA database. Then it all had to get loaded into SPSS for analysis. It was brutally time intensive. But it did generate incredible evidence-based insights about the[…]
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 a slow beast, and expectations of growth have persistently outstripped actual adoption, at least in North America, and especially in Canada. Adoption has a few drags on it in North America and Europe. No such drags exist in Asia. The chart below compares all the countries smartphone penetration. (Click to embiggen) That chart masks underlining maturity in each country. The chart below compares m-commerce ‘at[…]
This is a pretty good summary of the definition of data science. Some statisticians seem to be incensed. Some people say that this whole thing is invented as an O’Reilly buzzword. And there’s consternation, fear probably, over the devaluation of actual craft. Sound familiar? Ah, the great Web Analytics debate of 2007. Yes. We’ve seen this. Nothing like a fresh Gartner Hype Cycle in the morning, is there? But lets consider what technology is causing, and the role that data scientist will play, in driving that cause. Accessibility to data is expanding. What used to be the jealously guarded by people who didn’t want to be educators, is now liberally spread. It doesn’t really matter that most people don’t know[…]
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 analytics on the map. It’s likely. It’s just so damn relatable. Ideas have a long journey from conception to popularization. Nash had been known to game theorists and a sub-set of political scientists who don’t understand people, since the beginning. Most didn’t learn of it until ‘A Beautiful Mind’ came out. Moneyball is that movie. To extend the lesson from Moneyball – 1. Everybody has[…]
Google Analytics Premium was announced today. Finally. It wasn’t really a secret. What do you get for an enterprise fee? Dedicated support, a number to call, no data caps, some attribution modeling (nice), and now, 50 custom variables. There’s good literature around disruptive innovation in web analytics, with a very specific vocabulary and model build around. Is this disruptive or incremental? The increase to 50 custom variables is purely an increment on an established dimension. Enterprise support is incremental from the previous version of support. They did have a type of support. It was vague. But it was there. So that’s an increment. Increasing data caps is incremental. The guarantees are incremental. There was protection in the past. There’s more[…]
A lot happened at the F8 developers conference last week, the most significant was changes to the Facebook GraphRank and the Social-Product Graph. Instead of offering a single degree of freedom, to ‘like’ anything or remain silent, it will be possible for people to state (verb) + (noun) something. I have ‘read’ + ‘this book’. I have ‘watched’ + ‘dexter’. I have ‘eaten’ + ‘breakfast’. And, I hope, I have ‘bought’ + ‘this phone’. This goes to the notion of ‘friction’. Frictionless The term ‘frictionless’ was used a lot at the conference and this has significance. Friction is resistance to sharing information. It’s caused by technology, experience interruptions, and by, yourself. Let’s start with you. There’s a pretty good model,[…]
“The future belongs to the companies and people that turn data into products.”– Mike Loukides, O’Reilly Radar, June 2010. One of my favourite thinkers, Mike Loukides, repeated and expanded on that today. And a good thing too. It’s not as though product development alone is easy. Even when armed with the tears of hundreds of thousands of developers as a reference guide, you’re bound to contribute several of your own to the corpus. Google Search is the most familiar example of turning data into product. And it has a few effects you know about. We all know several dozens of people who can explain SEO in high detail. I know only four people who can describe the mechanic behind PageRank[…]