Two Statements and Four Questions About Big Data

This series appeared on the Eyes on Analytics blog the week of May 14. It’s consolidated here in part because it was popular. Consider the following two, distilled, points of view: Statement 1: “Big Data Analytics is going to change the way we do business. Sure, a lot of it will be routine “I’m okay!” [...]

May

21

Testing Three Themes

Post frequency on the analytics focused blog, Eyes on Analytics has increased to daily. In part, this is to solidify the understanding of the frequency-reach curve in blogging, and in part, it’s an attempt to understand where the broader market is at. I’m testing three themes: How to fight nature’s pesky way of inhibiting our [...]

Apr

15

Why don’t the campaign components add up?

Sometimes the components of a marketing channel will not add up to equal the total performance of the marketing channel. This is caused by any number of realities and limitations imposed in part by nature, and, in part, by you, the marketer. Consider the following deliberately simple scenario: March 2012 Impressions: Total Digital Impressions Delivered: [...]

Mar

17

Who’s Downvoting You On Reddit?

So who keeps on downvoting you on Reddit? We’ll find out. But first – three notes: You may be familiar with Reddit. If you’re not – you can read this explanation about what Reddit is. To answer that question, I downloaded a dataset that was built in early 2011 or very late 2010. The dataset [...]

Feb

12

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

Next Page »