While going through some old documents this week, I rediscovered a set of notes I took while reading Michael Porter many years ago. On rereading the notes, I find (again) his ideas to be really simple and compelling, worthy of sharing as a mental model for both practising data scientists and a value investors. A … More Understanding Industry Structure and Competition
Customer Lifetime Value (CLV) is a relatively new framework stemming from the idea of “treatment of customers as an asset”, in use at innovative companies like Harrah’s, IBM, and Capital One. The definition is a fairly natural one: CLV is the net present value of profit from all the future purchases a customer is going to … More Customer Lifetime Value and Its Application in Retail Analytics
Woolworths and Coles are the two largest grocery retailers in Australia. Between them, they command a large percentage of the market share, with the rest divided between Aldi, IGA, Costco, and smaller players. The recent competitive history between Woolies and Coles is quite an interesting one. Up until Coles was acquired by Wesfarmers in 2007 … More The Supermarket Trolley Index
To be a good scientist and investor, Charlie Munger counsels that we must “Invert, always invert.” It is in this spirit that I picked up the book Small Data: The Tiny Clues that Uncover Huge Trends by Martin Lindstrom earlier this year from Amazon. After spending the last several years evangelising Big Data up and … More Small Data: The Yin to Big Data’s Yang
Have you noticed more and more shopping malls are offering free wifi? That appears at first sight a puzzling investment, especially in this day and age where everyone has data subscription on their smart phones. But then you start noticing that it’s quite hard to get good signal coverage from your telcos inside those malls that offer … More Data Acquisition for Shopping Research
Incentive drives behaviour. If you have ever wondered why (brick-and-mortar) grocery retailers historically don’t pay much attention to understanding customer preferences — it’s getting better but things are still moving slowly — then you only have to look at how most of them make their money. It turns out that the main sources of supermarket profits … More Sources of Profit in Retail
Most of us have heard of this little puzzle in retail analytics: Assuming we know products A and B are usually purchased together from market basket analysis, how do we place them on shelves to maximise sales? The often-stated “sophisticated” answer is that A and B should be placed far away from each other because … More A Note on Shopping Efficiency and Product Placement
The Pareto Principle states that, for many events, roughly 80% of the effects come from 20% of the causes. The principle certainly finds expression in grocery sales data and the following diagram is quite typical of what one can observe. In retail parlance, the top product classes or SKUs are called the big heads and … More Big Heads and Long Tails in Retail
As the saying goes, retail is detail and to be successful in retail analytics, one needs to get many small things right. There is no one big simple idea in retail to guide us — marketing mix modelling comes close as a unifying analytical framework but there are still many facets that it doesn’t cover — … More How to Think About Retail Analytics
Combating terrorist financing
My Irrational Life
Updates on my research and expository papers, discussion of open problems, and other maths-related topics. By Terence Tao
Mental Models 4 Life 