In the previous two posts on the Economics of Analytics (I), I laid out an overview of the problems I was having – specifically with the Hourly Model. In the Economics of Analytics (II), I argued that the agent-client relationship suffers from two horrible asymmetries in knowledge that cause the process of project estimation to become muddled and complex. In this post, I’ll write about the scalability of Analytical methods, which is just another way of saying “how much benefit can a client derive from a project given a specific agent, depending on the size of the client and the size of the optimization benefit”. The more I thought about scalability, the more I realized that analytical approaches themselves can[…]

In the previous post, The Economics of Analytics (I), I set the stage for the complications of risk management and trust in agent-client relationships. Assume that I’m a client. I know I have an optimization need, but, assume that I don’t know what is involved in fixing the problem. Assume that I have perfect trust in an agent. I tell the agent that I have a problem, and I ask for a fixed-fee estimate. (Tell me how much it’s going to cost). The agent can certainly be glib about it, and give me an estimate without probing the true nature of the problem. As a client, assume that I have some idea about the volume of work and skill that[…]

I’ve been working for quite some time this month on the problems around the Economics of Analytics. In what I think will become a series of posts – I talked with some fairly brilliant people and I’ll be getting their permission to quote them over the next few weeks. I spent a lot of time figuring out how to ask the baseline questions that were troubling me. At the highest level, the argument runs like this: It starts off with private discussions. We lamented that “the hourly model is broken” and were generally “frustrated with the way that the market rewards performance” in the client-agent relationship. I was also particularly frustrated with an inability to understand the scalability of our[…]

I’ve changed the commenting settings to allow ‘anonymous’ comments, so it should be a heck of a lot easier for people to comment. On the downside, it’s going to make it easier for certain bots to comment. But the aim is to enable a lot more people to make their opinions known and open up more discourse and cross-linking with your own blog.

A good friend on “teh client side” emailed a reply. I get a lot of email replies these days as the commenting system on Blogger isn’t so nice. “Actually CB, i would look for sources of traffic that convert, and then advertise there more. Also question why and are there any other sites like that out there that have just never heard of me and advertise there too. For ecoms, this is low hanging fruit. But, changing topics slightly, how do you judge if all that bookmarked, direct dial traffic is good? That is my specially urk these days.” On the first point – I agree. If I was noticing a big conversion lift from a source, such as a[…]

There’s gold in those Referring Sites figures! You can find it in Google Analytics under Traffic Sources and then “Referring Sites”. You have the topline pronouncement: “Referring sites sent X Visits via Y Sources”. (Search Engines don’t appear to count as a ‘referring site’, though, you’ll see “” sometimes listed under referring sites. Not sure what that’s about.) The most basic questions to ask are: “what’s X, what’s Y?” Next, you should ask: “How does that compare to all my other sources?” Then you get a figure – % of traffic from Referring Sites (under the “Overview” Tab). Then, you should ask: “Is it good?” And the reply, maddeningly, is: “It depends”. The default answer delves into the Comparative Benchmarking[…]

I knew there was mud ahead, but I had expected it to be frozen. After all, it was -36c when I started in – hell having been recently frozen over and all. Boy, did it thaw ever quickly! We’re all guilty of spinning the wheels once or twice, with just enough torque that you figure that you can get out of it. Nope. Stuck. Insanity is to cling to the drivers seat – spinning and spinning – expecting a different outcome. Now, you can be the do-it-yourselfer…get out, grab two 2 by 4’s, wedge those suckers under the tires, and try to get some traction that way. You call the CAA or, AMA, and get that tow truck to pull[…]

I’ve been lucky to be able to snag a week off for some reading and reflection. On the reading list – “Canada and the United States: differences that count” – which came on the recommendation of Joseph Carrabis. It’s a very good book. I trolled “Competing on Analytics” and “Supercrunchers” for golden lines that might resonate with non-scientists. And, on the back end, I want to finish “The Volatility Surface” and “Computability, Complexity and Constructivity in Economic Analysis”. I’m happy to read that others are having the same problems I am. “False Induction” is one, especially when you’re dealing with volatile data like web analytics. How do you quantify the rate of uncertainty once you’ve observed a pattern? Can you[…]

I had a very good conversation today. We talked about how data is not only completely silo’d in most organizations, but it’s also in very different formats. So, when it comes to unifying data for the purposes of extracting better insights from it – it’s a slog. Therein lies the problem. People don’t want to hear that it’s a slog. Take, for instance, the variety of ways that a phone number can be captured. In North America, I can think of five formats off the top of my head: (212) 555 5555212-555-5555212 555 55551-212-555-55551 212 555 5555 Is it all in the same field? Sometimes the country code is stored in a different field from the area code. The router[…]