Definition by Tools

Just as some people define they're identity by what they buy, some people define themselves by the tools that they use.

There's a certain cache about using the ACH. Or being an OCP. Or knowing enough to choose select instead of forward regression. Or the use of Bayesian methods. Coremetrics against Omniture. Google Analytics over Webtrends. R over SPSS. Graffle over Visio. And so on.

There's a large degree of tool centricity in three communities: web analytics, data mining, and marketing science. The irrational judgements about people in each of those communities, based on the degree of sophistication of tools, is dangerous. Worse - it's detrimental.

It's detrimental because it narrows your view.

For one, different tools are right for different lines of inquiry. Sometimes the solution is to use a form of Bayes. Sometimes the solution is to use a genetic algorithm. Sometimes the solution, to be driven down into a scalable algorithm, has to be possible in SPSS or in SAS. Sometimes simpler is better. Sometimes complex problems need to be addressed with complexity.

Having been through all three communities, I can say that Marketing Scientists are by far more statistically sophisticated than data miners. By several orders of magnitude. Marketing Scientists at this last INFORMS conference were working on problems, using complex methods, in efforts to clean up rounding errors in some of the most well researched areas, long hollowed out by the last cohort (auctions and competitive game theory come to mind!).

Data miners, on the other hand, use methods that are several orders of magnitude more complex than web analysts.

And yet, certain web analysts, examining log file data with their own commercial tools, using their methods, have far more understanding of how a complex system like a web site performs, than certain marketing scientists.

I'm not advocating aloofness.

I abhor the aloofness that goes with the generalist mindset. If you know just a little about anything, you really don't know much about something. You need to have a very strong base to be able to come out and engage others. You have to have something to contribute to other disciplines.

In 2011, I'm really going to try to think outside of toolsets. I won't let tools define who I am.

Tricky. We'll see how that goes.

NCDM Day 3 Roundup

It's warmer today.

Two points from Day 3:

• When pressed on what DM'ers thought of web analysts, some made comparisons to 'convenient reasoning'. The comparison wasn't made in a nice voice. That should actually really concern you if you're a web analyst.

• Broad concern about devils in details on FTC 'do not track' list.

Reflections:

I have a much better understanding of the problems that face DM'ers, compared to the problems facing WA's. Not all of them are interesting problems. Some of them are solvable if DM'ers and analysts work together.

The linkage between 'insight' and 'innovation' has been finally, for the absolute first time in my mind, been completely made. I may actually calm down about the use of the term 'insight' and 'insights' in the coming quarter.

A thank you to those who came out to our session on database versus web analytics.

NCDM Day 2 Roundup

Did I mention how cold it is outside?

A few points from day 2:

• Impressed with the transparency of Bill Whymark of GE. He detailed his segmentation process, in detail, and had a large number of slides which had been redacted by legal. Words x'd out in mid sentence. My key takeaway was the ongoing gap between value proposition writing (marketing / comm strategy) and segmentation. Bill was able to prove very remarkable lifts as a result of the segmentation as a result of operational improvements caused as a result of the segments (prioritization). Pretty powerful material.

• A second instance of creative override of segmentation was discussed in another presentation. An automotive enthusiast/under the hood segment was to be activated by way of a travel-roadster campaign. That's what the creative agency matched. (What?). There's room for creativity. Always. There's being creative for the purpose of being smart, and there's being a dipstick. Clearly, there's a lot more work to be done on the ArtScience frontier.

• New jargon: "A Test and Learn Agenda"

• Lots of people talking about incorporating social, and are really vague about it.

Emma Warrillow and I are presenting "The Clash of the Analytics Titans" on day 3. I promise the content delivers on the title.

NCDM Day 1 Roundup

It's pretty cold in Miami - coat weather. Not quite freezing like the rest of you. But cold.

A few points from day 1:

• I'm impressed with Jeff Robertson of Delta. It's the first time I've heard a loyalty points analyst use customer centric language, doing right by people, and meaning it. His reported actions, and the manner in which he reached conclusions, is truly customer centric. His mouth was aligned with his hands and aligned with his heart. A very smart, very brilliant presentation in applied analytics. No cynicism. Loved it.

• Language. Much of the rhetoric is very similar to what you'll hear at an eMetrics conference. Some of the words are a little bit different. For instance, instead of 'KPI', they use the term 'lighthouse metric'. Precision means accuracy, or, at least, is used in a manner that means accuracy. 'Convenient reasoning' is a proxy for 'confirmation bias' or 'proof seeking'. Loyalty isn't the same as affinity or satisfaction - loyalty means loyal behavior. The language is always off just a little bit.

• Unawareness of innovators dilemma among loyalty paradigmers.

• Obsession with the term 'unmet needs', and this meshing of that term with 'insight'.

• Most excitingly: the definition of the word 'insight'. I've been on about this a lot as of late. One gentleman used a definition which was just close enough to serial innovation rhetoric to resonate. In analytics terms, an insight is defined as being an original finding, causing an alternative decision path to be taken that is feasible, and whose execution results in an increase in profit. This definition of an insight happens to coincide with what we consider to be an 'interesting problem' in the marketing science sphere. It plugs nicely.
  

Day 2 is underway. Off to troll somebody else.

The Trinity

I caught a fragment of comment on an analytics podcast:

"Everybody has been asking me, where can I find great analysts that have the analytical skills, the communication skills, and the business acumen?"

To which I laugh. Purple hippopotamus time? Mega-swiss army knife time?


They are so few and far between. They exist, certainly. But in such small quantities. And there are fundamentally good reasons why this is the case.

Maintaining subject matter expertise is a challenge - it mandates keeping on top of new developments and practicing them. It's time consuming. (Seriously time consuming!)

Communication is perhaps a direct statement about the ability to produce ppt's and being concise. Being a subject matter expert does not lend itself well to being concise, but, with training and time - it can be overcome. Powerpoint is a medium worthy of analytical study.

The latent statement in 'communication' is politics. I'd argue that most analysts I know have office political empathy.

Business acumen is the final leg in the trinity. Not everybody knows how a business is run. I say that many analysts understand some part of a business very well.

Well, if that's what everybody is asking for, then perhaps, at the very least, some analysts should be using whichever methodologies at their disposal to learn how other people prefer to be spoken to, and to acquire 'business acumen'.

How people inquire

I appreciate how people use analytics to inquire.

Let me put forward an initial schema:

• Sometimes an inquiry is geared towards confirmation. You're only interested in information that supports your original point.

• Sometimes an inquiry is geared towards a situation. You're only interested in knowing what was going on. So you can keep an eye on it. (Situational reporting of straight numbers is not analytics. But sometimes people think it is.)
  

• Sometimes an inquiry is geared towards explaining a (perceived) an outlier. You're only interested in information that explains why that thing, that doesn't make sense, happened.

• Sometimes an inquiry is geared towards discovery. You're only interested in learning something new that you can ultimately use to your advantage.

The greatest fault line that will continue to shake the relationship between analytics professionals and their customers is the misunderstanding between confirmation inquiries, specific explanatory inquiries, situational (reporting) inquiries, and discovery inquiries.

All four of those activities require different methods, mindsets, processes, technologies - and - ethical tolerance.

Is there anything you'd add to the schema?