Role of Analytical Marketing

Looking at marketing problems through the lens of economic theory and statistical methods is what we mean by the term, "analytical marketing." The real benefit to this approach is that it can serve to resolve issues within marketing departments that are otherwise dependent on intuitive judgment or other, less rigorous pieces of analysis like consumer research. Some questions really can't be solved without working through the theoretical implications of utility-maximizing consumers who face a budget constraint.

I suspect that what is happening in marketing is similar -- in some ways -- to what happened when economists started reading Samuelson (who has just died over the weekend at age 94). Of Samuelson, Robert Lucas said, "He'll take these incomprehensible verbal debates that go on and on and just end them; formulate the issue in such a way that the question is answerable, and then get the answer."

A lot of marketing departments will attempt to attack important questions without allowing themselves to build the proper framework for discussing the issue. So we sit in meetings where marketers will say things like:

• I wouldn't stop using our product if it cost a little bit more
• Customers haven't reacted to price increases before, but this could be the straw that makes them all switch producers
• Somebody like my grandmother only cares about [feature X]

Thing is, these statements might all be true. Problem is, everybody shows up at marketing meetings with a pocket full of these prior beliefs and little anecdotes about mythical consumer types, and feels free to put them to work -- whatever the question might be.

One solution is to use data to answer questions. The problem is that data seldom want to cooperate. If you look at a graph of customer churn for the last five years, for example, you are going to be able to fit all sorts of trends into the data. And every shift in the trend that we think we see is going to have lots of explanations -- often the supposed behavior of the same mythical consumers we were trying to ignore in the first place.

What we think we can do with the right analytical approach is not so much simply using the right statistical tools to answer the question, but using theory to frame the question properly.

Here's what I mean: Suppose we sell a primary good as well as a secondary, optional, good. Movie tickets and popcorn, for example, or basic cable and premium movie channels. We care a lot whether reducing the price on the secondary good will get more people to purchase the primary good. And this is precisely the kind of question most likely to be subject to stories about whether someone's grandma never bought popcorn at the movies, or whether the customers will all defect because a competitor is offering HBO for $1 less than we are.

Moreover, this is precisely the kind of question that isn't likely to be settled by looking at some data. Every observed change is going to be over-determined: every change will have a dozen explanations.

Instead, what analytical marketing can do is to reduce the number of variables to something manageable, and define what must be true in order for some policy to be correct. It is one thing to say, "People won't respond to a price change." It is another thing to say, "I think the correlation between the two products is lower than the threshold value." One statement is meaningful (we might be able to estimate the correlation of demand), while the other is not.

So analytical marketing is always asking: what does it mean to be right; what does the right policy look like; how can we test it?

And that's the main benefit, in my estimation. Analytical marketing reduces the scope of disagreements and the power of unexamined prior beliefs.