By Kevin Gray
Data…Science…Statistics…Machine Learning…sounds dull and dreary. Mechanical and not very creative, right?
Maybe not. I don’t believe there is one official definition of it but for the purposes of this article I’ll define Marketing Science as the application of scientific principles in marketing. Statistical modeling plays a major role in Marketing Science and “scientific principles” may indeed sound dull, dreary and mechanical to many but in reality there is great deal of Art in Marketing Science. Though we strive to emulate hard science we do not work under strict procedures mandated by a government authority. Actually, in some ways Marketing Science is a lot like jazz.
Jazz? Misconceptions about jazz also abound but from the opposite direction. As no less an authority as Winton Marsalis has put it “Jazz is not just ‘Well, man, this is what I feel like playing.’ It’s a very structured thing that comes down from a tradition and requires a lot of thought and study.” Many kinds of music are called “jazz” but nowadays nearly all jazz musicians are thoroughly trained in European Classical music and some, like Marsalis, are virtuosos on their instruments. In a jazz performance there is a structure that is a platform for improvisation, but the rule is not anything goes when you improvise. There are right “wrong” notes and there are wrong “wrong” notes.
While I wouldn’t want to stretch the parallels too far, this also applies to Marketing Science. We do our best to adhere to the scientific method but the reality is that much of what we do is improvised. For example, data are sometimes (figuratively speaking) dropped on our desk and, to paraphrase John Coltrane, we need to start in the middle and move in both directions at once. That is, we have to uncover what the original purpose of the research was and, at the other end, what the client is expecting as a deliverable and how it will be used. We should not just mechanically use a method we’re comfortable with.
Importantly, we need to be cautious about using labels. We don’t simply open a data file and “do” Latent Class, for example. One reason is that “Latent Class” is a generic term that in practice can refer to vastly different kinds of models that include basic Cluster Analysis, Structural Equation Mixture Modeling, Latent Transition Analysis and many other variations. Moreover, in a segmentation study I might have Latent Class cluster analysis in mind as my first choice but when I get to know the data another approach, older or newer, might actually work better. Not quite, in the words of Miles Davis “I’ll play it first and tell you what it is later,” but nevertheless competent Marketing Scientists steer clear of cookie cutters whenever possible. (A tip for younger researchers: these are reasons why you should not sell statistical techniques!)
Modeling itself should never be the purpose. Like a saxophone, piano or trumpet it is the means. Something else to keep in mind is that modeling can be complex, but its at times bewildering details more often than not are insignificant to our clients. A comment by Charles Mingus strikes a chord: “Making the simple complicated is commonplace; making the complicated simple, awesomely simple, that’s creativity.”
Both professions require considerable study, both formal and on the job. Woody Shaw was almost obsessive about using every performance and every interaction with other musicians as an opportunity to learn. There are many connections between the two professions in our daily (or nightly) work lives but also at a deeper level. I recall from taking John Holland’s personality inventory many years ago that Investigative and Artistic types aren’t that far apart.
Jazz trumpeter John McNeil, a faculty member of the New England Conservatory of Music, has written a book called The Art of Jazz Trumpet. The instructions to one set of exercises in particular caught my eye: “Play the following exercises as legato as possible. Use them as models when you make up your own exercises.” …when you make up your own exercises…seven words that speak volumes about an approach to learning that is radically different from what most of us are accustomed to. What is the bearing on Marketing Science? When learning new a modeling method we may create artificial data, test a assortment of techniques and options and make many trial runs. We experiment so that we understand and will be able to use the new procedure in a real “performance.” We make up our own exercises.
Again, though I don’t want to exaggerate the similarities between Marketing Science and Jazz, there are a surprising number of them that have practical relevance. Being disciplined and ever willing to try new things are essential to each profession. We both need to be detail-oriented and creative. So, to sum up, there is a lot of Science in Art and there is a lot of Art in Science. Both are human endeavors.
I’ll let Coleman Hawkins have the final word: “If you don’t make mistakes you aren’t really trying.”
Jazz fans and those wishing to learn more about this unique art form may find this link to jazz radio stations helpful: http://radio-locator.com/cgi-bin/finder?format=jaz&s=R&sr=Y .