Pat LaPointe wrote a pretty interesting article for MediaPost Publications. You can check it out here.
My response is pretty much ‘Yes, And…’
I don’t understand why some people are making inductive inferences that online word of mouth is somehow reflective of offline word of mouth. (As a certain company appears to be making). I share his concern and skepticism.
Let me unpack that.
A whole generation of quantitative market researchers are supposed to understand that if you take a small, random sample of a population and expose them to a treatment, then you can make an inductive inference on how the entire population will react to that same treatment. The probability that the inductive inference is accurate is a function of the sample size and basic probability.
This is why when we randomly call 100,000 people, and get 1000 responses, we make this inductive leap that those 1000 people are reflective of 300,000,000 million people.
This is the field called sample statistics. It’s an inductive science. And it has it’s problems. And it has it’s benefits.
I’m stunned that any firm would take a word of mouth dataset from the Internet and infer that it is reflective of what goes on offline. I don’t believe that there an inductive leap can be made that way. (Moreover, there’s a deeper problem with the self-selection bias that happens in the survey methodology, but that’s another rathole for another time).
However, I will say that online word of mouth analytics has much more in common with data mining than sample statistics. Remember the reason why sample statistics was invented in the first place? It was because we couldn’t possibly collect, store and run algorithms on such massive datasets.
Now we can. Giddyup.
Now, the next part.
I disagree that Word of Mouth (WOM) research is still in its infancy. We’ve inherited a very rich base of literature and understanding about how WOM really works, especially as applied to marketing and commerce. Being ignorant of that literature doesn’t mean that we’re all in our infancy. It just means that most people are in their infancy in terms of understanding.
Contemporary WOM research is now some 60 years old – and has been intensely studied from the 1960’s on. The number of databases we have to go off of is very deep, and debates within the Marketing Science community are nuanced and relevant. I’ll be touching on just two of those debates at eMetrics Toronto on April 9th.
There is much triangulation in methodologies in grappling with social media measurement, and indeed, brand measurement. We have approaches that span computer science, brand measurement, direct measurement, database marketing measurement, linguistics, decision neuroscience, psychology, marketing science, web analytics and data mining – just to name a few. We’re there. We’ve been there for a long time now.
I don’t believe that anybody really wants to hear how complex it is. These are problems that leaders will solve. The market will always reward people who will make the complex – simple.
In sum, prepare to be even more annoyed, Pat. Breathe deeply. We’re in for a very exciting decade.