If you are surprised by the title statement, you are in the majority.
This is actually a very strong statement and I did not make it lightly. It is saying that micro attribution is an area of data analytics that can be defined and studied with rigorous statistical methodologies. In short, it is more of a science than art or common sense. Micro attribution problem is more like a response modeling or risk modeling problem than the problem of finding out a fair rule for distributing year-end bonus.
Does this sound the same as how others describe attribution problem and solutions?
It is certainly different from those who think the solution to attribution problem is about tracking. Tracking is important because it provides you the data, but in itself they do not tell you what factors or customer experience have more or less influence on conversion.
It is also different from many who think about “last click”, “first click” etc. when they speak about attribution models. Those are not data analytics models or statistical models that I was referring to. One is about intuition-based smart rule; the other is about data-driven behavioral modeling. The smart rule vs. modeling debate was long over in Direct Marketing, but it is just beginning in web analytics and online, right here in the micro attribution problem.
It is also different from the many who think this is all about metrics (because of the claim that there is no right solution to attribution . It is not about averaging the attribution of first-click and last click. It is not about using engagement metrics as a proxy either.
It is definitely not the same as those who think we need to wisdom-of-the-crowd type of solution. The percentage of you who think early keywords should get 15% attribution for “assist” maybe right, but it has no bearing to me. I do not believe that there is an average truth in any of these, for reasons that I do not believe one retailer’s offer-X response model shouldn’t be used for a loyalty campaign of a telecom company.
It is categorically different from those who hold that there is no right answer to the attribution problem. I agree that there is no perfect model that has no model prediction errors, but that is not a refutation for statistical modeling. Statistics is founded on imprecision in data and never afraid of counter examples.
It is an approach of simplification, not of complication and certainly not a proposal to bring in psychology, media-logy or astrology into the picture. In that regard, it could be a spoiler for the fun party we had so far.
Still, it is really just a claim at this point. Please come back to read the next post: (TBD)