Knowledge is only power when you know what to do with it

"Strive not to be a success, but rather to be of value" -- Albert Einstein

Not that long ago I was pitched some predictive analytics project that was promising (according to the vendor) to solve many of my problems. Or, in their words, "just imagine all of the things you could do if you knew that this person is more likely to buy your services than that person". That's usually when the thinking stops and the dreaming begins. However, back on the ground, the question remains - given that knowledge, what exactly do you think you should do, and how do you know that this will be more efficient than what you are already doing?

The whole concept of "doing something" in marketing assumes that 1) your action will change behavior (analysts usually compare to a control group to assess if the behavior changed) and 2) the benefit from change is large enough to pay for the action you have taken. Often, both of those things are assumed to be true, and the action is taken. However, our curious analytical minds cannot take anything for granted, so let's just list some thoughts on why this type of knowledge may turn out a lot less useful when we start executing on it.

• It is not clear that the behavior can be changed. For example, if you know that someone is likely to disconnect your services (stop purchasing your product, stop paying on the mortgage you are holding) because they lost their job and can no longer afford it, then there is really little you can do to make them keep the services - or, at least, do it in a way that is profitable to you.
• It is not clear that the behavior needs to be changed. If someone is likely to buy your product, maybe they will - in quantities large enough that you can't improve with your communication. If someone shops at your store every two weeks, provinging a discount often only leads to giving away discount on the purchase that would have happened anyway.
• It is not clear that you can change the behavior with your action. This is related to the previous point stating that there may not be enough change in the behavior for the action you have chosen. This means that you may have to test a variety of actions, which often makes the knowledge you have obtained from the predictive research less and less relevalnt.
• The research does not give you much clue on who you want to target. That's when your vendor is going to throw a fit - of course it does, that's the whole purpose of the exercise! Hold your horses, though. So, if one person is more likely to buy your product, why does it mean that this person is more likely to change their behavior and buy your product after receiving a direct mail piece than the other person? From my experience in measurement based on recency, those who have bought the product most recently, are much more likely to buy again, in fact, so likely, that it makes little sense to send them a coupon. It is the other group - people who have bought before, but have not bought in a while that show most change in behavior when sent a coupon. The change is measured as a lift over control group, not as overal response rate. What that says is that if you know that person A is more likely to buy than person B, person B may turn out to be a more profitable target. Combined with the previous point - after all that money spent on predictive research, you still don't know what action to take, and whom to target with it!
• The research does not give you any information on whether your action is a cost effective way to act on the knowledge. We are again measuring our action against status quo, and looking for a lift in revenue that makes our efforts worthy.
• It is not clear that you should change your approach to the market. Assuming you have done some prior in-market testing and measurement, and figured out how to segment your market in a way that appears to makes sense based on responses to your communication, it is not clear at all that the additional predictive knowledge is going to help you optimize your marketing. It is nice to know that someone is likely to purchase or cancel your services, however, it does not necessarily ensure a change in strategy. If you know that a certain group of targets needs to be mailed every X month for optimal response, you don't really care that it is because they are more likely to purchase the product - or because they are less likely to. All that matters is that your mailing has been tested and optimized for efficiency.
• It is possible that your optimal go to market strategy is independent of the segment. That actually happens to good strategies - they let the customers to reasonably self-select, and they offer solutions optimized to serve certain needs. Customizing them on an individual basis is not going to move the needle much, but efficiencies will be lost.

The conclusion is that although the knowledge is a good thing, it is not always possible to use knowledge to improve business results. Correct testing, measurment and execution are generally more important for marketing optimization than having predictive knowledge.