|Research Blog - Customer Intelligence|
New record for longest-time-since-blogging - over two months! Well, to be fair, there was Christmas and I went to South East Asia for 5 weeks.
Last Friday I had doctoral consortium were I presented some of my views. Seemed to go fairly successfully: there was a mixture of healthy controversy and curiosity from the academics.
I met with my supervisor Graeme today, in preparation for a meeting with the industry sponsor, Bill, next Tuesday. It all seems to be ticking along nicely. The above-linked slides are the best formulation yet of the topic, and I'm moving closer to having the research questions elucidated. I believe the key is the idea of information as a discriminator - information is that which allows us to seperate, filter, distinguish and group. A central strategy for many organisations is to treat people differently, and there are numerous value models that explain the benefits of such differentiation. Information, then, is to be assessed on its ability to do such discrimination. Ie customer segments are valuable to the extent that they allow differentiated treatment of customers, information is valuable to the extent that it supports this segmentation activity. In order to measure this, we have to break-out my favourite tool - entropy.
I like this formulation because it pushes the value measuring problem onto an existing marketing area associated with CLV, CVA, LVT etc. It also naturally accomodates the difference between information at different levels (ie "average customer wants to spend $10" and "Robert Smith wants to spend $10").
My current approach is the gedanken experiment - I'm constructing a hypothetical model around Krusty Burger seeking to upsell fries, where it knows the cost and benefits of asking, and either being accepted or rejected. This is useful for me to sort out some ideas and look at generalisability.
This leads to my next point: I need to be careful with my research that it doesn't piss off the stakeholders. The reason is that I'm more comfortable with taking on risk than my supervisor or industry sponsor. I'm also happy to stay away from industry and then emerge from my Ivory Tower after a couple of years and say "You should do it this way" and pretty much leave it at that. I think I missed the boat on that as a viable research option (sometime in the 1970s). That said, I'm pretty sure I don't want to gain any "deep insight" into a particular case study and analyse the political macchinations and generally humans-as-social-animals approach (people react to situations depending on how they think it affects their careers - suprise, suprise!). Nor do I want to canvass "best-practices" from a dozen organisations. AFIC, if people want that they can pay Gartner for it like everyone else.