On Tue, Nov 5, 2013 at 5:44 PM, Michael Kay <mike(_at_)saxonica(_dot_)com>
wrote:
This can be
compounded by non-technical issues such as data owners not seeing the
information they actually have because they are blinded by their
expectations of what it is "supposed" to be.
Sometimes the data owners are better clued-in than the technicians. I
remember a friend who was the IT director of a supermarket chain telling
me (about 20 years ago, when data analytics had a different fashionable
name) about a sales presentation he had just sat through telling him all the
wonderful things he could do with the data from his tills. His remark:
"What I really want to know is what the customer didn't buy because it
wasn't on the shelves. They don't seem to realise that we haven't got
that data."
This can be gotten using techniques similar to how they can recommend
books you haven't read and movies you haven't seen.
"Many firms use decision tools called “automatic recommendation
systems” that attempt to analyze a customer’s purchase history and
identify products the customer may buy if the firm were to bring these
products to the customer’s attention. Much of the research in the
literature today attempts to recommend products that have a high
probability of purchase (conditional on the customer’s history). ......
ANAND V. BODAPATI*
Journal of Marketing Research
Vol. XLV (February 2008), 77–93
77
© 2008, American Marketing Association"
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