Many retailers know that if they could really anticipate our purchasing patterns and where it leads to – that this could be very beneficial to them since they could reach the customer quicker and more efficiently. And for many retailers “holy grail” application in the family or women’s segment is pregnancy prediction.
We all know
that life of any individual or family is
very different in terms of priorities, habits and shopping behavior – before and
after baby is born. At very least no one should argue that it should be
different. So, to be able to time such
“earth-shattering” event where old world is gone and a new star is born – and
then “help” that individual or family by paddling your own products ahead of
competitors - can really get you large
share of their wallets on purpose of serving their needs better than competitor. What is wrong
with that? Well, few
things can go wrong here, mostly in “privacy” department, and some “smarties”
who went ahead of themselves eventually learned their lessons and they had to
move a few steps back.
Lets’s
start with conceptually outlying how you could build pregnancy predictive
model, before putting a few warning signs, kind of “proceed with caution” or
“danger ahead”.
The
first thing you need to do is to put the "carrot on the hook" for any female customers
who would be willing to share their pregnancy secret with you (first or second
trimester preferable) for some hefty promotional discounts. Once you have a
critical mass of newly pregnant customers – it is just a matter of capturing
their purchasing history, so that you are able then to differentiate between
them the rest (non-pregnant segmented) in the form of robust and accurate
predictive model. Once, such model is in place it is a matter of implementing
it, monitoring it and measuring value it generates.
All
sound well and good - here is reality..
Once
upon time there was one very clever man, in very clever marketing department of
one forward-thinking retail company. And that man created a very smart data-mining
model who could predict if woman customer is pregnant. Soon after mailing list followed to its
likely pregnant female customers. As the story goes there were some very impressed
customers who were amazed with “how did they know”? But they were some who were
not so impressed, and they asked different questions of “how did they dare to
know”? There were also some who felt wrongly “impregnated” like the father
who stormed marketing department accusing them of leading his teenage daughter
into getting pregnant - so they can sell to her their new range of baby
products. But then, a few months later the same father end up sending letter of apology
after discovery that his daughter was indeed pregnant!. Not to say that he was
being completely stunned by how this retailer knew something he did not - even though his daughter lived with him.
The
biggest problem was that many customers felt spied on, feeling that their privacy
was compromised, so they started cutting ties with this retailer and doing
everything they could to hide their purchasing behavior. This prompted retailer
to adjust accordingly their model execution. And the only remedy was to blur
the fact that they had such probabilistic knowledge. This resulted in
promotions where baby-products coupons were masked with other vouchers, and
therefore it was no longer obvious that marketers had such knowledge, which kept
customers at ease. So, if you are
competing for baby product market think carefully about how you navigate
through this. Could be some stormy waters just when you think it is smooth
sailing.
Goran Dragosavac
SK Data Entry Services is dealing with data conversion services.It convert data from one format to another.It doesn't take much time.Within few time we do our work as transforming the particular format.
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