Stefan,
In my case, these products are not anything that expires (not food items)
so your method could work there as well -- in some cases simpler is
better.. I've got recorded data archived (SQL database dumps) going back
approx. 3-4 years for an older version of the code I wrote in PHP.. I'll
have to find a way to move the data into my Glorpified database and then
run some stats on the data and see what is spat out.. Thanks everyone!
On Tue, June 24, 2008 3:10 pm, Stefan Schmiedl wrote:
> On Tue, 24 Jun 2008 16:51:19 -0400
> "Glazier, Sean" <
sglazier@...> wrote:
>
>> You could write rules for extracting the person likes and interests from
>> what they buy and correlate them to the product categories and perform
>> another analysis to take the top ten picks etc.
>
> Or just try some simple statistics (basically "yesterday's weather") to
> provide estimates. The applicability of this approach depends heavily
> on the lifetime of your store items, though.
>
> If the articles are "long-lived" (as you indicated in your OP), you
> could just collect the ordered amounts per year and extrapolate from
> that. This approach works very well with one of my clients, where
> a human is using these indicators for managing the stock and haggling
> with suppliers.
>
> s.
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