hello and welcome to data science Wednesday my name is Tessa Jones and I'm
a data scientist with decisive data and today we're going to talk about how to
deconstruct a data science question and why it matters before I start diving
into things I wanted to add a little caveat that I am a scientist and I love
chemistry and so we're gonna talk about things in terms of molecules and
elements so prepare yourself let's walk through this per usual with an example I
feel like usually that helps to really bring the point across so let's start
with a really big business question let's pretend that you're a marketing
person and you need to know how and when should we market particular products
really good important question for you to understand now this question by
itself we really can't answer because we need to know a lot more information we
need to know information about our product demand we need to know
information about our sales and we need to know information about our customers
so that's the beginning of the deconstruction process so let's let's
look at this first one right here what does our product demand look like we're
gonna think about it in terms of a product demand molecule so this molecule
answers this question and it's built by elements these are constructed of your
elemental questions so we have our elemental questions over here about what
our product demand might look like and those elements of questions are what is
the seasonality of our products what is the growth or decline of our products
what is the relationship of our products can products be grouped by common
attributes all of these elemental questions build our product demand
molecule that answers this question which then tells us what particular
products we should market to if we continue on with this example we also
know that we need to understand what will our sales look like in the future
so we'll call this our future sales molecule and all the elements that
compose that are listed here what attributes impact demand the most what
is our sales seasonality and and what granularity granularity do
we want to build a forecast model from once we know all of these elemental
questions we can have our future sales molecule built and if we continue down
to the last one we discussed what is our customer segmentation understanding who
we want to market to and and what that might look like and in order to build
our customer segmentation molecule we want to understand what attributes
define a customer and are there specific attributes that derive demand more than
others once we understand this we have our
customer segmentation molecule and now we can answer all of these molecular
questions and so once we combine all three of these together then we get a
really good picture that allows us to answer our global question of how and
when should we market particular products and to add if you go through
the process this way you're really getting added business value at every
step of the way because it does have a lot of value to answer these these
elemental questions what attributes to find a customer that's pretty good
information to have and it's even better information to understand what specific
attributes are driving demand these are important by themselves once you put
them together then you can answer questions about customer segmentation
which is even more powerful once you combine that with all these other
molecular level questions then we we have even more powerful questions to
answer so to kind of wrap up we start with a very big global question and by
deconstructing that question into the molecular and elemental questions that
support that global question we can not only get to a really good business value
output but we can also have value all along the way thanks for joining us
today my name is Tessa Jones with decisive data