SAS Visual Analytics Demo for Retail

[MUSIC PLAYING] DRAGOS COLES: Hi. My name is Dragos Coles. And I’m a systems
engineer at SAS. Today, we’re going to use
Visual Analytics to look at transactional retail data. We’re going to go through
a segmentation exercise. And we’ll do some market
basket analysis reporting. The reason I want to
do all these analyses was because I’m going to try to
optimize my marketing campaign. And also I want to try to
personalize my campaign lists. So again, as I
mentioned, we are working with transactional retail data. On the side here,
on my Data tab, you’ll notice I have attributes
about the transactions, like a transaction timestamp,
transaction ID, a location. I also have some attributes
about my customers like customer ID and some
demographic information as well. What I want to focus on this
time though is my sales. And I want to look at the
average transaction sale. And let’s just explore
this really fast. Overtime, I can see that my
average transaction amount kind of hovers around
upper 30s, 40s. I have a couple of
spikes and variations, but typically stays
fairly constant. Since I’m looking at
a trend over time– let’s build a
forecast really fast. Visual Analytics is
looking in the background and forecasting a
model portfolio. And it’s just selecting
my champion forecast. The idea here is
though we’re looking at this average
transaction amount. And my goal with
this campaign is also I’m going to try to see if
I can drive this transaction amount to go up a little bit. The forecasting capability
in Visual Analytics is going allow me to do
a few things to do more than just a simple forecast. Let’s bring in some
additional measures. And what I’m going
to try to do is I’m going to try to see
if I have any underlying factors that could impact
this average sales amount. And I see that I have
actually three underlying factors in this case. I have margin, 12-week
RFM, and marketing budget. This could be intuitive
that this might be the case. But since I have this
underlying factor, the next thing I
might want to do is I’m going to try
to run a scenario. Now, let’s see what happens
if I increase this marketing budget by 40%. You’ll notice actually that
this average transaction amount and did go up a little bit. However, now the
question becomes are we going to get an increase
of 40% in our marketing budget. And the answer is probably not. So let’s take a
different approach. Let’s work with them the
decision tree capability in Visual Analytics. And we’re going to try to
segment our customer base, so that we can create a more
targeted marketing campaign. So again, our target variable
is sales or average transaction amount. Then bring in some predictors. In this case, keep in mind we’re
not doing a predictive model. We’re not going to
get propensity scores. What we’re going to use the
decision tree capability is to run a segmentation
and try to identify some segments of our
customer population to make sure that
maybe there’s something we can target in there
in our upcoming campaign. As I take a look at
the decision tree, a few things are happening here. One, I can see some
of those segments, by looking at the terminal
nodes, for examples, within this tree. Also, as I hover
over these nodes, I can see what the
average transaction amount is for this specific segments. So in this case, this node
has a $67 average transaction. This other node here
on this left side is a $19 average transaction. So right away, we can
identify certain segments. The segments are defined by some
of the attributes do we dropped onto our decision tree model. And we can see we have
transaction day of week. We have age bucket. We have channel type defining
some of these segments. But what we’re really
trying to do here is I want to get a
better visual of all these segments and the
average transaction amounts. And as I look through
this list here, I can see that we’re dealing
with three main categories. I’m going to call this
low spenders, people who are spending on average
under $20 per transaction. Our average spenders,
they, again, hover around the upper
$30 per transaction. And finally, I’m going to call
these the high spenders, who are above $60 per transaction. And I want to focus
my marketing campaign on this particular segment. Since I’ve built
this decision tree and I am on identifying the
segments, what I’m going to do is I want to be able
to capture the segment. And the way I’m going to
do that is simply just create a calculated item. We will call this calculated
item decision tree segments. And as I create this
variable, the variable is going to show
up in my Data tab. I’m going to try to
capture this segment along with the rest of my
transaction information. So let’s just capture,
maybe, transaction ID, transaction date, time. We’ll get the segments
and our customers ID. What I want to do
with this data set now I want to be able to run
market basket analysis. And I’m going to use Enterprise
Miner, SAS Enterprise Miner, which is our data mining
solution to run data analysis. Now simply all I have to
do is export this data so I can pull it into
Enterprise Miner. Once we’re done with the
market basket analysis, what I want to do is I want
to be able to report on those results. Market Basket produces quite
of bit of information for us. And we’re going to
use that information to be able to fine tune, again,
the customer marketing list. And this is the goal of
this particular report. And it also gives us measures,
like a lift measure, which will allow us to identify,
one, the customers that we want to advertise
too, and, two, which items do we want to advertise. This gets to the personalisation
of that marketing message. If you look into my
customer market list, the rules are representative of
two main items– the left side, which tells me what items
exist in the customer’s basket, and the right side, which
tells me the items missing from their baskets. And these are the items I
might want to advertise. Also, the way I’ve set
up this little report is so that I have
some interaction. And first thing that
I want to do here is I want to select one of those
segments that were produced with the decision tree. And here I have
those high spenders. As I make selections
on this report, let’s also go after
customers with a higher lift. Again, I’m going
to make selections. As I make those
selections, things are going up to update and
refresh on my dashboard. And this really gets to
sub-setting the customer base from within this
particular segment so that I can really optimize
and fine tune my marketing list. But at the same time, I’m also
personalizing the marketing message exactly. Which product do I
need to advertise next. I hope you liked
what you saw today. If you’d like to try Visual
Analytics please visit

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15 thoughts on “SAS Visual Analytics Demo for Retail

  1. I want to learn SAS software and how to use and Interpret, My background is in Sales and Marketing with MBA behind me.
    So to make sure you understand, I am looking for training to use SAS software and produce results or analyse Market and find a job with this certification.
    My email. [email protected]
    how much will it cost, the time duration and will it be on video related course or on line for certain hours per week. please reply with all the necessary info to get going. When and how soon can we start.

  2. Can we have a demo report on Social Media Analysis as well for FACEBOOK, Twitter and Google Analytic as we are having in built API for Twitter and Facebook.

  3. Thanks so much – this is great! Just a question – how did you work out the lift, What is the formula use. Is it a simple correlation test between the two products

  4. Hello, I'm trying SAS Visual Analytics in
    where I can find these datasets, but there is a problem that i can't fint how to import or export data sets… Do I can import or export datasets in there?

  5. Hey can this software be used in and for places like Africa, or Nigeria to be precise?
    If you do not have the enough customer data on the Nigerian local market

  6. Is SAS VA available for students to practice just like Free University edition. If yes then please let me know how to access the same.

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