MMM (Marketing Mix Modeling) depends on the concept of “Ad
Stock”. (To access a discussion of how
Marketing Mix Modeling works, click here MMM.) Advertising
is a catalyst; it changes a customer’s awareness, attitudes, and opinions, that
over time change their behaviors and hopefully increases sales. But the process is complex with many steps
within the minds of the customer, so the effects are seen over time. Ad stock is the distribution of these effects
over time.
Ad Stock is just one of many non-linear effects in Marketing
Mix Models. (To access a discussion of
some of the other effects, click here Non-Linear Effects.)
It is calculated (to over-simplify) but averaging the
volume of sales after each ad placement (if possible with other factors and
effects removed first). You look for the
patterns and usually “smooth the curve” to reduce noise. Usually after you do this you get a graph
like the one below.
Often a Marketing Mix Modeling project involves convincing
the client that ad stock exists, and that it often builds rather than always
starts at its highest point. People
naturally think that if they place an ad today they should see results
tomorrow. But that is just not how
advertising works. To prove this, I
usually show them a project I did for a client (the graph below). The client offered a 1-800 number in their ad
so people could request more information.
Note, that anyone calling a 1-800 number is likely already 90% sold on
buying the product. It probably took
them months of viewing ads just to get to the point of calling for more info. But I took the names and addresses of the
people calling the 1-800 number and matched them to names and addresses of
people who eventually bought the product.
I was looking for the time between calling the 1-800 and the actual
purchase. As you can see in the graph
below, sales built to a peak over the 11 months from the 1-800 call and then
slowly declined.
The above graph is for a “long term considered purchase”
product. You would expect the consumers
to take time to make the decision to buy.
But the same build of effect occurs even for impulse purchases like a
candy bar. If you see a candy bar ad,
you don’t run out and immediately buy the candy. More likely you won’t be in a store that
sales candy bars (and be hungry, and…) for days. But even if you are in a store within hours
of seeing the ad, in that case more likely you had already decided what candy
bar you were craving before you saw the current ad (but maybe the current ad
will inspire the next candy bar you buy after that one).
So Ad Stock often involves some build to a peak and then
decline of sales over time. But not
always. Some media do have a more
immediate effect. The below graph is the
ad stock for an ad that pushed an immediate discount on a product (with a time
limit on the discount). But it also had
a long term delayed effect because it got the customers thinking about buying
the product, which effected sales even after the discount was over.
But even “immediate effect” ad stock is more complex than
most people think. The below ad stock
curve was for an in-store promotion. It
was very effective at selling the item immediately (especially since it caught
customers who were in the store already), but also lead to “pantry
loading”. Customers bought so much of
the product they didn’t have to buy it again for a while and that hurt future
sales. However, the total effect was
positive, so the promotion did what it should have done. But a statistically significant drop in sales
afterwards also had to be put in the equation.
Most advertising (TV, Print, Digital banner ads, etc.) do
follow a build to a peak and slow decay pattern (usually following a “gamma
curve” distribution). But it takes a lot
of statistical effort to calculate the shape of these curves, their length over
time and where they peak. And they are
different for every media and marketing factor and every product. There are no “one-size-fits-all” ad stock
curves.
And often ad stock curves can get very complex. Competitive ads ad stock is particularly
complex. Competitive ads are a major
factor in models for new products trying to make a mark against an established
market leader. In the case below, my
client’s sales dropped immediately when their large competitors run a big ad
campaign, but then would grow after that (as more customers entered the market
for their product category based on the competitor’s ads), and in the long run
would drop again (as the large competitor won new loyal repeat customers).
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