A Sales Forecast Model for Short-Life-Cycle Products: New Releases at
Blockbuster
We develop in this paper a sales model for movie and game products at
Blockbuster. The model assumes that there are three sales components: the first
is from consumers who have already committed to purchasing (or renting) a
product (e.g., based on promotion of, or exposure to, the product prior to its
launch); the second comes from consumers who are potential buyers of the
product; and the third comes from either a networking effect on closely-tied
(as in a social group) potential buyers from previous buyers (in the case of
movie rental and all retail products) or re-rents (in the case of game rental).
In addition, we explicitly formulate into our model dynamic interactions
between these sales components, both within and across sales periods. This
important feature is motivated by realism, and it significantly contributes to
the accuracy of our model. The model is thoroughly tested against sales data
for rental and retail products from Blockbuster. Our empirical results show
that the model offers excellent fit to actual sales activity. We also
demonstrate that the model is capable of delivering reasonable sales forecasts
based solely on environmental data (e.g., theatrical sales, studio, genre, MPAA
ratings, etc.) and actual first-period sales. Accurate sales forecasts can lead
to significant cost savings. In particular, it can improve the retail
operations at Blockbuster by determining appropriate order quantities of
products, which is critical in effective inventory management (i.e., it can
reduce the extent of over-stocking and under-stocking). While our model is
developed specifically for product sales at Blockbuster, we believe that with
context-dependent modifications, our modeling approach could also provide a
reasonable basis for the study of sales for other short-life-cycle products.