| Probabilistic Scaling (PROSCAL) is a powerful
and flexible analytical tool for representing and understanding complex
objects. The power of PROSCAL comes from its sophisticated
modeling of how subjects perceive, prefer and choose objects.
PROSCAL models objects, such as consumer packaged goods, and subjects
(market segments) as distributions in a multidimensional space. The
distributions measure the differences that exist in the certainty with
which consumers view different products and attributes. Probabilistic modeling allows PROSCAL to
capture the complexity of
perceptions and test hypotheses that provide understanding of how
consumers view products and make product decisions. By realistically
modeling the richness of consumers' cognitive processes, high quality
estimates are obtained. In addition to helping analysts better understand the
structure of a market, PROSCAL estimates perceptual shares for existing
and experimental products and permits what-if modeling that allows the
evaluation of different product development strategies.
PROSCAL can utilize a variety of input data types including product
profiles, liking ratings, choices, similarities and preference
ratios. Data types can be analyzed individually or in combination
with other data types. Models can be constructed for up to sixty
products in spaces of one to six dimensions, employing Euclidean or
city-block metrics.
PROSCAL comes in two versions - an interactive
windows version built around S-PLUS and a command line version that can run
in a MS-DOS environment. |
