| Abstract: |
Different instruments are relevant for different marketing objectives
(category demand expansion or market share stealing). To help brand managers
make informed marketing mix decisions, it is essential that marketing mix
models appropriately measure the different effects of marketing instruments.
Discrete choice models that have been applied to this problem might not be
adequate because they possess the Invariant Proportion of Substitution (IPS)
property, which imposes counter-intuitive restrictions on individual choice
behavior. Indeed our empirical application to prescription writing choices of
physicians in the hyperlipidemia category shows this to be the case. We find
that three commonly used models that all suffer from the IPS restriction - the
homogeneous logit model, the nested logit model, and the random coefficient
logit model - lead to counter-intuitive estimates of the sources of demand
gains due to increased marketing investments in Direct-to-Consumer Advertising
(DTCA), detailing, and Meetings and Events (M&E). We then propose an
alternative choice model specification that relaxes the IPS property - the
so-called "flexible substitution" logit (FSL) model. The (random coefficient)
FSL model predicts that sales gains from DTCA and M&E come primarily from the
non-drug treatment (87.4% and 70.2% respectively), whereas gains from
detailing come at the expense of competing drugs (84%). By contrast, the
random coefficient logit model predicts that gains from DTCA, M&E and
detailing all would come largely from competing drugs. |