Characterization of the indecisiveness class of the customer through a hierarchical representation of his path in the selling area
Résumé
It has been shown that indecisiveness is involved in many
unwanted cognitive states, such as procrastination, distractibility,
the lack of self-esteem, or even revenge. The purpose of this work
is to propose a predictive model for the recognition of the
indecisiveness class, from the analysis of the customer’s
trajectory and his gripping. The movements are captured thanks
to infra-red sensors. A structural behavioral architecture is built,
based on eye-tracking methodology. Indeed, all the movements of
a customer in a selling area can be assimilated to fixations and
saccades. We show that the path in the selling area can be seen as
a sequence of states. The final predictive classifier is built with a
combination of Hidden Markov Models (HMM) through a
logistic regression model (LRM) and leads to satisfying results, as
it correctly predicts 88 % of the subjects’ indecisiveness classes.