  Structured interviews are used in many settings, importantly in market
research on topics such as brand perception, customer habits, or preferences,
which are critical to product development, marketing, and e-commerce at large.
Such interviews generally consist of a series of questions that are asked to a
participant. These interviews are typically conducted by skilled interviewers,
who interpret the responses from the participants and can adapt the interview
accordingly. Using automated conversational agents to conduct such interviews
would enable reaching a much larger and potentially more diverse group of
participants than currently possible. However, the technical challenges
involved in building such a conversational system are relatively unexplored. To
learn more about these challenges, we convert a market research multiple-choice
questionnaire to a conversational format and conduct a user study. We address
the key task of conducting structured interviews, namely interpreting the
participant's response, for example, by matching it to one or more predefined
options. Our findings can be applied to improve response interpretation for the
information elicitation phase of conversational recommender systems.
