  Visual representation of data like charts and tables can be challenging to
understand for readers. Previous work showed that combining visualisations with
text can improve the communication of insights in static contexts, but little
is known about interactive ones. In this work we present an NLG chatbot that
processes natural language queries and provides insights through a combination
of charts and text. We apply it to nutrition, a domain communication quality is
critical. Through crowd-sourced evaluation we compare the informativeness of
our chatbot against traditional, static diet-apps. We find that the
conversational context significantly improved users' understanding of dietary
data in various tasks, and that users considered the chatbot as more useful and
quick to use than traditional apps.
