ABSTRACT
As effects of pandemic COVID-19 emerge and become present in the retail, branding, and general marketing arena nowadays, it is evident and imperative to look for new veins of effective decision taking over the pitfalls of Pandemics. While customer purchasing and consumption habits change (in-home behavior), firms confront a shortage of physical attendants on “brick and mortar” stores and significantly increase digital commercial transactions. Big Data may be part of the solution for facing this new business landscape. As data is more and more available about consumer behavior, branding, and distribution channels, descriptive, predictive, and prescriptive analytics may support and improve decision-making in these areas mentioned above. This chapter exemplifies this using two real-world cases: one based on segmenting industrial clients, operating in a web-based sales platform, and the second, explaining a model for preventing stock-out from shelves. As cases demonstrate, the use of data collected by firms may represent a valid, helpful platform for new insights in decision making to cope effectively with the pandemic COVID-19 environment.
