  The main objective of the M5 competition, which focused on forecasting the
hierarchical unit sales of Walmart, was to evaluate the accuracy and
uncertainty of forecasting methods in the field in order to identify best
practices and highlight their practical implications. However, whether the
findings of the M5 competition can be generalized and exploited by retail firms
to better support their decisions and operation depends on the extent to which
the M5 data is sufficiently similar to unit sales data of retailers that
operate in different regions, sell different types of products, and consider
different marketing strategies. To answer this question, we analyze the
characteristics of the M5 time series and compare them with those of two
grocery retailers, namely Corporaci\'on Favorita and a major Greek supermarket
chain, using feature spaces. Our results suggest that there are only small
discrepancies between the examined data sets, supporting the representativeness
of the M5 data.
