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The most successful brands in this area are mostly "local champions'' that achieve high numeric distribution and extensive penetration in traditional trade.
In traditional trade, it is typically more important to master the route to market to maximize numeric distribution, working with distribution partners and wholesalers to improve availability and visibility.
For variables with numeric distribution, the data are presented as mean (confidence interval) ± standard deviation and median (minimum maximum).
Comparisons between the CG and CFG were performed with the Mann–Whitney test for variables with a numeric distribution, and calculations of differences in categorical variables between the CG and CFG were performed with the χ test.
The mean centre and standard distance for each population (equivalents to the mean and standard deviation of a numeric distribution) were calculated, along with the mean pairwise geographical distance within each population to assess the degree of clustering (Additional file 1, Table S5).
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We used non-parametric methods to analyse numeric distributions in order to have a consistent approach to analysing these data which included skewed distributions.
We summarized numeric distributions graphically by showing individual values superimposed over a box indicating the sample median and quartiles (i.e. the 25th, 50th and 75th percentiles).
These include: frequency distribution, numeric statistical analysis, target volume, and word count (a list of up to 100 of the most often used words).
Numeric parameters with normal distribution are presented as mean ± standard deviation (SD) and numeric parameters without normal distribution are presented as median.
Between-group differences in numeric parameters with normal distribution were analyzed using the independent samples t test, and between-group differences in numeric parameters without normal distribution were analyzed using the Mann–Whitney U test.
The Wilcoxon Rank Sum test or Kruskal-Wallis test was used to compare the distribution of numeric variables between groups.
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