“Where everybody knows your name”: How regulars at farmers' markets differ from less-frequent shoppers

Abstract

A survey of consumers at three farmers' markets (FMs) was done near Vancouver, British Columbia. The markets span urban and suburb locales, and the survey's 234 respondents were asked questions about shopping behavior, attitudes toward FMs, and demographic information. The focus of the analysis is on the differences between regulars and non-regulars to the market, where a regular is considered a shopper who shops weekly or bi-weekly. The results show that regulars spend more ($46.36 vs. 33.19 for non-regulars), are much more likely to expect higher prices compared to grocery stores than non-regulars, and buy more products (4.15 vs. 3.1). Regulars also value attributes of FMs differently: they value variety, organic products, and being locally-grown more highly. Organic purchasing behavior is also significantly different with regulars much more likely to say they “always” or “usually” buy organic products. As this is the first study to explicitly analyze regulars at FMs, suggested research directions and methods are offered to help guide future research.

Increasing customer purchases at farmers markets using point‐of‐sale scanner data

“…The literature using aggregate measures of performance consistently points to the importance of product variety to support customer purchases (e.g., Eastwood et al, 1999; Stobbe, 2023) and farm sales (e.g., Feenstra et al, 2003; Schmit & Gómez, 2011; Stephenson et al, 2008). However, no statistically significant effects on CTS are found for Item counts besides the level ItemDairy term (Table 3).…”

“…Based on the literature using more aggregate data (e.g., Brown & Miller, 2008; Hamilton, 2018; McGarry‐Wolf et al, 2005; Quick et al, 2022; Schmit, Severson, et al, 2019; Stobbe, 2023) we expect per capita income ( IncomePC ), racial diversity ( Pcnt_NonW ), and child dependency ( CDR ) will have positive effects, while poverty rate ( Pcnt_BPov ) and Nonmetro will be negative.…”

“…A significant body of FM research evaluating farm vendor performance uses annual farm financial data (e.g., Jablonski et al, 2022; Park et al, 2018; Schmit, Jablonski, et al, 2019), farm survey data (e.g., Feenstra et al, 2003; Govindasamy et al, 2003; Schmit & Gómez, 2011; Varner & Otto, 2008) and customer survey data (e.g., Eastwood et al, 1999; Quick et al, 2022; Schmit, Severson, et al, 2019; Stobbe, 2023) to inform marketing efforts. The studies include annual measures of farm revenue, daily sales and customer counts, or average customer purchase levels across vendors and shopping frequency to gauge farm/FM performance.…”