Aquaculture America 2024

February 18 - 21, 2024

San Antonio, Texas

CHARACTERISTICS OF U.S. SEAFOOD CONSUMERS: PERSPECTIVES BASED ON HOME SCANNER DATA

Lianqun Sun* and Ganesh Kumar

Delta Research and Extension Center, Thad Cochran National Warmwater Aquaculture Center, Mississippi State University, Stoneville, Mississippi-38776 USA

 



This study utilized AC Nielsen Home Scanner data to analyze consumer characteristics and their impact on seafood consumption in the United States. Weekly data spanning from January 2019 to June 2021 (130 weeks), encompasses purchasing information from 1,635 retail outlets, detailing over 7,500 UPC codes and 8000 different brands of seafood products. The demographic analysis of the data reveals insightful trends and patterns in seafood consumption across various household types. Sixty-six percent of the household consumers identified themselves as Caucasians, 19% as African American, 9% as Asian, and 6% represented other races. The majority (63%) of seafood-consuming households were married couples, while single female consumers account for 16%, and single male consumers for 6% (see Figure 1). Income distribution shows a concentration in the middle-income quintile, with more than half of the households earning around $81,800 in 2019. Within this group, 31% have incomes of $100,000 and above, while 23% earn between $70,000 and $99,999. Household size also plays a significant role, with 45% of households comprising two members and 22% with single individuals. Only 7% of households have children aged 13 to 17 years. Additionally, the educational background of the male household head is predominantly at least some college degree, with 26% having attended grade school and 24% holding post-graduate degrees. Interestingly, the female head age distribution showed an equal percentage of individuals aged 55-64 and those under 25. The data also suggested that high-income neighborhoods with predominantly Caucasians, married households with fewer children are prime targets for seafood consumption. This information is vital for targeted marketing strategies, potentially enhancing seafood sales in various cities. Further analysis using mixed logit models is proposed to estimate the impacts of consumer characteristics on seafood consumption more accurately. Such models will enable a deeper understanding of the factors driving seafood purchase decisions, providing a strategic edge to seafood marketers and industry stakeholders. This comprehensive approach to consumer analysis offers a path to optimizing marketing efforts and expanding seafood consumption across diverse demographic groups.