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The 3 types of melon consumers

Wed, Apr 14th, 2021, created by Ariana Torres

The average American eats almost 9 pounds of cantaloupe and 2 pounds of honeydew each year (Agricultural Marketing Resource Center, 2018). An increased melon consumption is mainly explained by consumer awareness of melon health benefits, year-round availability, creative marketing strategies, and improved cultivars. To address these economic opportunities, retailers, growers, and other industry stakeholders should have a clear understanding of the different market segments of melon consumers, and how individuals in these segments value diverse attributes of melons. This information can help industry stakeholders introduce new cultivars, increase melon sales and consumption, and convey key attributes and benefits to consumers.

This publication uses data from a study published by researchers from Purdue University and Michigan State University titled Characterizing the U.S. Melon Market (Torres et al., 2020). Using a cluster analysis, the study reported on 3 melon consumer segments and profiled those groups to help academics, farmers, and retailers better serve consumers.

The 3 segments of melon consumers

Americans can be comprised in 3 clusters (market segments) of melon consumers. Cluster 1 (“Local Melon Lovers”) comprised 34.6% of the sample (N=595), while Cluster 2 (“Ripe-For-The-Picking”) included 44.7% of the sample (N=354), and Cluster 3 (“Convenient shoppers”) composed 20.6% of the sample (N=769). Figure 1 illustrates the distribution of the clusters based on their consumer profile. As seen in Figure 1, the largest cluster corresponds to the “Ripe-For-The-Picking” type of consumer, followed by “Local Melon Lovers”, and lastly by “Convenient shoppers”.

Figure 1. Ripe-For-The-Picking composes the largest segment of melon consumers.

The most significant demographic variables, or those which contributed most to the differences between clusters, are listed in Figure 2. Variables like gender, number of children in the household, race, living area, and distance traveled were important in describing the differences between clusters.

Figure 2. Local Melon Lovers Tend to Be Male, Have More Children, Be Minority, and Live in Metro Areas.

Consumers in the Local Melon Lovers cluster had a lower percentage of women and Caucasian shoppers, a greater number of children, and tended to live in metropolitan areas. Consumers in Cluster 2 and 3 (Ripe-For-The-Picking and Convenient Shoppers) had very similar demographic variables: having the same amount of female participation, a greater proportion of white/Caucasian people in each cluster, fewer children, and traveled shorter distances than consumers in Cluster 1. Understanding these differences helps practitioners find the type of consumer who might belong to each group, and then target them with appropriate marketing messages.

Americans were asked about the importance they give to melons on their diets, the knowledge they have about melons, and their valuation of local or imported melons. As illustrated in Figure 3, Local Melon Lovers rated highest in all the perception variables. For example, Local Melon Lovers stated they consider melons very important in their diets (80%), that they know a lot about melons (50%), and that they prefer local than regional melons (70%), and domestic more than imported melons (60%). On the other hand, Convenient Shoppers rated lowest in all perception variables, they also were the ones who reported knowing the least about melons and having low interest in local melons. Finally, Ripe-For-The-Picking consumers placed their beliefs in between Melon Lovers and Convenient Shoppers. For example, 60% of Ripe-For-The-Picking consumers believed melons are important for their diet, similarly, 40% believed local melons are better than regional melons and 30% believed that melons grown in the U.S are better than imported ones.












About the Author:

Ariana Torres

Assistant Professor, Purdue University


Ariana Torres is an Assistant Professor of Horticulture and Agricultural Economics. Her program focuses on the decision-making processes of specialty crop farmers, along with the use of digital marketing technologies among industry stakeholders. Her expertise includes the economic modeling of adoption of new technologies, the development of decision-making tools for specialty crop growers, and the economic impact of growers decision-making processes. Her research provides relevant research-based information to her extension program, Horticulture Business to provide trainings and publications to farmers, business owners, Extension personnel, and policymakers.

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