Identifying market segments in beef: Breed, slaughter weight and ageing time implications

Area of Science:

• Food Science
• Consumer Behavior
• Data Science

Background:

• Understanding consumer preferences is crucial for market segmentation in the food industry.
• Previous research often overlooks group-based preferences, treating consumers as individuals.
• Identifying distinct consumer groups can lead to targeted product development and marketing strategies for beef.

Purpose of the Study:

• To develop and apply a novel method for identifying consumer groups based on beef preferences.
• To explain the factors driving these preferences within identified consumer segments.
• To analyze how beef breed, slaughter weight, and aging period influence consumer choices.

Main Methods:

• Consumer preferences were mapped into a metric space.
• A kernel-based similarity function and clustering algorithm were used to identify homogeneous consumer groups.
• Support Vector Machines (SVM) were employed to model and explain preferences within each cluster.
• The method was validated using data from consumers evaluating beef from seven Spanish breeds, two slaughter weights, and three aging periods.

Main Results:

• Two distinct consumer clusters were identified for beef acceptability and tenderness, but not for flavor.
• These clusters exhibited opposing preferences for two different Spanish beef breeds (Asturiana and Retinta).
• Consumer appreciation for aging period varied between clusters for acceptability.
• For tenderness, a preference for longer aging periods and heavier animals was observed across most consumers.

Conclusions:

• The proposed method effectively identifies distinct consumer segments for beef based on preferences.
• Consumer preferences for beef are influenced by breed, aging, and weight, with significant variation between groups.
• This approach provides valuable insights for the beef industry in developing products tailored to specific market segments.