Efficacy of Appetite-Based Segmentation

Traditional segmentation approaches—demographics, psychographics, and behavioral variables—often fail to predict consumer behavior effectively. Building on Geraldine Fennell’s work, this project develops and tests a segmentation approach based on experience appetites, defined by consumers’ perceptions of the product-use situation. 

This study evaluates whether appetite-based segmentation provides stronger explanatory and predictive power than conventional segmentation methods.

Fennell’s framework proposes:

• Markets consist of occasions, not just people 
• Consumer choice is driven by perceived product-use situations 
• These perceptions generate appetites that guide behavior 

This project operationalizes that idea by:

• Measuring consumer appetites 
• Creating segmentation schemes based on those appetites 
• Testing their effectiveness

This research directly addresses a central question:

Do alternative segmentation approaches actually perform better?
 

It contributes by:

• Providing a testable methodology for appetite-based segmentation 
• Demonstrating how different segmentation approaches yield different insights 
• Offering a practical framework for applying Fennell’s theory

The study develops a structured methodology:

• Identify attributes that define a consumption experience (26 items) 
• Measure importance of those attributes 
• Use factor analysis to identify appetite dimensions 
• Create segments using: 
  • Most-important-factor method 
  • Cluster analysis 

This results in multiple segmentation schemata for comparison. 

Different segmentation approaches produce different types of insight:

• Simple segmentation (most important appetite)
  → Clear, intuitive segments 
• Cluster-based segmentation
  → More nuanced understanding of consumer motivations 

Most importantly:

Appetite-based segmentation reveals meaningful differences in consumer priorities that traditional variables often miss.

• Conference presentation (AMTP 2025) 
• Data collection across multiple samples 
• Factor analysis identifying appetite dimensions 
• Two segmentation approaches (factor-based and cluster-based) 
• Initial comparative analysis of segmentation efficacy 

This project is highly suitable for journal development through:

• Formal statistical comparison with demographic segmentation 
• Predictive validation using behavioral outcomes 
• Extension to other industries beyond tourism 
• Refinement of appetite measurement scales

• Do appetite-based segments predict behavior better than demographics? 
• Which segmentation method (factor vs. cluster) is more effective? 
• How stable are appetite segments across contexts? 
• Can appetite-based segmentation improve targeting and positioning?

This project is particularly well-suited for:

Assistant Professors
Seeking empirical, publishable segmentation research

Doctoral Students
Interested in methodology, segmentation, or quantitative analysis

Researchers in:
Marketing strategy, segmentation, tourism, consumer behavior

Extended abstract, slides, conceptual framework, and project notes are available upon request.

Request project materials or start a conversation to explore:

• Independent development 
• Collaboration 
• Data collection support or funding

Most projects can be developed into conference submissions or journal articles with appropriate empirical testing.