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Scholastic Case Reports
(ISSN: 3108-1827)



Conceptual Paper
Volume 2 Issue 3 March 2026

The Mindsets of Amazon Shoppers: A Mind Genomics and AI-Based Behavioral Backgrounder

Dipak Paul1, Howard Moskowitz1,2*, Sharon Wingert2, David Stevens3

1Mind Genomics Associates Inc., White Plains, New York, USA
2Tactical Data Group, Stafford, Virginia, USA
3Advanced Learning Strategies, Silver Lake, New Hampshire, USA

Corresponding Author: Howard Moskowitz, Mind Genomics Associates Inc., White Plains, New York, USA & Tactical Data Group, Stafford, Virginia, USA

Received: March 12, 2026; Published: March 24, 2026



Abstract

Objective: To explore, using an AI-assisted Mind Genomics framework, the psychological patterns that may shape how consumers make decisions while shopping on Amazon.
Materials and Methods: A unified set of 16 elements was developed to represent the Amazon shopping journey, including motivations for visiting the platform, product selection cues, checkout triggers, and loyalty drivers. Three hundred synthetic respondents were generated using artificial intelligence. Each simulated respondent evaluated 24 experimentally designed vignettes. Ordinary least squares regression was used to estimate element-level coefficients, and k-means clustering was applied to identify distinct mindsets.
Results: The strongest-performing elements in the total panel were price-drop alerts, guarantees against fake reviews, and transparent price comparisons. Three mindsets emerged: Efficiency Maximizers, who value speed and convenience; Trust and Relationship Seekers, who prioritize authenticity and reassurance; and Autonomy and Control Drivers, who prefer customization and control.
Discussion: The findings suggest that Amazon shoppers may differ systematically in the psychological priorities that guide their decisions. These differences may help explain why certain interface features resonate more strongly with some shoppers than with others.
Conclusion: This backgrounder illustrates how Mind Genomics and artificial intelligence may be used to uncover meaningful consumer segments and generate actionable insights for improving personalization, trust, and the overall online shopping experience.
Keywords: Mind Genomics; Artificial Intelligence; Consumer Behavior; Amazon Shopping; Behavioral Segmentation; E-commerce Personalization; Digital Decision-Making.

References

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  4. The Psychology of Amazon Shoppers: Behavior, Trust & Conversion. AMZ-DOC. 2025 Nov 6.
  5. Gigerenzer G. Gut Feelings: The Intelligence of the Unconscious. New York, NY: Penguin Books; 2007.
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  7. Tversky A, Kahneman D(1974). Judgment under uncertainty: Heuristics and biases. 185(4157): 1124-1131.
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  9. Ariely D (2008). Predictably Irrational: The Hidden Forces That Shape Our Decisions. New York, NY: HarperCollins Publishers.
  10. Gofman A, Moskowitz H (2010). Isomorphic permuted experimental designs and their application in conjoint analysis. J Sens Stud. 25(1): 127-145.
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Citation: Howard Moskowitz., et al. “The Mindsets of Amazon Shoppers: A Mind Genomics and AI-Based Behavioral Backgrounder”. Scholastic Case Reports 2.3 (2026): 01-08.

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