Understanding Review Hijacking on Amazon Through Variation Listings: The ABCD's of The Bountiful Company Restricted; Files Only

Abstract

 This thesis delves into the dynamics of product variants on Amazon's Best Seller Rank (BSR) within the Vitamins, Minerals, & Supplements category, leveraging a comprehensive dataset from Keepa.com spanning 6 months from November 2023 to February 2024. It specifically examines how factors such as the number of variants, average ratings, review volumes, pricing strategies, and participation in Amazon's Fulfillment by Amazon (FBA) and Subscribe & Save programs correlate with BSR improvements, employing statistical models like OLS, LASSO, and GLS for analysis. The findings highlight that a well-curated selection of product variants significantly bolsters BSR, while also pointing to the effectiveness of Subscribe & Save and FBA participation in strengthening market presence. However, the study identifies a threshold of 8 variants beyond which additional variants no longer contribute to BSR improvement, suggesting a balance is crucial to avoid consumer choice overload.

 This thesis emphasizes the strategic manipulation of BSR through product variants by sellers, pointing to a gap in consumer awareness regarding the introduction of new variants to existing product listings. The thesis advocates for Amazon to implement clearer notifications for consumers when new variants are added, aiming to enhance transparency and support informed decision-making. This thesis not only sheds light on seller strategies in e-commerce but also brings to light the importance of safeguarding consumer interests through better marketplace regulations, contributing valuable insights into the interplay between seller tactics and consumer protection in the digital shopping realm.

Table of Contents

1 Motivation 1

Figure 1: The Bountiful Company Review Hijacking Case Evidence . . . . . . . . . . . . . . . . . . 3

2 Literature Review 6

2.1 History of Review Hijacking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

2.1.1 Defining Review Hijacking .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.2 Public Awareness and Consumer Reports Investigation . . . . . . . . . . . . . . . . . . . . . . . . 6

2.1.3 Legal Actions and Continued Concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.2 Economic Implications of Review Manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.3 Legal and Regulatory Context of Online Review Manipulation . . . . . . . . . . . . . . . . . . . 8

2.4 Marketing Impact of Deceptive Reviews . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.4.1 In-Depth Analysis of Deceptive Review Practices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.4.2 Further Research Exploring Consumer Awareness . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.4.3 Exploring Specific Cases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

2.4.4 Utilizing Advanced Techniques of Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

2.5 Brand Leverage In The World of Review Hijacking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

2.5.1 Impact on Brand Communication . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11

2.5.2 Macroeconomic Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

2.5.3 New Product Launch Strategies in the Era of Review Hijacking . . . . . . . . . . . . . . . 12

3 Institutional Details for Amazon.com 13

3.1 Connecting Variation Listings & BSR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 

3.1.1 Overview of Amazon’s Variation Listing System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

Figure 2: Example of A Product Listing Page . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14 

3.1.2 Understanding BSR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

3.1.3 BSR’s Influence on Seller Strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.1.4 Interplay Between BSR and Review Manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

3.1.5 Price Fluctuations Within BSR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .15

3.2 Impact of Search Order Ranking on Product Visibility . . . . . . . . . . . . . . . . . . . . . . . . . .16 

3.2.1 Influence of Amazon’s Search Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .16 

3.2.2 Potential Biases and Implications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17

3.3 Comparative Analysis of The Amazon Badge System . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 

3.3.1 Detailed Examination of Each Badge . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .17 

3.3.2 Analyzing the Comparative Impact . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

4 Data 18

4.1 Data Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18 

4.1.1 Data Collection Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

4.1.2 Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .19

4.2 Data Cleaning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

4.3 Descriptive Statistics & Preliminary Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

5 Empirical Model 23

5.1 Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

5.2 Thesis Results: OLS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .26

5.3 Alternative Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

5.3.1 Lasso Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .28

5.3.2 GLS Regression . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

5.4 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

5.5 Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

6 Conclusion 35 

References 37

Appendix

Figure 3: Line Graphs of Price Data for Vitamins A, B, C,& D . . . . . . . . . . . . . . . . . . . . . . . . 41

Table1:Keepa Variable Descriptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .42

Table 2: Variable Categories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 

Table 3: Regression Variables Summary Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44

Table 4: Correlation Matrix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

Figure 4: Variation ASIN Count Trend Lines by Product & Vitamin Categories . . . . . . . 48

Figure 5: Line Graph Representing Percentage of Products With Variants . . . . . . . . . . . . 50

Figure 6: Box-plot of Log(Sales Rank: Current) Divided by FBA . . . . . . . . . . . . . . . . . . . . . . 51

Table 5: OLS Specification Outputs. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52

Table 6: Linear Regression Output Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 

Table 7:Lasso Estimation Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 

Table 8: GLS Regression Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

About this Honors Thesis

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School	Emory College
Department	Economics
Degree	B.B.A.
Submission	Honors Thesis
Language	English
Research Field	Economics, General Business Administration, Marketing Economics, Commerce-Business
Keyword	Variants Review Hijacking Amazon FTC The Bountiful
Committee Chair / Thesis Advisor	Maria Arbatskaya, Emory University
Committee Members	Marina Cooley, Emory University Ellen Gough, Emory University Samiran Banerjee, Emory University

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