Customer Reviews Have Become Strategic Business Data
The rapid expansion of e-commerce has fundamentally changed how consumers make purchasing decisions. Before buying products online, customers increasingly consult reviews written by other users. These reviews influence trust, reduce uncertainty, and shape perceptions about product quality.
Businesses have also recognized the growing value of this information. Instead of treating reviews as simple feedback, companies now use them as a rich source of consumer intelligence. Advances in AI allow businesses to extract insights from written comments, helping them understand customer emotions, preferences, expectations, and purchasing intentions.
According to the authors, research has evolved beyond measuring numerical ratings. Modern studies increasingly focus on understanding consumer preferences through sophisticated analysis of review content, reflecting a broader shift in digital commerce and customer analytics.
Mapping Two Decades of Global Research
Rather than conducting experiments with consumers, the researchers performed a bibliometric analysis, a method used to examine scientific publications and identify research trends.
The study analyzed 108 Scopus-indexed publications published between 2005 and 2025. The articles were identified through systematic screening using the keywords "Customer Review" and "preference." After selecting eligible English-language publications, the researchers mapped scientific collaboration, keyword relationships, and thematic development using VOSviewer, a visualization tool commonly employed in bibliometric research.
This approach allowed the authors to examine how research on customer reviews has evolved internationally and which topics are becoming increasingly important.
Research on Customer Reviews Is Growing Rapidly
One of the study's most significant findings is the dramatic increase in scientific publications after 2020.
The researchers found that:
- Research output remained relatively limited between 2005 and 2015.
- Publication volume increased steadily after 2016.
- Growth accelerated significantly following 2020, coinciding with rapid expansion of e-commerce platforms and advances in AI technologies.
- The highest publication levels were recorded during 2024–2025, indicating that customer review analysis has become a major international research topic.
The authors attribute this growth to increasing interest in applying machine learning, sentiment analysis, recommendation systems, and big data analytics to better understand consumer behavior.
Six Major Research Themes Define the Field
Using keyword network analysis, the researchers identified six dominant research clusters shaping customer review studies worldwide:
- Customer-Centric Product Design and Preference Modelling, where reviews guide product development based on customer needs.
- E-Commerce Customer Review Analytics and Performance Evaluation, focusing on service quality and platform performance.
- Sentiment Analysis and Personalization, using AI to interpret customer emotions and generate personalized recommendations.
- AI-Driven Recommendation Systems, applying machine learning to improve product suggestions.
- Consumer Decision-Making and Online Purchasing Behavior, examining how reviews influence buying decisions.
- Machine Learning and Text Mining for Customer Satisfaction, using automated analysis to measure customer experiences from review data.
Together, these themes illustrate the transition from evaluating customer ratings to predicting customer preferences through intelligent data analysis.
Artificial Intelligence Dominates Current Research
The bibliometric review also reveals that Computer Science accounts for the largest share of publications, followed by Engineering, Business and Management, Mathematics, and Decision Sciences. This interdisciplinary distribution demonstrates that customer review research now combines expertise from technology, behavioral science, business, and data analytics.
Geographically, India emerged as the leading contributor to publications in this field, followed by China and the United States. Among research institutions, The Hong Kong Polytechnic University recorded the highest publication output, highlighting Asia's growing leadership in AI-driven customer analytics.
Why These Findings Matter
The findings suggest that online customer reviews have become far more valuable than simple product ratings.
Businesses can use AI-powered review analysis to:
- Improve recommendation systems.
- Identify customer expectations more accurately.
- Personalize shopping experiences.
- Detect emerging market trends.
- Enhance product development and customer service.
The study also highlights opportunities for policymakers, educators, and technology developers. As digital commerce continues expanding, advanced review analytics may strengthen national digital economies while supporting more data-driven business decision-making.
The authors further recommend expanding future research in developing countries, including Indonesia, where consumer behavior may differ from patterns observed in existing international literature. Integrating data from marketplaces, social media platforms, online communities, images, and videos could produce more comprehensive consumer preference models.
Academic Perspective
According to Fikri Kurniawan, Agung Utama, and Tony Wijaya of Yogyakarta State University, customer review research has entered a new phase in which artificial intelligence, machine learning, natural language processing, and big data transform customer reviews into strategic information for understanding consumer preferences, emotions, and purchasing decisions. Their bibliometric analysis demonstrates that scholarly attention is shifting from simple numerical ratings toward predictive, AI-powered consumer preference modelling.
Author Profiles
Fikri Kurniawan is a researcher in the Master of Management Program, Yogyakarta State University (Universitas Negeri Yogyakarta), Indonesia, whose research interests include digital marketing, consumer behavior, bibliometric analysis, and artificial intelligence applications in business.
Agung Utama is an academic at the Master of Management Program, Yogyakarta State University, specializing in management, marketing, and business research.
Tony Wijaya is a professor and researcher at Yogyakarta State University whose expertise includes marketing management, consumer behavior, business analytics, and quantitative research methods. The uploaded journal article identifies the authors and their affiliation but does not provide their complete academic degrees; therefore, only information supported by the article is presented.
Source
Kurniawan, F., Utama, A., & Wijaya, T. (2026). From Ratings to Consumer Preferences: A Bibliometric Review of Customer Review Research in the Digital Age. Formosa Journal of Multidisciplinary Research, Vol. 5, No. 7, pp. 2051–2066.
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