- 31/01/2025
- Category: Commentaries
Author: Hilman Nurjaman
Editor: Ayom Mratita Purbandanii
Fake reviews are becoming one of the most pressing problems in today’s digital world, particularly in the e-commerce industry.[1] In everyday practice, many online reviews are fabricated, with cases like Amazon’s fake review networks highlighting the issue.[2] This problem also exists in Indonesia, where platforms like Google Maps have taken action by warning businesses that engage in fake review practices.[3] Online product reviews are a cornerstone of consumer decision-making, helping people determine whether a product is worth buying.[4] But when fake reviews enter the picture, the trustworthiness of platforms and businesses is compromised, leading to concerns over transparency. In Indonesia, for example, some companies have been caught using fake accounts to artificially inflate their product ratings. It highlights the importance of taking fake reviews seriously and developing strategies to combat them.
From distrust to unfair competition
A market survey conducted by Dixa in 2022 found that 93% of consumers read online reviews before deciding to purchase a product.[5] Similarly, 82% of consumers read online reviews as part of their information-gathering process, with an average of 10 reviews read before deciding whether to trust a product or not.[6]
The problem with fake reviews, however, runs much deeper than just damaging brand reputations. Fake reviews—whether generated by bots, incentivized by payments, or based on fabricated orders—manipulate perceptions of products and services. They mess with the efficiency of online trade, distort fair competition, and chip away at consumer trust—not just in the e-commerce industry but across all digital platforms.[7] When fake reviews flood these spaces, it becomes harder for customers to distinguish the genuine feedback from the fabricated ones, making online shopping feel less reliable. This has become especially evident on some platforms, where even genuine and trustworthy reviews are met with growing skepticism.
Moreover, fake reviews create unfair competition in the marketplace. Less competitive businesses often use them as a shortcut to boost their image, while higher-quality competitors often suffer from targeted negative reviews.[8] This manipulation threatens the fairness of the e-commerce ecosystem, which is supposed to reward businesses based on authentic reputations. Unfortunately, this erosion of trust is particularly damaging to first-time buyers, who rely heavily on reviews, lose trust in online platforms.
Why people create fake reviews
The reasons behind fake reviews are as varied as the people and companies that write them. For ‘consumers’, the motivation is often simple: incentives. Many write fake reviews in exchange for freebies, discounts, or other perks offered by brands.[9] A well-known example is the case of Sunday Riley, a skincare brand that was caught instructing employees to write fake positive reviews on Sephora’s website to boost sales and counteract negative feedback.[10] Others see it as a way to exert influence, feeling a sense of power by manipulating how products are perceived. There’s also a social angle—people may write fake reviews to fit in or strengthen their ties within online communities where experiences with products and services are frequently shared.[11]
Fake reviews are just the surface of a bigger issue. E-commerce platforms like Shopee and Tokopedia favor top sellers, making it tough for new or smaller businesses to get noticed.[12] The more sales a product has, the more visibility it gets, creating a cycle where big players keep winning while newcomers struggle. This imbalance pushes some sellers to rely on fake reviews just to stay in the game.
Thus, for businesses, the motivations are more strategic. Positive fake reviews are a quick and unethical way to boost the image of their products or services. On the flip side, negative fake reviews are used to sabotage competitors, damaging their reputation and swaying consumer opinion.[13] These practices are all too common on e-commerce platforms, where companies have been caught creating fake accounts to undermine rival products and manipulate public perception.
Certain products are especially vulnerable to fake reviews, particularly high-engagement items like baby products, beauty, health, and fashion.[14] These products are often expensive, complex, and carry higher risks for buyers, making reviews play a huge role in decision-making. In this context, how a review is written can make all the difference—detailed, experience-based reviews tend to be much more persuasive than vague or generic ones.
Interestingly, studies show that star ratings alone don’t always influence purchasing decisions as much as the actual content of reviews. Consumers are more likely to be swayed by written feedback than by a numerical score.[15] This is why businesses are encouraged to focus on genuine, meaningful feedback rather than simply chasing higher ratings—because, ultimately, it’s the details that truly matter to potential buyers.
How to spot and prevent fake reviews
Detecting fake reviews is challenging, but it can be done with the right strategies. Both businesses and individual consumers play a role in addressing this issue.
For businesses, the process often involves using analytical tools to detect suspicious patterns. Content analysis can help flag reviews that use overly glowing or excessively critical language, lack specific details, or are posted at oddly consistent intervals.[16] Similarly, behavioral analysis can identify unusual activity, such as reviewers who post too frequently or seem to fixate on certain products.
Another effective method involves looking at the relationships between reviewers and sellers. Research has shown that inauthentic interactions—like coordinated fake reviews—often follow detectable patterns. Artificial intelligence (AI) is particularly powerful in this area.[17] AI-based tools, like language analysis algorithms, can scan for patterns in tone, sentiment, and content that suggest fraud. For example, AI can pinpoint fake reviews by spotting overly generic phrasing or unusually repetitive language.
While consumers can take steps to protect themselves from fake reviews by reading critically and spotting red flags—like vague language, overly enthusiastic praise, or inconsistent details—this shouldn’t be their burden alone. It’s also crucial for governments and online platforms to step up by enforcing stricter policies to detect and remove fraudulent reviews. A fair and transparent marketplace isn’t just the responsibility of individual shoppers; it requires collective action to ensure trust and authenticity in online spaces.
Conclusion
Fake reviews pose a significant challenge to the health of the e-commerce world, by undermining trust, distorting fair competition, and making online shopping less reliable for everyone. To tackle this issue, it’s essential to understand why fake reviews happen and use smart strategies to detect and prevent them.
Looking ahead, AI will likely play a big role in identifying fake reviews by analyzing patterns in language, sentiment, and reviewer behavior. However, technology alone isn’t enough. Educating consumers to spot and avoid fake reviews is just as important. By combining cutting-edge tech with informed and critical consumers, we can build a more transparent, reliable, and fair digital marketplace for everyone.
[1] Pan, Y. and Xu, L. (2024) ‘Detecting Fake Online Reviews: An Unsupervised Detection Method With a Novel Performance Evaluation’, International Journal of Electronic Commerce, 28(1), pp. 84–107. doi: 10.1080/10864415.2023.2295067.
[2] Trumbull, R. (2024) ‘An ethicist’s take on Amazon’s fake review problem’, GeekWire. geekwire.com/2024/an-ethicists-take-on-amazons-fake-review-problem/
[3] Ariyani, D. (2024) ‘Google Maps Kini Beri Peringatan untuk Bisnis dengan Review Palsu, Liputan 6. liputan6.com/tekno/read/5712905/google-maps-kini-beri-peringatan-untuk-bisnis-dengan-review-palsu?utm_source=chatgpt.com
[4] Sahut, J.M., Laroche, M. and Braune, E. (2024) ‘Antecedents and consequences of fake reviews in a marketing approach: An overview and synthesis’, Journal of Business Research, 175. doi: 10.1016/j.jbusres.2024.114572.
[5] Loiselle, M. (2022) ‘3 Statistics That Show How Customer Reviews Influence Consumers’, Dixa. dixa.com/blog/3-important-statistics-that-show-how-reviews-influence-consumers /
[6] Murphy, R. (2019) ‘Local Consumer Review Survey 2019’, Bright Local. brightlocal.com/research/local-consumer-review-survey-2019/
[7] Lim, W. M., Agarwal, R., Mishra, A. and Mehrotra, A. (2024) ‘The Rise of Fake Reviews: Toward a Marketing-Oriented Framework for Understanding Fake Reviews’, Australasian Marketing Journal, 0(0). doi: 10.1177/14413582241283505.
[8] Ibid.
[9] Rynarzewska, A. I. (2019) ‘It’s not fake, it’s biased: Insights into morality of incentivized reviewers’, Journal of Consumer Marketing, 36(3), 401–409.
[10] Elassar, A. (2019) Skin care brand Sunday Riley wrote fake Sephora reviews for almost two years, FTC says’, CNN US. edition.cnn.com/2019/10/22/us/sunday-riley-fake-reviews-trnd/index.html
[11] Talwar, S., Dhir, A., Kaur, P., Zafar, N., and Alrasheedy, M. (2019) ‘Why do people share fake news? Associations between the dark side of social media use and fake news sharing behavior’, Journal of Retailing and Consumer Services, 51, 72–82.
[12] Meilina, K. (2024) ‘Sisi Gelap E-Commerce: Modus Pengembalian Barang dan Ulasan Palsu’, Katadata. /katadata.co.id/digital/e-commerce/6773b7e7815f4/sisi-gelap-e-commerce-modus-pengembalian-barang-dan-ulasan-palsu
[13] Lim, W. M., Agarwal, R., Mishra, A. and Mehrotra, A. (2024) ‘The Rise of Fake Reviews: Toward a Marketing-Oriented Framework for Understanding Fake Reviews’, Australasian Marketing Journal, 0(0). doi: 10.1177/14413582241283505.
[14] Kumar, R., Mukherjee, S. and Rana, N.P. (2024) ‘Exploring Latent Characteristics of Fake Reviews and Their Intermediary Role in Persuading Buying Decisions’, Inf Syst Front 26, 1091–1108. doi: 1007/s10796-023-10401-w.
[15] Ibid.
[16] Barbado, R., Araque, O. and Iglesia, C. A. (2019) ‘A framework for fake review detection in online consumer electronics retailers’, Information Processing & Management, 56(4), 1234-1244.
[17] Evans A. M., Stavrova O., and Rosenbusch H. (2021) ‘Expressions of doubt and trust in online user reviews’, Computers in Human Behavior, 114, 106556.
