In a world of information chaos, the idea of consensus has intuitive appeal. Online ratings and reviews provide us with conclusions that feel certain. That feel real. Online reviews are like a shrewd companion we can rely on to nudge us here and away from there on our online journeys. They have become so ubiquitous that we expect them to be present and are a bit discombobulated when they aren’t. From food to tech to clothes to movies to music to books, there are very few consumer spaces where online reviews don’t play a central role.
And for e-commerce—an industry that was worth approximately $6 trillion (US) globally in 2022—they have become essential. There is a vast and growing industry, what I call the opinion economy, that leverages our belief in the value of the (allegedly) authentic views of others and that increasingly shapes not only our purchasing behaviour but also our tastes and expressions of personal identity. The opinion economy is built on our desire for a beacon of clarity and certainty in our fantastically chaotic information ecosystem. It stands as one of the best examples of a certainty illusion. It also serves to illustrate how our best hopes for the internet—the frictionless and free exchange of authentic ideas and opinions—can be exploited, distorted, and monetized, all with very little recognition or care that it is happening.
Over 70 percent of consumers, one industry survey found, won’t pull the trigger on a purchase unless they’ve read online consumer reviews. We assume ratings, raves, and rants will be there to guide us through the noise. So many of our day-to-day decisions are shaped by them. Online reviews exist for almost every product, service, and human experience.
A 2021 survey of 6,000 online consumers found “ratings and reviews have become the most important factor impacting online purchase decisions.” In fact, survey participants placed the value of online reviews above price, free shipping, brand, and recommendations from family and friends. The survey found 94 percent of customers ranked it as the single most important factor, and four out of five said they won’t shop on a website unless it has customer reviews.
A 2023 study published in the journal Nature found that “the most important attribute for consumers in selecting an online shopping service is star rating.” And studies have consistently found that over 90 percent of consumers use online reviews before making a purchase, and 88 percent say they trust reviews as much as or more than personal recommendations.
The problem is that many online reviews are straight-up fake.
And by fake, I mean not written by a true customer. They were either purchased, generated by an AI-powered bot, or written by someone with an ulterior motive, such as wanting to sell stuff or, at the other end of the motivation spectrum, trying to hurt a business, product, or service.
Estimates on the frequency of fakes vary greatly. A 2019 analysis that used an online detection tool called Fakespot concluded that, on average, 39 percent of product reviews are unreliable, with posts about apparel (46.2 percent), home decor (45.6 percent), and electronics (42 percent) being particularly bad. Others have suggested the number may be even higher. A 2022 industry analysis suggested that 61 percent of reviews about electronics “have been deemed fake.”
Saoud Khalifah, the CEO of Fakespot, tells me that their team estimates “about 30 percent of the reviews on Amazon are unreliable to consumers.” While there is variation between platforms, and certain categories of products fare better or worse, “no platform has zero fake reviews,” Khalifah says. “It is basically a wild west of misinformation.”
Other experts I talked with suggest the range of verifiable fakes is lower, around 15 percent. But they all quickly qualified that assessment with the caveat that it has become increasingly difficult to identify fakes. In other words, it is very likely there are more fakes than we all, including the experts, realize.
The degree to which the average star rating is boosted by fake reviews can be startling. A 2019 analysis by The Hustle found that for some products, such as electronics, untrustworthy reviews boost ratings by anywhere from 0.5 to almost a full star. For headphones, for example, the average trustworthy rating was 3.99 stars, but when you add the fake reviews, it rises to 4.89. Again, this analysis assumes that they can tell when a review is untrustworthy, and they probably often can’t. That means the gap in the average star rating between only the real reviews and all reviews is likely even larger.
The incentive for companies to generate positive reviews is intense. On a global level, trillions of dollars are in play. Almost the entire consumer economy has a horse in this race. Good reviews translate into profits. Alas, studies have consistently shown that generating fake or “incentivized” positive reviews works. An analysis by the World Economic Forum estimates that fake online reviews influence the $791 billion (US) of online spending that happens per year in the US alone and directly impact about $152 billion (US) in spending.
The other way that fake reviews help companies is by increasing their search rankings. This is critical to improving the awareness and visibility of a product or service. Google explicitly states that online reviews impact its approach to rankings. Good reviews might mean the difference between being on the first page of search results and on the second or third page. The first page sucks up about 95 percent of web traffic. (As the joke goes, what’s the best place to hide a dead body? The second page of a Google search.) The financial incentive to get on page one is extreme. Once you realize your competitors are likely doing the same thing, you might find yourself in a review-manipulation arms race.
Research by Sherry He, a PhD candidate at the Anderson School of Management, University of California, Los Angeles, shines a light on the massive but illusive fake-review industry. She has investigated the use of Facebook to recruit individuals to write fake reviews for products sold on Amazon. Suffice to say, she found a lot of recruiting. “We estimate there are 4.8 million [recruitment] posts in a year,” she tells me when I ask about the scope of the problem. “And we only observed Facebook groups, which is a semi-public channel. We cannot speak of private fake-review recruiting channels.”
It often works like this: a person is recruited to post a fake review and is paid usually in the amount of the cost of the product being reviewed. Some companies also give reviewers a small commission—once they provide a screenshot of a realistic-looking five-star review. To avoid detection by platform algorithms designed to identify and remove fakes, the recruits are told to search for and buy the products themselves.
This means Amazon, for example, notes their purchase as a verified one, and their review looks as authentic and organic as possible. Not only do fake reviews lead to a significant increase in average ratings and sales rank by inflating the number of high reviews but they can also influence how legitimate reviewers rate a product or service.
The anchoring effect is a cognitive bias that can influence how we value things. Say you have a mediocre meal at a local restaurant after seeing that the restaurant’s average online score is 4.8 out of 5 stars (perhaps inflated by fake reviews). That is your starting reference point. The anchor. In that context, you might feel like your relatively run-of-the-mill experience deserves a four-star rating. That is almost a full star below the restaurant’s average, after all, but four stars isn’t all that bad, right? Even if your rating pulls their overall score down, the score will probably still be higher than 4.5.
But if the anchor is, say, 3.5 stars, you may feel like a rating of three stars better reflects your experience. After all, your experience was unexceptional. Thus, to ensure a higher anchor score, businesses may feel compelled to get a bunch of five-star raves up on the scoreboard. The research shows that the anchoring effect works: fake and manipulated reviews have an impact on both review judgments and purchasing behaviour.
Of course, government regulators around the world are familiar with these kinds of shenanigans and have taken steps to respond.
In April 2022, for instance, the UK took regulatory steps to make it illegal to write or post fake reviews. The US Federal Trade Commission is also not a big fan of fake and manipulated reviews. In February 2022, it commenced lawsuits against two companies that are major fake-review brokers. The companies coordinate and profit from the posting of fake customer reviews on platforms such as Amazon, eBay, Walmart, and Etsy. The FTC has also taken action against companies that have suppressed negative reviews or instructed employees to write authentic-looking positive reviews for the products they sell.
While this kind of legal action is certainly needed and welcome, the gargantuan scale of the problem—and the billions of dollars in play—makes such moves seem, if not totally futile, little more than symbolic. “It is very hard to police everyone, and the fake reviewers are getting better and better,” Davide Proserpio tells me. And by “better and better,” he means the fakers know how to ensure that the reviews look more and more authentic, thus making it difficult for either you or me or anyone, including a platform’s algorithms or academic experts, to ferret them out. “The number of fake reviews is increasing all the time,” Proserpio says. “This is going to be a very hard problem to solve. It is going to take a long time.”
Curtis Boyd, a data scientist and the head of the Transparency Company, an initiative with the explicit goal of stopping the spread of fake reviews, tells me the same thing. “Selling fake reviews is a multi-billion-dollar business. Almost every industry is affected by it,” he says. “Doctors, lawyers, preschools, everything.” And like Proserpio, Boyd is not optimistic regulators can have a meaningful impact; the incentives to create and use fake reviews are too formidable. And he also agrees that the fakers are “getting better and better at making them look real.”
Because fake reviews help everyone profit along the marketing food chain, there is little incentive to take meaningful action to remove the unreliable noise, says Boyd. He calls this the fake-review cycle. It works like this: a business (a restaurant, shoe store, law office, toy manufacturer, etc.) purchases fake reviews, which result in that business selling more products or services. This, in turn, makes more money available for marketing, and often the business spends it on the platform hosting their fake reviews because it is likely where the increased sales are coming from.
As a result, fake reviews become profitable for the platforms hosting them, the advertisers, the businesses creating them, and often the individuals writing them—but not you and me, the real customers. In the end, as noted in a 2021 article by Boyd in which he maps out this vicious cycle, “turning a partial blind eye to review fraud generates a win-win for big tech and their advertisers. Consumers are getting the short straw.”
Platforms like Google, which is the biggest source of online reviews, say they remove millions of fake posts every year. Boyd tells me his research team estimates that Google removes about 180,000 bogus reviews a day, which gives you a sense of the extent of the problem. But despite that impressive number, Boyd doesn’t think it is making a dent. “That’s just the tip of the iceberg.”
Excerpted from The Certainty Illusion: What You Don’t Know and Why It Matters by Timothy Caulfield. Copyright © 2025 Timothy Caulfield. Published by Allen Lane/Penguin Canada, a division of Penguin Random House Canada Limited. Reproduced by arrangement with the publisher. All rights reserved.
