TMW #198 | The review economy

Oct 27, 2024

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The review economy

AI has accelerated the spread of fake online reviews, so the FTC has decided to act. Is it too late for marketers to maintain consumers’ faith in reviews and ratings?

I had an eye-opening experience as I drove down the coast of Albania earlier this year.

The roads were terrible, so oncoming drivers would play chicken with me to maintain their position in the center of the road where the most reliable tarmac was. The coastal road is basically a series of narrow hairpin turns, which required a lot of faith that drivers coming the other way wouldn’t just blindly fly around them.

But, despite the driving experience, the biggest eye-opener was what happened when I arrived in Dhermi for the night. I had a quick scan on Google Maps for local restaurants, and settled upon one with a 4.8-star rating and over 1,000 reviews. The meal was decidedly average, but I understood how the restaurant achieved its rating when at the end of the meal, the waiter asked if I enjoyed my meal, and once I said “yes” out of politeness, he offered me a tap-to-review NFC reader and hovered above me as he suggested what I could write in my review.

I learned my lesson that day not to believe everything I see when it comes to online reviews, which is why I took a keen interest when the US Federal Trade Commission (FTC) announced new rules to clamp down on fake reviews and testimonials – which have since gone into effect – as I explained in TMW #189 | Martech Briefing:

“The U.S. Federal Trade Commission (FTC) announced a final set of rules to clamp down on fake customer reviews and testimonials. The new rules prohibit the buying and selling of fake reviews and testimonials, incentivizing positive or negative reviews, getting company staff to publish reviews, and suppressing customer reviews through threats or intimidation… The FTC's new rules give it broader power to punish not just sellers of fake reviews, but also companies that solicit or allow fake reviews to be published in their name, with fines of up to $50K per offense.”

So why, of all the things that the FTC has on its plate, has it focused its attention on fake reviews? And what does it mean for marketers?

The ultimate form of advertising

Let’s start with why reviews are such an important lever for marketers. Put simply, it all comes down trust.

People trust other people more than they trust brands. According to Nielsen’s Trust In Advertising Study 2021, 88% of consumers trust recommendations from people they know above any other form of marketing messaging. Moreover, word-of-mouth is, according to McKinsey, the primary factor behind 20% to 50% of all purchasing decisions.

But the problem with word-of-mouth is that it doesn’t scale as much as other forms of digital marketing, and it’s a largely uncontrollable channel. Enter online reviews: Why just rely on a customer to tell their immediate family and friends about your product when you can publish their opinion for the whole world to see? 

As the internet gained popularity, buyer journeys across industries became increasingly digital and therefore impersonal too, creating the perfect conditions for the rise of online reviews. Amazon have in many ways led the market when it comes to online reviews: They were the first to adopt them in 1995 , as well as being the first major platform to roll out AI-powered review summaries in June 2023. A lot has happened in the intervening years.

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The review economy has become increasingly crowded over the last 30 years, reflecting the growing reliance of consumers on reviews to make purchases. Even as early as 2015, research published via the Oxford Academic Journal of Consumer Research claimed that online reviews can “make or break” the success of a product or service.

Nowadays, online reviews are one of the key components of most buyer journeys: 93% of consumers have made a purchase based on an online review; 81% refer to Google reviews to evaluate local businesses; and 91% of millennials trust online reviews as much as recommendations from friends and family! The data doesn’t lie: Consumers are more motivated by reviews than they are by free shipping, discounts, and loyalty rewards.

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Consumers’ reliance on online reviews is borne out by the impact that good reviews have on businesses. Review signals account for 13% of how Google ranks local search results, meaning the better your reviews, the more search traffic you’ll get. 

Plus, brands with strong reviews and ratings online are able to use the trust garnered to demand a price premium: 68% of consumers are willing to pay a 15% premium for the same product if they’re assured they’ll have a better experience.

To add further weight: A study by the Harvard Business Review determined that if a business increases its star rating on Yelp by one, it will on average increase revenue by 9%. Put simply, good reviews impact a business’ bottom line. But if you think reviews are already as important as they can be for brands, then think again. Trust in corporations – and government and media for that matter – is continuing to fall, meaning consumers are increasingly relying on each other. According to Edelman’s Trust Barometer for 2024, 61% of people worry that business leaders are purposely trying to mislead them via false statements and exaggeration.

The FTC is getting involved because online reviews have become critical for businesses to gain and maintain trust with increasingly digital buyers.

The review economy

Given how reviews have become such a crucial part of how businesses operate in the 21st century, it’s no surprise that such a massive economy has grown out of it. And it’s not just a binary ‘review or no review’ ecosystem: Within the review economy, there are a range of different types of consumer review sites, which can be sorted based on their level of independence and generality.

In the top left, we have general review sites. These aggregate reviews across any type of product and are truly independent in so much that they have no incentive but to uncover the truth from consumer reviews. Social media reviews are almost identical to general review sites, ; the only difference is that they exist on platforms that are predominantly for social connection rather than reviews themselves. 

Next up are general marketplaces. Platforms like Amazon and eBay aggregate reviews, but these are only for e-commerce products, making them slightly narrower in scope. It’s worth noting the bad incentives at play for Amazon, which directly competes with its sellers in some categories but also controls how consumers discover products on their platform, including using star ratings as a filter.

In the top right-hand corner, we have independent, niche review sites. Think: OpenTable for restaurants, TripAdvisor for tours and travel experiences, and RateMDs for doctors. Nearby are the niche marketplaces like Poshmark and Etsy.

Finally, the bottom-right corner is for brand-owned reviews. Sites like ASOS, Zappos, and Sephora have their own review ecosystems within their sites.

This is just a small slice of the overall review economy to illustrate the flavors reviews that exist out there; there are hundreds or maybe even thousands of other sites and platforms that publish consumer reviews.

These companies have built their businesses around the ability for humans to voice their honest opinion about products. But what happens when reviews don’t represent that honesty? And what about when they’re not even posted by a human?

The problem with fake reviews

Before I jump into the current challenge with fake reviews, let me define what I mean by fake reviews. There are many different flavors of fake reviews, with varying harms to consumers and competing brands.

 

The big weak spot of online reviews is the relative anonymity afforded to reviewers and the lack of validation of their reviews. Fake reviews have existed since Amazon launched in 1995, but as online reviews have become more important commercially, so too has the prevalence of fraudulent ones.

And that problem has accelerated in recent years as AI has made it easier than ever to spread fake reviews. Today, 11% to 15% of reviews on Amazon.co.uk across consumer electronics, home and kitchen, and sports and outdoors are fake. Amazon is one of the most active companies in trying to ensure the veracity of their reviews, so they are at the lower end of the scale; of the top eight e-commerce sites that use reviews in the UK, the estimated number of fake reviews ranges from 32.5% to 46.1%.

We can also see the scale of fake reviews by the clean-ups that big review platforms have undertaken in recent years: Amazon removed more than 200M suspected fake reviews in 2022 alone, while Google removed 115M “policy-violating reviews” in the same year, which was a jump of 20% from 2021.

And consumers are noticing the rise in fake reviews too, especially across the major platforms.

As part of an investigation into fake reviews, the UK Department for Business & Trade assessed the financial impact of fake reviews on consumers, giving a “conservative estimate” of £50M to £312M of annual harm caused to UK consumers by fake reviews. That harm is likely concentrated in higher priced products, as consumers are 9.2% more likely to purchase a product based on a well-written fake review for products over £80.

This might all sound like a big consumer problem, but it’s really a brand problem. The more harm that consumers experience from fake reviews, the lower their trust in reviews and brands. In a perfect world, good reviews are the ultimate arbitrator between successful brands and unsuccessful ones, but the more that trust in reviews is eroded, the further we get from that perfect world.

So, how do we reverse the growing trend of fake reviews?

Regulation and technology, working hand in hand

The FTC’s new regulation really lights a fire underneath all those involved in the review economy by enacting fines for anyone that sells or buys fake reviews, or even allows them on their website. A $50K per offense fine – which scales for the largest platforms – is a forceful incentive to stamp out fake reviews.

Let’s consider this in terms of the 200M suspected fake reviews that Amazon removed from its platform in the 2022 calendar year. If Amazon didn’t delete those reviews, then its potential liability for fines for fake reviews would be $10 trillion per year!

The trouble for Amazon and other companies that use online reviews is no longer one of incentive; it’s a challenge of scale. If Yelp accounts for 6% of reviews on the internet and publishes 26,380 new reviews every minute, then there are roughly 633M reviews published across all platforms every single day! How can companies weed out fake ones fast enough to keep up?

Well, some tech companies have taken a first-principles approach by building review platforms that focus on purchase verification. Platforms like the aptly named Verified Reviews build integrations with customers’ purchase data to first verify a reviewer has at least bought the product, then integrate the reviews into public review platforms like Google My Business and Facebook.

This works to a certain extent, but for large review aggregator platforms, there is no way they can integrate with all their listed sellers’ purchase data. For these companies, the answer is… AI.

Let’s stick with Amazon here, who is a leader when it comes to reviews, including minimizing fake ones. The company uses AI over the top of its massive first-party data set to work out which reviews are likely to be fake, taking into account behavioral and purchasing patterns, the timing and frequency of reviews, relationships of reviewers, and customer-submitted reports of review abuse.

For companies that don’t have the capability to build proprietary AI-powered fake review detectors, an industry of third-party fraud prevention platforms has sprung up to serve this need. Platforms like Pasabi use AI to help brands keep fake reviews off their own properties and even third-party review sites. 

And this tech is also being incorporated into consumer tools. ReviewMeta is a free tool that allows consumers to input product URLs from Amazon and then uses AI to give an independent assessment of which reviews are real and fake, including a recalculated star rating. Although the proliferation of AI has been one of the big drivers of believable, scaled fake reviews, it is also playing a big part in solving the problem it exacerbated.

Another approach playing out is brands building out community-style platforms that foster deep engagement between prospects and existing customers, rather than just relying on reviews and star ratings to act as social proof.1 💬

The big question here is if review platforms and brands can act quickly enough before consumers become too jaded by bad experiences caused by fake reviews. Although companies like Google and Amazon are deleting millions of reviews each year, consumers are still noticing fake reviews on their platforms, and therefore may be continuing to lose faith in them.

This would be the worst-case scenario for any brand that differentiates itself through its quality and service -level. If online reviews become meaningless, what proof points do you have left to convince consumers that your product is high-quality or made-to-last? Perhaps it will even lead to a resurgence in bricks-and-mortar stores and physical experiences where consumers can see and touch a product in the flesh. 

So, is this the start of the end for the review economy? Consumers rely on reviews to make almost any type of purchase, but if they can’t trust the reviews they are reading, then they won’t trust the brands they’re buying from, which will make reviews count for not very much at all.


💬 Insights from Alium, The Buyer Intelligence Platform:

  1. “What [brand] has done is they've created this community or this ecosystem, where I as a user can go onto their website and I can search and ask questions and I can get answers from real people, not from their customer service agents or people that are paid. They're real [brand] advocates that [are also] experts. And that gives a different level of trust and authenticity, but they've done it in a way where it's all funneled through this one platform. It's almost like going to YouTube, but you can [find] very specifically the [information] you're looking for.”

Beverage, Food & Healthcare | $10B – $100B revenue | 100K+ employees


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Stay Curious,

Keanu Taylor

Make sense of marketing technology.

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Want to share something interesting or be featured in The Martech Weekly? Drop me a line at juan@themartechweekly.com.

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