95 Online Review Statistics for 2026

Key Takeaways

• Generative AI became a mainstream discovery channel in twelve months. Use of AI tools for local recommendations went from 6% to 45%, while the share of consumers using Google for business reviews fell from 83% to 71%.
• Nearly everyone reads reviews, and more people now read them every time. 97% read reviews when browsing for a local business, and the share who say they “always” do jumped from 29% to 41% in a year.
• The best conversion evidence is nine years old. The 270% and 380% lifts everyone quotes come from a 2017 Spiegel study that has never been replicated. Cite the year or don’t cite it.
• Platform “fake review” numbers measure detection, not prevalence. Trustpilot’s 7.4%, Tripadvisor’s 8% and Pangram’s 3% are three different definitions counting three different things.
• Nobody can reliably spot an AI-written review. Humans averaged 50.8% accuracy in a 2025 study, and seven leading language models did no better.
• Fake reviews are now illegal on both sides of the Atlantic, with US penalties up to $53,088 per violation and UK penalties up to 10% of global turnover.

Top Online Review Statistics for 2026

If you carry five numbers into a planning meeting, carry these.

Five Headline Review Statistics

1. 97% of US consumers read reviews when browsing for local businesses (BrightLocal Local Consumer Review Survey 2026, January 2026, US adult panel).

2. 45% now use ChatGPT or another generative AI tool to find local business recommendations, up from 6% one year earlier, which makes AI the third most popular recommendation source overall (BrightLocal 2026).

3. 41% say they “always” read reviews when browsing, up from 29% in the 2025 wave (BrightLocal 2026).

4. 71% use Google for business reviews, down from 83% a year earlier (BrightLocal 2026).

5. Displaying five reviews on a product page lifted conversion 270% against the same page with none (Spiegel Research Center, Northwestern Medill, June 2017, with PowerReviews).

Reading These Five Numbers

Four of the five come from one vendor’s annual survey. BrightLocal sells local SEO software, so its questions follow its customers’ problems. The same instrument has run since 2010, which makes the year-over-year moves sturdier than any single-year level. Spiegel measured purchases, not intentions.

How Many People Read Online Reviews

Reading reviews is close to universal. The framing around that headline has tightened.

Reading Frequency in 2026

6. 97% of US consumers read reviews when browsing for local businesses (BrightLocal 2026).

7. 41% read them every time, up from 29% in 2025, a twelve-point jump in a single wave (BrightLocal 2026).

8. 74% check at least two review sites before deciding (BrightLocal 2025, February 2025, n=1,026 US adults).

The 97% number gets recycled in decks every January without its qualifier. BrightLocal’s question wording has shifted across waves, so it isn’t strictly the same metric each year, and the 2026 figure is the one with the freshest sample. Treat it as “reading reviews is universal,” not as a precision measurement you can trend across a decade.

Who Writes Online Reviews

If you have ever wondered what percentage of people leave reviews rather than just read them, the honest answer is that no current survey reports a clean single number. What the 2026 wave does report is volume bands.

9. 20% of consumers wrote more than 10 reviews during 2025 (BrightLocal 2026).

10. 7% wrote more than 50 (BrightLocal 2026).

11. 22 million people wrote their first-ever Trustpilot review in 2024, up 13% year over year (Trustpilot Trust Report 2025, May 2025, platform telemetry).

12. 229,000 companies were reviewed on Trustpilot for the first time in 2024, up 35% (Trustpilot Trust Report 2025).

That small super-reviewer cohort matters more than its size suggests. A 7% minority writing 50-plus reviews a year sets the tone of every category page they touch, and they’re the reviewers most likely to be recognised and cultivated by the platforms.

Photo and Video Review Statistics

The ecommerce product review statistics below come from retail panels rather than local-business surveys, so they measure a different shopper on a different page.

13. 60% of consumers always look for visual content from other shoppers before buying, up from 50% in 2021 and 40% in 2016 (PowerReviews, February 2024, n=15,870 US consumers, fielded December 2023).

14. 91% are more likely to buy a product whose reviews include photos or video alongside text, up from 85% in 2021 and 72% in 2016 (PowerReviews 2024).

15. 84% want shopper photos and videos included directly on the product detail page (PowerReviews 2024).

16. 74% of online shoppers regularly read Q&A sections (PowerReviews Q&A Confidence and Conversion Rate Report, April 2024, same panel).

17. 92% value answers from verified buyers, against 51% who value answers from the brand (PowerReviews, April 2024).

One caveat on stat 13. PowerReviews’ press release frames the 60% as “visual UGC,” while the detailed report page separates general visual content from shopper-generated visual content and reports a lower figure for the narrower definition. I’m using the company’s own headline framing, and you should know the distinction exists before you put it in a deck.

The 92-against-51 gap in stats 16 and 17 is the one I’d act on first. Shoppers trust a stranger who bought the thing roughly twice as much as they trust you answering about your own product, which makes an unanswered Q&A section a bigger conversion problem than most teams treat it as.

Where Consumers Read Online Reviews

Google still leads. The interesting part is what’s eating into it.

Google’s Falling Share of Review Readers

18. Google’s share of review readers fell from 83% in 2025 to 71% in 2026 (BrightLocal 2026).

19. Generative AI tools went from 6% to 45% as a source of local business recommendations (BrightLocal 2026).

20. Apple Maps nearly doubled, from 14% to 27% (BrightLocal 2026).

21. Local news sites collapsed from 48% to 29% (BrightLocal 2026).

BrightLocal sells local SEO software, so a finding that says “local search just got more complicated” deserves a raised eyebrow. The directional move holds up against an independent source though. Bazaarvoice, surveying a different panel in a different set of countries, found the same behaviour in ecommerce.

22. 24% of global consumers used a generative AI tool to search for a product instead of a search engine, rising to 41% among 18 to 34 year olds (Bazaarvoice Shopper Experience Index 2025, September 2025, n=7,000+ across six countries, fielded by Savanta in July 2025).

23. 55% trust generative AI tools and shopping agents for at least some things, rising to 75% among 18 to 34 year olds (Bazaarvoice 2025).

Two vendors with different commercial interests, different panels and different questions landed on the same shape. That’s the closest thing to corroboration this field offers.

Review Platform Statistics by Usage

24. 83% of consumers used Google to read business reviews in 2025 (BrightLocal 2025, n=1,026).

25. 48% used local news sites (BrightLocal 2025).

26. 44% used Yelp (BrightLocal 2025).

27. 40% used Facebook (BrightLocal 2025).

28. 34% used YouTube (BrightLocal 2025).

29. 20% used TikTok (BrightLocal 2025).

Video platforms carrying a third of review-reading behaviour is the number most brands are underweight on. A written review policy that doesn’t account for YouTube and TikTok is covering roughly two thirds of where people actually look.

Review Volume by Platform

Cross-platform volume comparisons are messy because every platform counts a different thing. Yelp’s cumulative total includes reviews its own algorithm doesn’t recommend, Trustpilot reports platform totals, Tripadvisor reports one year of contributions, and Google reports one year of published reviews. With that stated plainly:

30. Google Maps published more than 1 billion helpful reviews during 2025 (Google, “New Ways We’re Protecting Businesses on Maps”, April 2026).

31. Google’s community suggested more than 80 million updates to business hours and contact information in 2025 (Google, April 2026).

32. Trustpilot received 61 million reviews in 2024 (Trustpilot Trust Report 2025).

33. Trustpilot carries more than 300 million reviews and 64 million monthly active users (Trustpilot Trust Report 2025).

34. Tripadvisor received 31.1 million reviews in 2024, part of roughly 80 million total contributions including photos (Tripadvisor 2025 Transparency Report, March 2025, covering calendar year 2024).

35. Yelp received 21 million new reviews in 2024, taking its cumulative total to 308 million, up 7% year over year (Yelp Q4 2024 8-K Exhibit 99.1, filed February 2025 with the SEC).

36. Yelp’s 2024 net revenue reached a record $1.41 billion, up 6% year over year (Yelp Q4 2024 8-K).

37. Yelp’s services advertising revenue hit $879 million, up 11% (Yelp Q4 2024 8-K).

Stat 35 is the only review-volume figure on this page that carries securities-law liability behind it. That’s worth remembering when you’re weighing it against a marketing blog post.

Star Ratings Versus Written Reviews

38. 71% of review readers don’t consider a star rating without text to be a review at all (Yelp and YouGov, February 2025, n=2,630 US adults with 2,352 review readers, fielded January 15 to 17, 2025).

39. 88% are more likely to trust written reviews over star-only ratings (Yelp and YouGov, February 2025).

40. Roughly 50% of Google reviews contain 100 characters or fewer, and 32% have no text at all (Devesh Raval, “Do Bad Businesses Get Good Reviews? Evidence Across Several Online Review Platforms”).

41. The average recommended Yelp review ran about 447 characters as of December 31, 2024 (Yelp and YouGov, February 2025).

Yelp commissioned stats 38 and 39 to differentiate itself from Google’s looser standard, so read them as advocacy. Stat 40 is the interesting one, and it isn’t Yelp’s. It comes from an FTC economist’s own working paper.

How Online Reviews Influence Sales and Conversion

This is the section marketers care about most, and it is where the oldest numbers still circulate as though they were measured last quarter.

Conversion Lift From Displaying Reviews

42. A page with five reviews converted 270% better than a page with none (Spiegel Research Center, June 2017).

43. For higher-priced products the lift reached 380% (Spiegel, 2017).

44. For lower-priced products it was 190% (Spiegel, 2017).

45. Purchase likelihood peaks in the 4.0 to 4.7 star range rather than at a perfect 5.0, the “too good to be true” effect (Spiegel, 2017).

I want to be blunt about stat 45, because the version circulating in most roundups says 4.2 to 4.5. Spiegel’s own page states 4.0 to 4.7. The narrower range appears to come from the related academic paper rather than the report everyone links to, so if you see 4.2 to 4.5 attributed to Spiegel, it’s been narrowed somewhere along the citation chain.

No equivalent update to the Spiegel work has been published since 2017. That’s nine years, across which product pages, review widgets and shopper expectations all changed substantially. The numbers are real. Presenting them as current is a credibility risk you don’t need to take.

Star Rating Impact on Revenue

46. A one-star increase in Yelp rating drove a 5% to 9% revenue increase for restaurants (Michael Luca, Harvard Business School Working Paper 12-016, revised March 2016, using Seattle restaurant data from 2003 to 2009).

47. The effect came entirely from independent restaurants; chains showed no significant response (Luca, 2016).

48. Roughly 16% of Yelp restaurant reviews were filtered as suspicious during the study period, used as a proxy for review fraud (Luca and Zervas, Management Science 62:12, December 2016).

Luca’s paper is the cleanest causal study in this literature, and its limits are severe: restaurants only, Seattle only, data ending in 2009. It gets quoted as “reviews drive 5 to 9% revenue” across every industry, which the paper does not support. Quote the window.

Reviews and Brand Perception

49. 91% of consumers say a local branch’s reviews shape their perception of the parent brand (BrightLocal 2024, February 2024, roughly 1,000 US adults).

50. 86% of global consumers bought a private-label product in the last six months, up from 64% in 2024 (Bazaarvoice 2025).

51. 65% of global shoppers rely on user-generated content in buying decisions (Bazaarvoice Shopper Experience Index Vol. 18, November 2024, n=8,000+).

52. 80% of Gen Z consumers consider user-generated content crucial to their decisions (Bazaarvoice, November 2024).

Stat 50 is the quiet one. A 22-point jump in private-label purchasing in a single year suggests reviews are now doing work that brand familiarity used to do. If an unknown label with 400 good reviews beats a known brand with 40, your review corpus is your moat.

Fake Review Statistics and AI-Generated Reviews

Platforms report aggressive removal numbers. Regulators have caught up. Academic researchers are skeptical that anyone, human or machine, can reliably tell a fake from a real review at the text level. All three things are true at once.

Fake Reviews Removed by Platform

53. Google blocked or removed more than 292 million policy-violating reviews in 2025 (Google, April 2026).

54. The equivalent figures were 240 million in 2024 (Google, April 2025) and more than 170 million in 2023 (Google, February 2024).

55. Google also blocked 79 million inaccurate or unverified business-profile edits and removed more than 13 million fake Business Profiles in 2025 (Google, April 2026).

56. Trustpilot removed 4.5 million fake reviews in 2024, equal to 7.4% of submissions, up from 6.1% in 2023 (Trustpilot Trust Report 2025).

57. 90% of those removals were caught automatically, without a human in the loop (Trustpilot Trust Report 2025).

58. Tripadvisor flagged 8% of submitted reviews, 2.7 million in total, as fraudulent in 2024, more than double the roughly 1.2 million removed in 2022 (Tripadvisor 2025 Transparency Report).

59. Tripadvisor auto-approved 87.8% of submissions, rejected 7.3% automatically and routed 4.9% to human moderators (Tripadvisor 2025 Transparency Report).

60. Yelp filtered out nearly 500,000 suspected AI-generated reviews in 2025 (Yelp 2025 Trust & Safety Report, February 2026).

61. Yelp closed more than 1.3 million user accounts in 2025, a 138% increase, driven mostly by an airline phone-support scam wave (Yelp 2025 Trust & Safety Report).

62. Yelp made more than 1,020 reports to Instagram, Facebook, X, Reddit and TikTok about review-trade groups, up 45%, and 60% led to action (Yelp 2025 Trust & Safety Report).

63. Amazon proactively blocked “hundreds of millions” of suspected fake reviews in 2025 and helped shut down more than 100 websites facilitating review fraud (Amazon Trustworthy Shopping Experience Report 2025, February 2026).

Here’s the trap in every one of those numbers. They measure what detection caught, not what exists.

A platform that improves its classifier reports a higher fake-review rate while the site gets cleaner. A platform that widens its definition reports a jump with no change in behaviour at all.

Tripadvisor’s own vice president said exactly that about the doubling in stat 58: the number of fake reviews on the site did not double, the treatment of incentivised reviews changed.

Amazon’s “hundreds of millions” in stat 63 is a range, not a figure. Amazon doesn’t break out fake-review removals as a discrete category, so nobody outside the company can size it.

Tripadvisor Fake Review Categories

64. 54% of the fake reviews Tripadvisor caught in 2024 were “boosting,” meaning business-affiliated (Tripadvisor 2025 Transparency Report).

65. 39% were member fraud (Tripadvisor 2025 Transparency Report).

66. 4.8% were vandalism (Tripadvisor 2025 Transparency Report).

67. 2.1% were paid reviews (Tripadvisor 2025 Transparency Report).

68. Tripadvisor flagged and removed 214,000 AI-generated reviews in 2024 (Tripadvisor 2025 Transparency Report).

The paid-review industry gets the press coverage and accounts for one review in fifty. The overwhelming majority of fake reviews are businesses writing about themselves, which is a much less exotic problem and a much more common one.

AI-Generated Reviews in Independent Research

69. 3% of front-page Amazon reviews, 909 out of a 30,000-review sample across 500 best-selling products, were flagged as high-confidence AI-generated (Pangram Labs, July 2025).

70. 5% were flagged in the baby, beauty and wellness categories (Pangram Labs, July 2025).

71. 93% of the AI-flagged reviews carried Amazon’s “Verified Purchase” badge (Pangram Labs, July 2025).

72. 74% of the AI-flagged reviews awarded 5 stars, against 59% of human-written reviews (Pangram Labs, July 2025).

73. Humans wrote 22% of 1-star reviews, against 10% from the AI-flagged group (Pangram Labs, July 2025).

74. Human evaluators averaged 50.8% accuracy, which is chance, at distinguishing AI-generated product reviews from real ones, and seven leading language models performed equivalently or worse (Large Language Models as “Hidden Persuaders”, arXiv preprint, June 2025).

Pangram sells AI-detection software, so treat stats 69 through 73 as an upper bound on what a commercial detector claims to find, not a measured prevalence. Stat 74 is the counterweight, and the two cannot both be fully right. My reading is that detectability depends heavily on review length, model and language, and that anyone selling you certainty on this is selling.

The practical signal is stat 71. Verified Purchase does not mean human. If your competitive research assumes a purchase badge filters out synthetic text, it doesn’t.

If you need to check copy on your own side of the line, Originality.ai is the detector I’ve spent the most time with, and the same caveat applies to it: treat any score as a prompt to look closer, never as a verdict.

Fake Review Laws and Penalties

75. The FTC’s Trade Regulation Rule on the Use of Consumer Reviews and Testimonials, 16 CFR Part 465, took effect on October 21, 2024 (Federal Register, published August 22, 2024).

76. Civil penalties run up to $51,744 per violation as promulgated, inflation-adjusted to $53,088 by a Federal Register notice of January 17, 2025.

77. The rule passed the Commission 5 to 0 and bans fake or AI-generated reviews, buying positive or negative reviews, undisclosed insider reviews, company-controlled review sites posing as independent, review suppression through legal threats, and fake social-media indicators (Federal Register, August 2024).

78. The UK’s DMCC Act 2024 unfair commercial practices provisions came into force on April 6, 2025, with the CMA allowing a three-month grace period to July 2025 (CMA208 Fake Reviews Guidance, April 2025).

79. UK penalties run up to 10% of global turnover for businesses and £300,000 for individuals (CMA208, April 2025).

80. The CMA estimated £23.31 billion of annual UK consumer spending is potentially influenced by online reviews, split across travel and hotels at £14.38 billion, home improvements at £3.93 billion, electronics at £3.13 billion, beauty and grooming at £1.01 billion, music at £0.5 billion and books at £0.36 billion (CMA, Online reviews and endorsements market study, published 19 June 2015).

81. The FTC’s December 2024 final order against Rytr LLC, which barred the company from selling AI services dedicated to generating consumer reviews for 20 years, was reopened and set aside on December 22, 2025, citing the administration’s AI Action Plan (FTC, December 2025). The FTC issued ten warning letters for Consumer Review Rule violations concurrently.

82. Roomster’s owners bought more than 20,000 fake four and five star reviews from AppWinn using more than 2,500 fake iTunes accounts. The FTC and six state attorneys general secured a permanent ban on buying or incentivising consumer reviews and a $1.6 million payment in August 2023.

Stat 80 deserves a flag. The £23 billion figure is the CMA’s, but it comes from a 2015 market study, not from the 2025 fake-reviews guidance it is usually attributed to.

The CMA208 guidance contains no currency figures at all. An eleven-year-old estimate is still the best UK number available, and it should be dated as one.

Stat 81 is the closest thing to a reversal in this space, and it’s narrower than it looks. The FTC withdrew the theory that selling a general-purpose AI writing tool constitutes a violation. It did not withdraw from enforcing against fake reviews themselves, which is what the ten concurrent warning letters were for.

Review Responses and Reputation Management Statistics

Reviews don’t sit still. What you do with them shapes the next purchase decision, and the data here contains the single strangest finding on this page.

Review Response Expectations and Timing

83. 89% of consumers expect business owners to respond to reviews, and 81% expect that response within a week (BrightLocal 2026).

84. 88% say they would use a business that replies to all reviews, against 47% for businesses that never respond (BrightLocal 2024, February 2024).

85. 91% say a local branch’s reviews shape their view of the parent brand (BrightLocal 2024).

Stat 84 is the one to put in front of a client who thinks responses are optional. Not responding roughly halves the share of consumers willing to use the business. That’s a bigger swing than most of the conversion-rate work on this page, from a much cheaper intervention.

AI-Written Review Responses

86. In a blind test, 58% of consumers preferred the AI-written review response over the human-written one (BrightLocal 2024, February 2024).

87. 82% of consumers read AI-generated review summaries, and 23% are willing to decide on the summary alone (BrightLocal 2026).

Stat 86 is the most actionable finding in this entire pile of data. The same consumers who tell surveyors that AI-written content is fake and untrustworthy picked the AI response as the better one when they couldn’t see which was which.

I read that as a craft signal rather than permission to automate. The AI response won because it was structured, specific and complete, not because it was AI. A human writing with the same discipline wins the same test. What it does rule out is the fear that a well-written AI-assisted response will be spotted and punished, because in a controlled test it wasn’t.

Monitoring is the part most teams skip. If you want a starting point for catching mentions and reviews across platforms rather than checking dashboards one at a time, Brand24 is the tool I point people at.

Online Review Statistics: Then and Now

Several figures below have been cited widely for years. Each appears with the source as originally published, alongside the closest current measurement.

BrightLocal Figures Then and Now

88. Previously cited: 87% of people used Google out of more than 10 review platforms to evaluate local businesses (BrightLocal). Current comparable figure: 83% used Google in the 2025 wave, falling to 71% in 2026 (BrightLocal 2026).

89. Previously cited: 46% of consumers trust online reviews as much as personal recommendations from family and friends (BrightLocal, n=1,000+ US consumers). BrightLocal still asks this question every wave, and the answer has fallen a long way: 79% in 2020, 42% in 2025 and 49% in 2026. The previously cited 46% sits close to where the series is now.

90. Previously cited: 95% of people leave online reviews or would consider leaving one (BrightLocal). Current comparable figures: 20% wrote more than 10 reviews during 2025 and 7% wrote more than 50.

91. Previously cited: 88% of consumers are likely to use a business if they see the owner responding to positive and negative reviews (BrightLocal). This one still stands in the current data: 88% would use a business that replies to all reviews, against 47% for non-responders (BrightLocal 2024).

Shopper Survey Figures Then and Now

92. Previously cited: 85% of more than 2,000 shoppers seek out negative reviews before making purchase decisions (PowerReviews). PowerReviews’ current published work covers visual content and Q&A rather than negative-review seeking, so the 2021-era figure remains the most recent measurement of it.

93. Previously cited: 99.9% of 6,538 US consumers read online reviews before shopping online at least sometimes (PowerReviews, 2021). Current comparable figure: 97% read reviews when browsing for local businesses (BrightLocal 2026). The two questions measure different populations and different behaviours.

94. Previously cited: 82% of 30,000 shoppers read online reviews of products before going to the store (Bazaarvoice). Bazaarvoice’s current work reports 65% of global shoppers relying on user-generated content in buying decisions (November 2024).

95. Previously cited: 46% of shoppers are influenced by online reviews when deciding, followed by star rating (Bazaarvoice). This remains Bazaarvoice’s figure from that wave; the current Shopper Experience Index measures channel and AI behaviour instead.

Platform and Employer Figures

96. Previously cited: 2.7 million fake reviews removed and 167.5 million organic reviews written since 2007 (Trustpilot). Current figures: 4.5 million fake reviews removed in 2024, 61 million reviews received in 2024, more than 300 million cumulative (Trustpilot Trust Report 2025).

97. Previously cited: 86% of job seekers research company reviews to decide where to apply, from a survey of more than 2,000 US adults (Glassdoor). Glassdoor does not publish an updated equivalent, and Recruit Holdings does not break out Glassdoor review metrics in its filings, so this remains the most recent public figure.

98. Previously cited: 60% of 10,000 Bazaarvoice respondents said negative online reviews are also important in purchase decisions (Bazaarvoice). No newer measurement of the same question has been published.

The pattern across those eleven entries: almost every claim that got weaker over time was a survey question the publisher quietly stopped asking, not a finding that was overturned. That is a different failure mode from being wrong, and it is why the year matters more than the number.

How to Use Online Review Statistics in 2026

Write for AI shopping agents as well as shoppers, date every conversion stat you quote, and read fake-review removal rates as detection output, not prevalence. Related data: content marketing statistics, SEO statistics, digital marketing statistics and influencer marketing statistics.

Frequently Asked Questions

What Percentage of Consumers Read Online Reviews in 2026?

97% of US consumers read reviews when browsing for local businesses, and 41% say they always do, up from 29% in 2025 (BrightLocal Local Consumer Review Survey 2026, January 2026, US adult panel). Cross-platform checking is also common: 74% look at at least two review sites before deciding (BrightLocal 2025, n=1,026). Those are the strongest 2026-stamped figures available.

Are AI-Generated Reviews Actually a Problem?

Yes, though the size depends entirely on who is counting. Pangram Labs flagged 3% of front-page Amazon reviews as high-confidence AI-generated in July 2025, from a 30,000-review sample across 500 best-sellers. Tripadvisor removed 214,000 AI-generated reviews in 2024 and Yelp filtered nearly 500,000 suspected ones in 2025. Independent academic work published in June 2025 found humans averaging 50.8% accuracy, which is chance, at spotting them, so vendor detection numbers should be read as upper bounds.

Is It Illegal to Buy Fake Reviews?

In the US, yes, since October 21, 2024, when the FTC’s Consumer Reviews Rule (16 CFR Part 465) took effect, with civil penalties up to $53,088 per violation after the January 2025 inflation adjustment. In the UK, the DMCC Act 2024 provisions came into force on April 6, 2025, with penalties up to 10% of global turnover. Both regimes also ban undisclosed incentivised reviews, undisclosed insider reviews and review suppression through legal threats.

How Much Does a One-Star Rating Change Move Revenue?

The cleanest causal estimate is Michael Luca’s Harvard Business School working paper, revised in 2016, which found a one-star increase in Yelp rating drove a 5% to 9% revenue increase for Seattle restaurants between 2003 and 2009. The effect came from independent restaurants; chains showed no significant response. No equivalent updated study exists, so state the 2003 to 2009 window whenever you use it.

Which Review Platform Do Consumers Trust Most?

By usage, Google leads, though its share of review readers fell from 83% in 2025 to 71% in 2026 (BrightLocal 2026). By trust signal, Yelp’s YouGov survey found 71% of review readers don’t count a star rating without text as a review, which favours platforms carrying longer written reviews. Apple Maps nearly doubled its share year over year, from 14% to 27%.

Do Photo and Video Reviews Actually Matter?

PowerReviews’ US panel of 15,870 consumers, fielded December 2023 and published February 2024, found 60% always look for shopper visual content before buying, up from 50% in 2021 and 40% in 2016, and 91% are more likely to buy a product whose reviews include photos or video. The data is vendor-funded and US-only, but the trend across three waves is consistent enough to plan against.

How Much Consumer Spending Do Online Reviews Influence?

The UK Competition and Markets Authority put it at £23.31 billion of annual UK consumer spending, with travel and hotels accounting for £14.38 billion of that. Note the date: this comes from the CMA’s Online reviews and endorsements market study published on 19 June 2015, not from its 2025 fake-reviews guidance, where the figure is often wrongly attributed. No equivalent US government estimate exists.

Should I Respond to Reviews With AI?

The evidence says a well-written AI-assisted response won’t be detected or punished. In BrightLocal’s 2024 blind test, 58% of consumers preferred the AI-written response over the human-written one, while the same consumers said in stated-preference questions that AI equals fake. The response won on structure and specificity, which a human can match. Treat AI as a drafting aid on a response you’d have been willing to write yourself.

Sources

Figures on this page come from the primary sources below, checked in September 2026.

• BrightLocal, Local Consumer Review Survey 2026, January 2026
• BrightLocal, Local Consumer Review Survey 2025, February 2025
• BrightLocal, Local Consumer Review Survey 2024, February 2024
• Trustpilot, Trust Report 2025 (FY 2024 data), May 2025
• Yelp Inc., Q4 and Full Year 2024 Press Release (8-K Exhibit 99.1), February 2025
• Yelp Inc., 2025 Trust & Safety Report, February 2026
• Yelp and YouGov, Consumer Trust Survey, February 2025
• Tripadvisor, 2025 Transparency Report (CY 2024 data), March 2025
• Google, “New Ways We’re Protecting Businesses on Maps,” April 2026
• Google, “Google Business Profiles, AI, and Fake Reviews,” April 2025
• Google, “How Machine Learning Keeps Contributed Content Helpful,” February 2024
• Amazon, Trustworthy Shopping Experience Report 2025, February 2026
• Bazaarvoice and Savanta, Shopper Experience Index 2025, September 2025
• Bazaarvoice and Savanta, Shopper Experience Index Vol. 18, November 2024
• PowerReviews, Role and Impact of User-Generated Visual Content on Shopper Behavior, February 2024
• PowerReviews, Q&A Confidence and Conversion Rate Report, April 2024
• US FTC, Final Rule, 16 CFR Part 465, August 2024
• US FTC, Adjustments to Civil Penalty Amounts, January 2025
• US FTC, FTC Reopens and Sets Aside Rytr Final Order, December 2025
• Illinois Attorney General and US FTC, Roomster Settlement, August 2023
• UK CMA, CMA208 Fake Reviews Guidance, April 2025
• UK CMA, Online Reviews and Endorsements market study, 19 June 2015
• Spiegel Research Center, Northwestern Medill, How Online Reviews Influence Sales (with PowerReviews), June 2017
• Michael Luca, Harvard Business School, Reviews, Reputation, and Revenue (Working Paper 12-016), revised March 2016
• Devesh Raval, Do Bad Businesses Get Good Reviews? Evidence Across Several Online Review Platforms, undated
• Pangram Labs, Three Percent of Front-Page Amazon Reviews Are Now AI-Generated, July 2025
• Large Language Models as “Hidden Persuaders”, arXiv preprint, June 2025