United States Federal Trade Commission Enforcement in Novel Online Reviews Algorithm Case and Potential Implications for Canada

by Practical Law Canada Competition
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This Legal Update discusses potential implications in Canadian competition law regarding false and misleading advertising and algorithms following a recent enforcement decision by the United States Federal Trade Commission (FTC) against Fashion Nova, LLC (Fashion Nova). In this case, the FTC concluded that Fashion Nova misled consumers contrary to section 5(a) of the United States Federal Trade Commission Act by using a third-party management interface algorithm to automatically publish favourable customer reviews while withholding and concealing more negative customer reviews. It follows increased enforcement efforts from Canadian and foreign competition authorities regarding algorithms in the digital economy. This Update discusses this novel case, Canadian parallels and potential implications, and some of the broader emerging issues relating to algorithms and competition.
Online customer reviews are commonplace for internet retailers and can inform and influence consumer purchases. However, concealing negative customer reviews can contravene competition and other consumer protection laws. For example, the use of management interface software or algorithms to conceal negative online customer reviews directly or indirectly may inaccurately reflect and inflate customer satisfaction, raising misleading advertising issues under the Competition Act, R.S.C. 1985, c. C-34 and other Canadian and international competition or consumer protection laws.
In this regard, on January 25, 2022, the United States Federal Trade Commission (FTC) announced that it reached a proposed settlement agreement with California-based fashion retailer Fashion Nova, LLC (Fashion Nova) (see Press Release, Fashion Nova will Pay $4.2 Million as part of Settlement of FTC Allegations it Blocked Negative Reviews of Products, FTC, January 25, 2022).
In making the announcement, the FTC’s Director of Consumer Protection said:
“Deceptive review practices cheat consumers, undercut honest businesses, and pollute online commerce.”
Under the settlement agreement, Fashion Nova will pay USD4.2 million for allegedly concealing negative online customer reviews, thereby misleading customers. In addition, Fashion Nova will be prohibited from making misrepresentations about customer reviews or endorsements and must post on its website all product reviews, excluding unrelated and obscene reviews (for example, reviews that contain obscene, sexually explicit or racist content).
Like many online retailers, Fashion Nova’s website uses a five-star customer review rating system for its products. Each product web page allows customers to post a product review and rating. Prospective customers visiting the web page can view the average product rating, number of reviews and individual reviews.
According to the FTC, Fashion Nova engaged in deceptive marketing practices by intentionally filtering reviews through its management interface algorithm, which automatically posted four- and five-star reviews, while holding and not approving lower-star (more negative) reviews. In particular, the FTC claims that Fashion Nova installed a third-party online product review management interface algorithm to filter and conceal hundreds of thousands of unfavourable reviews below four stars from as early as late 2015 to mid-November 2019. As such, the FTC alleged that Fashion Nova inaccurately inflated its overall online product rating contrary to section 5(a) of the Federal Trade Commission Act.
In addition to the settlement agreement, the FTC also announced that it was sending warning letters to ten companies offering review management services regarding the collection or publication of online customer reviews. This follows the FTC’s wide sweeping warnings in October 2021 sent to more than 700 companies regarding fake or misleading endorsements and representations in social media (see Press Release, FTC Puts Hundreds of Businesses on Notice About Fake Reviews and Other Misleading Endorsements, FTC, October 13, 2021).
The FTC has also released new guidance for online retailers and review platforms to educate them with respect to the agency’s key principles for collecting and publishing customer reviews to not mislead consumers (see Soliciting and Paying For Online Reviews: A Guide For Marketers, FTC, January 2022).
While this case involves online retailers in the United States, it reflects many parallel competition-law issues and enforcement priorities in Canada, including the Canadian Competition Bureau’s (Bureau) increasing focus on the digital economy and algorithms.

False or Misleading Testimonials/Endorsements Under the Competition Act

The Competition Act contains both criminal and civil misleading advertising provisions under sections 52 and 74.01. These provisions apply to false and misleading advertising claims made to promote products, services or business interests, and are broad enough to include false or misleading testimonials and endorsements, including online customer reviews and product ratings. For more information, see Practice Note, Misleading Advertising Under the Competition Act.
With respect to testimonials and endorsements, the misleading advertising provisions of the Competition Act can apply where an influencer or consumer has not actually used the product or service being promoted, claims that do not reflect an influencer or consumer’s actual experience, unsubstantiated product performance claims, and claims where the material connection or interest between a brand and the influencer or consumer is not adequately disclosed to other consumers. For more information, see:
In this respect, both the literal meaning and the “general impression” of an advertising or marketing claim are relevant in determining whether the claim is false or misleading in a material respect. It is also neither necessary to show that any person has actually been deceived or misled as a result of a claim or that a claim was made in Canada (that is, cross-border misleading advertising, including by retailers in the United States, can be caught).
The Bureau in Canada has also both commenced enforcement and issued compliance guidance in relation to online reviews and influencers. For more information, see:

Algorithms and Competition Law

The subject of how emerging technologies, including algorithms, may facilitate anti-competitive practices in the digital economy is receiving increasing attention from both Canadian and international antitrust enforcement agencies.
For example, in Canada, the Bureau’s 2017 Draft Discussion Paper on Big Data and Innovation acknowledged the risk of big data and pricing algorithms in conspiracy (cartel) agreements to collude by using, among other things, common third-party algorithms used by competitors or price algorithms that “adjust rates almost instantaneously” through real-time responses (see Draft Discussion Paper, Big Data and Innovation: Implications for Competition Policy in Canada, Competition Bureau, 2017).
The Bureau’s 2020-2024 Strategic Vision report also expressly sets out measures on how competition law and policy can adapt to enforcement challenges in the digital economy, including exploring opportunities to deploy new digital tools, such as advanced analytics, artificial intelligence and algorithms (see Competition in the Digital Age: The Competition Bureau’s Strategic Vision for 2020-2024, Competition Bureau, February 11, 2020).
Notwithstanding these efforts, the Bureau’s 2018 publication on big data and innovation took the position that “the advent of computer algorithms… should [not] lead to a rethinking of competition law enforcement” considering the broad application of existing conspiracy (cartel) provisions (i.e., there must be an “Agreement”). In other words, while the use of algorithms may introduce more effective and sophisticated ways for competitors to collude, the offence remains rooted in the agreement itself.
Internationally, in November 2019, France’s and Germany’s antitrust agencies released a joint study on algorithms and competition, which includes potential analytical approaches to investigate algorithms (for example, through historical input/output comparisons, pre-defined input testing, simulated real-world testing and sandboxing) (see Algorithms and Competition, Autorité de la concurrence and Bundeskartellamt, November 2019).
In January 2021, the United Kingdom’s Competition & Markets Authority (CMA) released a report on algorithms to describe how they can lead to collusion, self-preferencing (that is, a platform preferencing its own products), as well as discriminatory ranking and consumer pricing, among other things (see Algorithms: How they can reduce competition and harm consumers, Competition & Markets Authority, 2021). The CMA’s report also outlines some techniques (for example, algorithmic auditing and dynamic analysis testing) and recommendations (for example, increasing transparency by developing ethical approaches, guidelines, tools, and principles) that could be used to investigate and address the potentially adverse competitive effects arising from the increased use of algorithms in the digital economy.
The policy and enforcement work discussed above was also summarized in a recent 2021 G7 compendium of approaches report, which included a submission by Canada’s Bureau (see Compendium of approaches to improving competition in digital markets, G7, November 29, 2021).
The increasing use by online sellers of algorithms is also attracting increased enforcement from antitrust enforcement agencies. For example, in January 2022, Amazon entered into a USD2.25 million settlement with Washington State for using a price-fixing algorithm under its “Sold by Amazon” program. According to the State, Amazon allegedly guaranteed that third-party sellers using the platform would receive at least an agreed-upon minimum payment (through a floor price) in exchange for no longer competing with Amazon’s product pricing (see News Release, AG Ferguson investigation shuts down Amazon price-fixing program nationwide, Washington State Office of the Attorney General, January 26, 2022).

Implications

This important and novel online reviews case, which is the first in the United States to challenge a company’s failure to post negative reviews, reflects the growing interest by American, Canadian, and other international enforcement agencies to counter deceptive marketing practices in the digital economy. This case also adds to the growing body of law and enforcement effort against anti-competitive algorithms by online sellers.
In addition, this case is a caution for both Canadian and international online sellers to ensure that online reviews are not false or misleading, and that algorithms are not used to create deceptive online claims (including by omission of material information, such as negative reviews).
Given that Canada’s Bureau is increasing its enforcement capabilities in relation to the digital economy, including the use of algorithms (both by online sellers and as a competition enforcement tool), it remains to be seen whether it will also follow the increasingly robust competition law enforcement and policies of other international agencies, particularly in the United States.
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Law stated as at 03-Feb-2022
Resource Type Legal update: archive
Jurisdiction
  • Federal (Canada)
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