FTC Settlement Illustrates Challenges with “Up to” Claims
“Up to” claims can be difficult to substantiate, in part, because the standard for substantiating those claims isn’t always clear. Over the years, the FTC, NAD, and courts have articulated different standards that are hard to reconcile with each other. For example, last month, we posted about a decision in which a three-judge panel with the Ninth Circuit determined that an “up to” claim reflected the “upper limit” of what consumers could expect and rejected the plaintiff’s assertions that consumers should “always” expect that. This month, the FTC announced a settlement that takes a different view.
In the context of a case that involves compliance with the FTC’s Business Opportunity Rule, the FTC challenged Arise Virtual Solutions’ claims that gig workers on its platform could earn “up to” $18 per hour. According to the FTC’s complaint, when Arise began citing that number in 2020, the average pay for jobs on its platform was just $12 per hour. In fact, the FTC alleges between 2019 and 2022, fewer than 1% of workers on the company’s platform made $18 per hour.
Among other things, the proposed settlement prohibits Arise from making any earning claims unless it has written materials to substantiate “that the claimed earnings are typical for consumers similarly situated to those to whom the claim is made.” The settlement doesn’t elaborate on what “typical” means, but it’s clearly a much higher standard than what the Ninth Circuit panel expected in its decision. It’s also not clear how that standard fits with other standards the FTC has articulated in the past.
Although Commissioner Ferguson voted to approve the complaint and stipulated order, he withheld judgment on what Section 5 requires for substantiation of “up to” claims, stating that the FTC “appears to have articulated at least three inconsistent standards” for those claims:
- In 1983, the FTC took the position that “up to” claims could be substantiated if “the maximum level of performance claimed could be achieved by an appreciable number of consumers.” (The term “appreciable number” wasn’t defined, but the Commissioner’s dictionary suggests that it has to be a noticeable, nonnegligible, amount.)
- In February 2012, in a settlement involving the energy-saving claims of five window companies, the FTC said those companies “must have competent and reliable scientific evidence to substantiate that all or almost all consumers are likely to achieve the maximum savings claimed.”
- In June 2012, the FTC released a report on “up to” claims. A press release accompanying the report claimed that the report “reinforce[d] the FTC’s view that advertisers using [“up to”] claims should be able to substantiate that consumers are likely to achieve the maximum results promised under normal circumstances.”
Commissioner Ferguson noted that these “shifting answers” result in a “monumental shift” in the FTC’s approach. Odds are that most companies feel the same way and are confused about the standard. After all, there’s a wide gap between an “appreciable number” and “all or almost all.” Chair Khan, however, doesn’t feel that way. In a separate statement, she suggests that there hasn’t been a shift at all and notes that the Commission assesses “up to” claims by analyzing whether they are “likely to mislead reasonable consumers under the circumstances.” That analysis is always going to depend on the context.
Where does this leave us? Unfortunately, there isn’t a clear answer. As both Chair Khan and Commissioner Ferguson noted, the answer is going to depend on the context of the claim. (It may also depend on who answers the question.) Some cases will be relatively easy to figure out. For example, in the context of the Arise case, it’s no surprise that the FTC determined that the company couldn’t substantiate the claim when fewer than 1% of users achieved the advertised result. On the other end of the spectrum, if the numbers were flipped, we can’t imagine the FTC would have had an issue. Most cases are in the middle, though, and those will require a careful analysis.