On 25 June the Netherlands Consumer and Markets Authority (ACM) announced an investigation of fake accounts, fake reviews and fake likes. It is set to identify companies selling fake reviews and seize their customer data in order to stamp out such practices.
The ACM states that a number of Dutch companies supply fake reviews and fake social evidence to companies to be used on platforms such as Facebook, Instagram, YouTube and Google. It says that such reviews (ie reviews that are not based on true experiences or actual (existing) users) can mislead consumers about the qualities or characteristics of a certain product or service. It estimates the damage caused globally to actual advertising companies by such fake social evidence at €1.2bn.
The ACM issues a stern warning to the digital economy in its press release (available in Dutch here): 'If users or suppliers of misleading reviews refuse to cease their practices, the ACM can revert to other instruments such as imposing fines.'
The announcement of the ACM follows an earlier communication from the UK Competition and Markets Authority (CMA) in May 2020. The CMA announced that it had launched an investigation into several major websites to see whether they are doing enough to protect shoppers from fake and misleading reviews, focusing on:
- suspicious reviews (eg a single user reviewing an unlikely range of products or services);
- presentation of reviews (eg combining positive reviews for multiple products); and
- paid reviews (eg how websites handle reviews that were commissioned).
The initiatives of the ACM and CMA in the digital space come at a time when unfair commercial practices, including misleading online consumers, are a hot topic in Europe.
Since the outbreak of the COVID-19 pandemic, online shopping and online interaction with consumers have increased, leading regulators across Europe to monitor websites and platforms for such unfair practices.
This follows the wider trend in enforcement by regulators against companies for misleading consumers in the digital space, which has gained significant traction in the past year.
What’s next in the online B2C space?
We expect further broad investigations to be launched into online B2C practices by the ACM and other national agencies in Europe in the foreseeable future. For the ACM, online misleading practices are a key enforcement priority in 2020 and 2021, as set out in its agenda (the other priority being energy markets in transition).
The ACM published a 60-page set of guidelines on the protection of online consumers ('the guidelines') at the beginning of the year, available on the ACM website (both in English and Dutch). The guidelines deal with 11 manners in which online consumers could be misled, including by 'social evidence'.
In relation to 'social evidence', the guidelines emphasise that this influences consumers’ behaviour by accelerating the selection and purchasing process and that consumers reading (very positive) reviews would consider products and/or services less 'critically', being less likely to compare offerings.
The ACM notes that companies must '…clearly inform consumers about the processes and control mechanisms that it has built into the system in order to be able to make [a claim that reviews of the product relate to consumers that have actually purchased that product]. Does the business not have proper processes and control mechanisms in place to make that claim? Then it cannot claim or give the impression that the reviews come from real consumers.'
It remains unclear what would qualify as a 'proper process and control mechanism' and how that would need to be disclosed to consumers.
The 10 other manners discussed by the ACM in the guidelines are:
- price indications;
- personalisation of prices and offers;
- unfair business models for games;
- scarcity claims;
- unclear information: who will you be buying from and what will you buy?;
- unclear information on data protection;
- standard settings and hidden information;
- unfair order and presentation;
- difficult cancellations; and
- abuse of automatic behaviour.
