At the end of 2023, Meta (parent company of Facebook, Instagram, and WhatsApp) introduced a new model in Europe giving users a choice regarding the use of their personal data in advertising. Unofficially known as "Pay or Consent," this model offers two alternatives:

Paid subscription without personalized ads: the user pays a monthly fee (about €7.99 per month) to browse these social networks without personalized advertising, meaning Meta commits not to use the subscriber's personal data for ad targeting purposes. In other words, those who pay have extra privacy.

Free use with personalized advertising: the user chooses to continue using the platforms for free, but consents to their personal data being collected and processed so that the displayed ads are targeted according to their profile and activities. In this case, Meta gathers information such as activities on networks, contacts, and the user's device data to target the displayed advertising.

The subscription was initially launched in November 2023 for users in the European Union, European Economic Area, and Switzerland. Initially, the standard advertised price was €9.99 per month (on the web version) or €12.99 on iOS/Android, covering one account; additional linked accounts would incur an extra monthly fee. However, in November 2024, after discussions with regulators, Meta reduced these prices by approximately 40%, to €5.99 (web) and €7.99 (mobile devices) per month, with €4-5 for each additional account. This reduction aimed to make the service more accessible and address the concerns of European authorities.

Why did Meta adopt this measure? (GDPR and regulatory pressure)

The implementation of the paid model in Europe was not voluntary, but driven by strict regulatory requirements. Two European standards are at the center of this discussion: the General Data Protection Regulation (GDPR) and the Digital Markets Act (DMA). The GDPR, in effect since 2018, reinforced the need for free, informed, and unambiguous consent for the processing of personal data – especially for purposes such as behavioral advertising. The more recent DMA imposes specific obligations on big tech companies to promote competition and greater user protection. For example, the DMA began to prohibit extensive user tracking for targeted advertising without explicit consent.

In the European context, the question arises: could the Brazilian LGPD enforce a similar model here?

Although Meta has not yet officially implemented an ad-free subscription program in Brazil, there are indications that this may change. The main driving force would be precisely the evolution of the LGPD application. In recent years, the National Data Protection Authority has become more active and strict in overseeing large technology companies. In July 2024, for example, the ANPD ordered the suspension of parts of Meta's new privacy policy in Brazil, which allowed the use of data published by users to train artificial intelligence systems, citing evidence of violations of the LGPD. In this decision, the authority pointed out issues such as inadequate legal basis, lack of transparency, and limitations on the rights of data subjects, including imposing a daily fine for non-compliance.

Although this specific case was about data use for AI, the message is clear and transferable to other areas: the ANPD does not hesitate to intervene against practices it considers abusive or lacking legal support. Personalized advertising could come into focus in the future.

Another factor to consider is international alignment. Global companies tend to seek a certain uniformity in policies, also for operational practicality. If Meta has already built the infrastructure for a "no ads" subscription model in Europe, it is plausible that they are considering expanding it to other regions according to regulatory demand.

Although there is not (yet) an explicit obligation in the LGPD to offer an ad-free version, the law does impose a duty of full transparency regarding which data is collected and for what purpose. If a social network extensively uses personal data for advertising profit, this must be very clear to the user, who in turn has the right not to consent or to revoke given consents. The lack of alternatives – that is, forcing the user to accept targeted advertising or abandon the service – can be interpreted as invalid consent (due to coercion) under the LGPD. In this sense, offering a paid alternative without data collection can be seen as a way to validate the consent of those who choose to continue with the free version. It wouldn't be surprising to see the ANPD or even the Judiciary questioning the freedom of Brazilian users' consent if they do not have a real choice. The existence of a paid subscription, although potentially controversial (since it involves charging for privacy), at least materializes a choice for the holder – which can be legally defensible.

So, can this "pay or consent" model happen in Brazil? In theory, yes, and there are both legal and strategic arguments to believe that it is only a matter of time before we see something similar.

On the other hand, it is necessary to note challenges. Brazil, unlike the EU, does not have a unified regulatory ecosystem like GDPR + DMA + DSA; the LGPD operates alone on the issue. There are also economic considerations: the free ad-supported model is what enables broad access to social networks. Charging for a subscription may not be well received by a large portion of Brazilian users, and Meta naturally fears losing engagement (and advertising revenue) in an important market. Thus, it is possible for the company to adopt a gradual approach: first, increase transparency and facilitate opting out of personalized ads; then, if necessary, test an ad-free subscription with small groups or specific regions, and only then launch more broadly if there is concrete regulatory pressure.

In conclusion, the LGPD already has the potential to transform the way digital marketing is conducted in Brazil. If the "novelty" of paying €7.99 a month for your privacy seemed distant, today it is no longer unthinkable. The European Union has shown a path, and although Brazil will not simply copy and paste solutions from there, the underlying logic is the same: giving the actual user decision-making power over their data. Privacy, compliance, and digital law professionals should stay alert: they may soon have to advise their clients or companies on subscription models versus personalized ads here as well. And when that happens, it will be the confirmation that the data protection culture, driven by the LGPD, has indeed changed the rules of the game in the Brazilian market.

High investments directed at sophisticated strategies, persuasive texts, and creative campaigns do not always translate into the expected results. This frustration, quite common in the market, is often not related to the quality of execution but rather to a frequently overlooked element: outdated contacts.

More than just a database, a qualified, lively, and reliable contact list is the true foundation of any successful corporate campaign. Ignoring this point can compromise not only the delivery of actions but also the relationship with the target audience and, consequently, the return on investment (ROI).

Managers and decision-makers recognize the value of data as a source for strategic actions. However, having a large volume of information is useless if there is no guarantee that this data is true, valid, and up-to-date. According to a Validity study, 75% of respondents state that approaches based on inaccurate or outdated data lead to customer loss and hinder the actual measurement of action results.

The problem goes beyond incomplete registrations or typing errors. The real bottleneck is the lack of monitoring of the communication journey. Many contacts return to the relationship cycle after a period of inactivity, but through other numbers or channels. Not recognizing this pattern prevents the company from adjusting its actions in real time and compromises the exploitation of opportunities. Without a continuous validation structure and proper integration between the databases and the channels that consume the data, the database quickly becomes outdated — even if it appears to be large.

The lack of governance over data and the absence of mechanisms to prioritize the right number for each CPF generate direct impacts: poorly targeted campaigns, ineffective attempts, wasted budget, operational rework, loss of performance, and in more sensitive cases, strain on the customer relationship due to persistent contacts with incorrect or repeated numbers.

Furthermore, the lack of intelligence about return behavior—how and when the customer re-engages—hinders the development of more effective re-engagement strategies. The result is an operation that attempts, without criteria, multiple numbers for the same CPF, consuming resources, team time, and running legal risks such as violations of LGPD due to inappropriate contacts.

Although it may seem like a complex problem, this scenario can be reversed with methodologies that prioritize the intelligent use of data. The key is to direct efforts toward the validated number, with the highest likelihood of response and aligned with the relationship history with that CPF. Having an enriched, up-to-date, and strategically built database is essential to ensure that the message reaches those who truly matter — the right phone, through the right channel, at the right time.

In this context, technology plays a central role, not only as a tool for point validation but as part of a continuous relationship framework. Models based on inference and behavior, combined with a daily feedback system, make the contact database a living asset — capable of learning from data and continuously improving.

More than identifying if a number is active, it is essential to recognize which contact has the greatest potential to generate results. This means reducing attempts, increasing the effectiveness rate, protecting the brand's image, and offering a more relevant experience to the customer.

The use of data-driven decision layers is what differentiates high-performance operations from those that just broadcast to everyone. Therefore, it is essential for companies to adopt models that not only clean the data but also learn from it. What worked? When did it work? And what could work as new?

Treat the contact database as a strategic asset — integrating external sources, historical behavior, carrier validation, and channel preferences — is the safest way to generate real value. After all, no one likes to be impacted by a communication that doesn't make sense for their moment or profile. Just as excessive attempts harm the customer, they also harm the company.

Avoiding this type of wear requires consistency, intelligence, and structure. A living database is one that evolves over time, adapts to customer behavior, and delivers value both to the sender and the receiver.