Meet the data brokers: the invisible companies profiting from your life 🤑

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In the first episode of this series, we established a simple fact: your smartphone constantly generates data that flows to actors you’ve never heard of. The natural question that follows is — what do they do with it?

The short answer: they sell you. Not you as a person, but you as a behavior. Your habits, your preferences, your hesitations, your routines. A profile of remarkable precision that you never built yourself and likely don’t know exists.

This is what this episode is about: understanding who the profile merchants are, how their trade works, and why Africa has become one of their most coveted growth markets.

From raw data to predicted behavior 🔄

To understand what happens with your data, you first need to understand the business model that drives it. American researcher Shoshana Zuboff, a professor at Harvard, named this model surveillance capitalism in her landmark 2019 book.

The logic works like this. Your data isn’t the final product. It’s the raw material. What gets extracted from it — predictions about your future behavior — is the real commodity. What you’ll buy, when, at what price, which message will tip you toward action. Those predictions are sold to companies that want to influence your decisions.

The cycle runs as follows: you generate data, it’s collected, processed by machine learning algorithms, converted into a behavioral profile, and that profile is monetized. Every digital interaction — a click, a pause in scrolling, an abandoned search — feeds the model. There is no stop point. The cycle never ends.

What makes this structurally different from traditional advertising is granularity. A billboard reaches everyone who passes it. A targeted online ad reaches you — at the precise moment an algorithm calculates you’re most likely to act, based on your mood signals, recent activity, and consumption history.

Data brokers: a $300 billion invisible industry 💼

There is a category of actor that most users are entirely unaware of: data brokers. These companies offer you no service. You’ve never contacted them. But they likely know where you live, your approximate income, your health status, your political leanings, and your purchasing habits.

Their business is to collect data from hundreds of sources — public records, social platforms, apps, online transactions, and data purchased from other brokers — aggregate it, and resell it to businesses, insurers, banks, employers, and government agencies.

The scale of the industry is rarely discussed in public debate. In 2025, the global data broker market was valued at approximately $300 billion, with growth projected to surpass $500 billion by 2033. It is an entire industry built on monetizing data you never directly provided to these actors.

Concretely: when you use a dating app, a health tracking app, or make an online purchase, it’s likely that a data broker somewhere receives a version of that information, aggregates it with dozens of other data points about you, and sells it on — without any notification to you.

Your data decides the price you pay 💸

Targeted advertising is the best-known use of your data. But it’s not the only one — and probably not the most impactful on your daily life.

There is a practice experts call personalized pricing or surveillance pricing: the price you see for a product or service is calculated based on what algorithms estimate you’re willing to pay.

The most documented example is air travel. Delta Air Lines announced in 2024 the deployment of an AI-driven personalized pricing system, targeting up to 20% of its ticket inventory by end of 2025. The airline’s president described the goal plainly: one price available on that flight, at that time, for you specifically. No fixed fare. A price calculated in real time from your purchase history, travel frequency, browsing behavior — and your estimated spending tolerance.

This extends well beyond aviation. Recent studies have documented similar practices in hotel booking, insurance, and e-commerce — where the displayed price can vary based on your device’s operating system, your geographic location, or simply whether you’ve viewed the product multiple times.

In March 2026, the U.S. House Committee on Oversight wrote to Booking Holdings seeking accountability for its dynamic pricing practices, citing evidence that its algorithms adjust prices based on users’ estimated « willingness to pay » — often without their knowledge.

Africa: the new data frontier 🌍

To understand why this issue is particularly urgent on the continent, it’s worth examining a strategy that major tech platforms have been deploying for years.

Facebook, Google, Amazon, and SpaceX have all invested heavily in connectivity infrastructure across Africa — undersea cables, satellites, subsidized internet access programs. The stated intention is to bridge the digital divide. The economic reality is more straightforward: every newly connected user is a new generator of behavioral data.

The stakes are enormous. Africa now represents more than 500 million mobile internet users — a massive reservoir of behavioral data that remains largely untapped compared to what platforms know about their users in Europe or North America.

What makes the situation more acute is the state of the regulatory environment. Major tech platforms exploit existing legislative gaps: in several African countries, personal data protection laws are either non-existent, inadequate, or poorly enforced. African users structurally benefit from far weaker protections than their European counterparts under the General Data Protection Regulation (GDPR).

In Cameroon, Law No. 2010/012 on cybersecurity and cybercrime provides the legislative framework. But its application remains limited, and its data protection provisions haven’t been updated in over fifteen years — in a digital landscape that has transformed entirely since then.

In practice, this means that the data of a user in Yaoundé or Douala circulates, gets aggregated and monetized, with legal safeguards far weaker than those afforded to a user in Paris or Berlin.

What a profile actually knows about you 🧠

Here is what a behavioral profile built from your data can reasonably reveal — without you ever having directly shared this information with anyone:

Your approximate financial situation, inferred from your spending habits, connection times, and the apps you use. Your health status, derived from your searches, the health apps you consult, and your location visits near medical facilities. Your political and religious convictions, deduced from the content you consume, the groups you follow, the people you engage with. Your psychological vulnerabilities, identified by the content you dwell on, the subjects that trigger reactions, the times of day when your engagement peaks.

This information doesn’t just serve to show you an ad for something you want. It determines the price you’ll pay, the credit you’ll be offered, the insurance coverage you’ll receive — and, as we’ll explore in the next episode, the decisions that governments can make about you.

The implicit contract paradox ⚖️

Most users, when confronted with these realities, express a form of unease — then conclude they have no choice. And to some degree, they’re right. Alternatives to major platforms are scarce, adoption against social network gravity is difficult, and terms of service are designed to be accepted unread.

But that resignation deserves scrutiny. It rests on a premise the industry has carefully constructed: the idea that you access these services for free and that your data is a reasonable trade-off. What this premise conceals is the true scale of the transaction — and the fact that a $300 billion industry has been built on an exchange you never explicitly agreed to.

In the next episode, we move beyond commerce. We examine what governments do with this same data. The stakes shift: this is no longer about charging you the maximum price for a plane ticket. It’s about watching you.

💬 Join the conversation: Have you ever noticed different prices for the same product depending on your device or location? Do you think tech platforms have a special responsibility toward their African users? Share your experiences in the comments.

This article is part of What You’re Worth, TechGriot’s series on the personal data economy.