I was one of the core team leads at Itheum a few years back before joining Cointelegraph, and the reason was simple – I love my data and wanted to own it.

A privacy-preserving data marketplace built on Ocean Protocol, in my opinion, will be the right answer here. Ocean Protocol has data privacy at its core, and the biggest difference is that you can use this protocol and its infrastructure to build products on top of it.

Ex: music DataNFT or a gym membership or a loyalty card programme.

How they work: data owners lock their raw data and only expose it to a compute environment (TEE/FHE/ZKP) that lets buyers run queries or algorithms without ever seeing or extracting the underlying data.

Buyers pay for insights and answers, not for the dataset. The platform never touches raw data, it proves the query ran correctly over unseen data via cryptography and can be explored via their on-chain explorer.

Why it’s a real business (in my opinion): it opens a market that basically can’t exist in Web2, ie selling proprietary/sensitive data (health records, financial data, token-holder behavior, supply chain) that owners would never hand over because there was no way to guarantee it wouldn’t be scraped or leaked.

Privacy is not a feature here, it is the entire reason the transaction is possible. You collect a marketplace fee on every insight sold and have a token based economy to help you scale as a solution.

What makes it different from a normal Web2 model:

– Web2 model is extractive: the platform collects your data, monetizes it, and privacy is a compliance checkbox (a long privacy policy telling you what they take). You are the product.

– This model is additive: the customer pays money to access data, and the differentiation is cryptographic proof of non-exposure. Privacy is the thing being sold, not the thing being waived.

That inversion is the crux. The biggest difference is the core of their infrastructure, data tokens, DataNFT and their extensive ecosystem.

Brave Rewards is a useful Web3 example because privacy forms part of the advertising transaction. Users opt into ads, matching happens on their device, and their browsing activity does not reach Brave or advertisers. Advertisers buy attention, while users receive BAT and can pass tokens to publishers or use them elsewhere. The business model therefore shares value without first building a central behavioural profile. Its real differentiator is a system that avoids requiring personal data for relevance and measurement. That distinction matters because many Web3 products decentralise payments while retaining conventional data extraction.

A strong example of a Web3 business model built around privacy is decentralized identity, where the product helps users prove something about themselves without handing over all of their personal data. The clearest version is a wallet-based identity or credential system that lets a person verify facts like age, account ownership, membership, or reputation through selective disclosure instead of uploading full documents to a centralized platform.

What makes that model different is that privacy is not a feature added later. It is the core reason the product is useful. In a traditional platform, the business often captures and stores identity data, then monetizes access, retention, or profiling around that data. In a privacy-first Web3 model, the user holds the credential and only shares the minimum needed for a transaction. The platform’s value comes from verification infrastructure, credential issuance, integrations, and trust layers, not from building a large centralized database of user information.

A practical example would be a Web3 age or identity verification service for marketplaces, communities, or fintech onboarding. Instead of collecting a full ID every time, the user could present a cryptographic proof that confirms they meet a requirement without exposing unnecessary personal details. The business can charge B2B fees for verification rails, API access, issuer partnerships, premium trust signals, or enterprise integration, while reducing the liability and storage burden that come with centralized personal data collection.

From my perspective in privacy-focused consumer education, that is the real distinction: the model aligns incentives better. When the company does not need to warehouse sensitive user data to create value, it lowers both privacy risk and the temptation to over-collect. In Web3, the strongest privacy businesses are the ones where user control, minimal disclosure, and portable identity are part of the economics, not just the marketing.

A Web3 identity management service that treats data privacy as its core value proposition is one that enforces data minimization, strong encryption, role-based access controls, and explicit user consent with the ability to revoke access. What makes this model different is its deliberate alignment with GDPR, HIPAA, and CCPA principles so users and relying parties operate under clear privacy rules. By limiting shared identifiers to what is strictly necessary and protecting stored identity material with robust encryption, the service reduces exposure and preserves user trust. For our small-business clients, that approach creates transparent, auditable access controls and simple user-driven mechanisms to restrict or remove data disclosures.

Brave Rewards is a strong example of privacy becoming the transaction design rather than a policy promise. Users opt into privacy-respecting advertising and can receive BAT, while verified creators can receive BAT contributions. The model monetises attention without requiring a conventional cross-site profile to pass between intermediaries. That is what makes it different. Consent, value exchange and settlement are visible to participants instead of hidden inside an advertising supply chain. As a digital marketer and AI operator, I find the design lesson more important than the token. Keep sensitive data close to the user, move only the minimum information needed and reward permission directly. A Web3 label adds little if the business still centralises behavioural data and merely settles payments on-chain.

Brave’s advertising and Basic Attention Token ecosystem is a useful example. The distinction I would emphasize is where ad matching happens. Brave says matching takes place on the user’s device, rather than requiring the advertiser to receive that person’s browsing history. Eligible Brave Rewards users can earn BAT from participating in its advertising system.

From a marketing perspective, that changes the proposition: sell access to relevant attention while reducing the need to collect a detailed personal browsing profile. Privacy is part of the product’s operating design and user appeal, not simply a statement attached to an otherwise conventional tracking model.

The token is not what makes the matching private. The on-device processing and the way reporting is designed do that work; BAT supplies a rewards component. Keeping those two ideas separate is essential when evaluating any Web3 privacy claim. A blockchain connection does not automatically make a service private, and wallet or account requirements still deserve their own scrutiny.

What makes this example interesting to me is that it attempts to give advertisers a commercially useful service without making individual browsing-history collection the core bargain. This is an assessment of Brave’s documented model, not a claim that we ran a Brave campaign or measured its results.

The most effective Web3 business model that I’m aware of is Railgun. Railgun is a decentralized privacy protocol for Ethereum that shields wallet balances and transaction histories using Zero Knowledge cryptography. It is different because it verifies transactions without revealing any data regarding the transaction, it eliminates third parties because users have their own encryption keys, and lets users generate viewing keys to prove legitimacy without exposure.

Most Web3 privacy pitches fail because they lead with the tech and bury the business model. The ones that work flip that.

Ocean Protocol is the clearest example. They built a data marketplace where companies can monetize datasets without ever exposing the raw data. The mechanism is compute-to-data: the algorithm goes to the data, not the other way around. A pharma company can sell access to patient records for research purposes without a single record leaving their infrastructure. GDPR compliance becomes a feature, not a constraint.

What makes it different from a standard SaaS play: the privacy guarantee is the product. Remove it and the entire value proposition collapses. Most Web2 companies treat privacy as a compliance checkbox. Ocean made it the reason the transaction exists at all.

I’ve watched similar logic play out at a smaller scale running Pageloot, where 20,000+ brands across 110 countries trust us with their scan analytics. The moment we started being explicit about what data we store versus what we don’t, enterprise procurement conversations got shorter. Transparency about data handling isn’t a legal department problem, it’s a sales tool.

The Web3 projects that survive the next cycle will be the ones where privacy isn’t a differentiator you add on top. It has to be load-bearing architecture from day one.

A privacy-first Web3 publishing cooperative could replace surveillance advertising with reader-held preference credentials. A reader proves interest in climate policy, local sport, or business travel without revealing browsing history, name, or a cross-site identifier. Publishers receive campaign eligibility counts and conversion proofs, while readers choose whether to accept a paid offer or remain anonymous.

Advertisers fund qualified reach rather than dossiers, and publishers gain a revenue stream that is less vulnerable to browser changes and consent fatigue. I require strict controls around linkable wallet activity, since transaction patterns can quietly recreate identity. The differentiator is economic, not cosmetic. Privacy changes what is traded, from behavioural records to verifiable audience fit.

Aztec is a useful example of how the privacy conversation in Web3 is evolving.

The interesting point is not privacy as an end in itself, but the ability to control what is public, what remains confidential and what can still be verified. That becomes particularly relevant as blockchain infrastructure is considered for areas such as payments, treasury, tokenised assets and other financial applications.

Traditional financial markets are not fully transparent environments. Businesses need confidentiality around counterparties, pricing, positions and commercially sensitive transactions, while still operating within clear regulatory and reporting frameworks.

Privacy infrastructure is therefore likely to become an important part of the broader question around how more financial activity can move on-chain.

Aztec is one of the businesses working on that problem, through technology designed to combine public and private execution. It is also building capability beyond the technical team, including across finance, legal and commercial functions, which is interesting from an organisational perspective.

It is still an emerging area, and commercial adoption will ultimately determine which models succeed. But the underlying issue is a significant one: if blockchain is going to support a broader range of financial activity, the market will need credible ways to combine transparency, privacy and control.

A strong real-world example is the European Blockchain Services Infrastructure (EBSI) and its verifiable-credentials model. Rather than treating personal information as a centralized database asset, the model keeps credentials in a digital wallet while blockchain infrastructure provides a trusted way to verify authenticity. The European Commission notes that personal data is not stored on the ledger, while holders control what information is shared and with whom. The key difference is that privacy becomes part of the business architecture, not simply a security feature added afterward. A university, employer, bank, or government agency can verify a claim without necessarily receiving an entire identity record. Zero-knowledge and selective-disclosure approaches can further allow verification of a fact without exposing the underlying data. From a business-model perspective, the value comes from reducing dependence on centralized data custodians while creating trusted, reusable credentials. That distinction is particularly important as Web3 moves toward user-controlled data models; NIST’s 2025 Web3 security report similarly identifies user ownership and decentralized data management as central characteristics of the proposed Web3 paradigm.

A strong Web3 business model built around data privacy is a decentralized identity platform where users own their credentials instead of handing personal information to every company they interact with. What makes this different is that a business can verify something about a customer—such as their age, eligibility, or certification—without necessarily collecting and storing all of the underlying personal data.

Running a metal plating business has taught me that the safest sensitive information is often the information you never needed to collect in the first place. We work with customer specifications and proprietary project details, and I’ve seen how limiting access and keeping only what is necessary reduces unnecessary exposure. Web3 can apply that same principle at a much larger scale: businesses verify what they need, users retain greater control over their information, and privacy becomes part of the product’s value rather than an afterthought.

Brave rewards changes user behavior towards attention being rewarded with money. One researcher studied people using Brave and found that when they knew they were getting paid, they viewed it differently. People that were receiving BAT felt as if the ad wasn’t interrupting them. After trying out Brave rewards, one advertiser stated that they saw an increase of 56% with users on Brave that were receiving BAT vs those that weren’t. By allowing the user to feel as if they were being fairly rewarded for their attention, you increase the chance of them engaging. When you allow a user to feel as if your reward is worth their time, they will pay attention. Most people believe that because the user is getting something for free, they should allow themselves to be interrupted. By rewarding your user for their time, they will pay more attention to what you’re selling. Its similar to how web3 allows us to procure things instead of taking. You are now procuring users attention by paying them to watch. Most people thought you could take the attention of the user and use it however you please. We have shown that if you reward your users, they will pay more attention to your message. After learning about the Brave program, one advertiser stated that by rewarding the user with a fair amount of value, they will pay attention to what you’re trying to sell them. If you’re paying the user to look at your message, they are going to think higher of you. Once you learn to market to users who want to be rewarded for their time, you’re going to see higher engagement.

A strong Web3 business model built around data privacy is a decentralized data marketplace where users control access to their personal information and can choose whether to share or monetize it. What makes this different is that the business does not need to hold a massive centralized database of sensitive customer information; blockchain-based permissions and encryption can keep control closer to the user. In my own business, I’ve seen how much trust matters when homeowners share addresses, property details, photos, and project information, and that trust disappears quickly when people feel their information is being passed around without their knowledge. A Web3 platform could apply the same principle by letting customers grant specific, time-limited access to their data rather than permanently surrendering it. The practical advantage is that privacy becomes part of the product itself instead of simply being buried in a privacy policy. That creates a different value proposition: the company can generate revenue by facilitating trusted data exchanges while giving users greater visibility and control over who gets their information.

The clearest example is **self-sovereign identity (SSI)** systems like Polygon ID or Sovrin. Here’s what makes them different: instead of a company (LinkedIn, Google, Equifax) holding your credentials centrally, you control cryptographic proofs of your identity on a blockchain or personal device. When you need to prove something about yourself–your age, accreditation, credit history–you send only that specific proof, not your entire identity profile.

The business model works because:

1. **Users reduce exposure** — you’re not giving Facebook your medical history or home address; you’re sharing a zero-knowledge proof that you’re “over 18” or “accredited investor”

2. **Enterprises reduce liability** — they don’t store sensitive data, so no breach risk or GDPR compliance headaches

3. **Wallets and verifiers monetize** — instead of data brokers profiting from selling your personal data, credential wallets and verification services generate revenue

What’s fundamentally different from Web2: privacy isn’t something the company *promises* to protect (and sells anyway). Privacy is **built into the architecture**–you own the credentials, control what’s shared, and can audit every verification. The company profits from service, not surveillance.

This works at scale for KYC, employee verification, supply chain credentials, and insurance claims. Privacy stops being performative compliance theater and becomes the actual product.

A publisher made the switch to Brave Rewards over using ad-networks to make money off their site because they can receive payment directly from their audience. It opened up their mind to making better quality content. Not focused on view count or social shares but what the reader would get out of it. Most online publishers will do anything to try and gain that attention. Since ad networks take 70% of what your content earns. You have to drive more views to make more money. With Brave Rewards you can focus on making quality content that people will want to reward. That’s what this publisher said about knowing her audience could give her BAT. She could focus on creating quality content for her audience instead of just trying to gain more views. When your content can make money based off what people think it’s worth. You’ll produce higher quality content. When using ad networks you’re trying to please the advertisers not your readers. Which can sometimes contradict one another. Another person who tried brave rewards stated that they were able to focus more on quality content. Instead of pushing quantity. When you allow your reader to pay you for what they enjoy. They will send you more for better content. That’s how web3 can be beneficial to business. If I know I can make more money from my readers. Then I will produce higher quality content for my readers. And if you don’t have privacy you won’t be able to focus on creating that quality. Digital marketing should know that. As more websites switch to allowing their audience to pay them directly. They will need to change their marketing tactics to fit.

A strong Web3 business model that uses data privacy as its core value proposition is a decentralized data marketplace where individuals retain ownership of their information and grant businesses limited, permission-based access. What makes this different from traditional data platforms is that companies don’t automatically gain permanent control of the underlying customer data; blockchain-based permissions and privacy technologies can let users decide what is shared, with whom, and for how long.

In logistics, I’ve seen how valuable shipment and customer data can be, but I’ve also seen why businesses are increasingly careful about where that information goes. We’ve worked with customers who needed multiple parties involved in a shipment while still wanting sensitive commercial details restricted to only those who actually required them. A privacy-first Web3 model applies that same principle at the infrastructure level: verify or exchange only what’s necessary rather than handing over an entire dataset. For businesses adopting this approach, I would focus on making privacy useful and measurable—give customers clear control over permissions, minimize the data collected, and make consent easy to revoke.

Web3 business models mark a major improvement over the enterprise’s role, changing it from being a Data Custodian to being a Verifier. The best example of this change is the introduction of Self-Sovereign Identity (SSI) in accordance with the W3C Decentralized Identifier (DID) standards. Traditional companies keep tons of Personally Identifiable Information (PII) on their servers in order to perform transactions, which creates large security vulnerabilities and a significant amount of regulatory requirements. Meanwhile, within a privacy-oriented Web3 model, the company’s business model revolves around the verification of cryptographically verified claims instead of keeping physical data. This leads to a significant decrease in costs and risks of data management for the business while increasing user trust.

This model is unique due to the implementation of Zero-Knowledge Proofs (ZKP) together with the W3C Verifiable Credentials framework. Selective disclosure makes it possible for the user to prove only that he/she meets the certain criteria, for example, that he/she is a resident or possesses a particular profession, while keeping information about the sensitive data undisclosed. A vivid example of this is a situation where a vendor in a multi-party supply chain is able to prove to all his partners that he has successfully undergone a sustainability audit by means of a single verifiable credential without revealing any details of the audit.

This architecture solves a coordination problem leading to the appearance of data silos and reconciliation problems in global operations. With the help of DIDs, it becomes possible for organizations to interact within DPKI using their public keys without the necessity of trusting any third party with central authority. The main advantage of this approach is the decrease of the attack model of the company and the elimination of redundant data collections.

Decentralized storage networks where users hold their own encryption keys represent a genuinely different privacy model than traditional cloud storage, where the provider technically can access stored data regardless of stated policy.

In these models, files get encrypted client-side before upload, and the storage network only ever holds encrypted data it cannot decrypt without keys the user retains independently.

What makes this different from privacy-marketed centralized storage is structural rather than promissory. A traditional provider says they won’t access your files. A decentralized network with user-held keys technically cannot, regardless of intent or policy changes down the line.

That distinction matters considerably during acquisitions, policy changes, or legal compulsion scenarios, situations where a centralized provider’s privacy commitment can shift or be overridden entirely, while a user-held-key architecture remains unchanged by any of those external pressures.

The privacy protection persists independent of the platform’s future decisions, which is a fundamentally different guarantee.