There is a remark widely used for differentiating Web1, Web2, and Web3: Web1 is read, Web2 is read and write, and Web3 is read, write and own. In Web2, people don’t have any control over their data or decide how the data are stored. Instead, companies often track and save user data without users’ consent.
To some extent, Web2 has been bringing a lot of convenience to people’s lives. Benefiting from Facebook and other social media sites, people are able to connect with people globally. Thanks to the advanced algorithms of Google and TikTok, people can easily find what they are looking for online. Even if people know that the internet giants are monetizing their data through ads, people are still willing to sacrifice a certain level of privacy for convenience and better user experiences.
However, as more privacy-related scandals of internet giants are revealed, users’ desire to hold and control their personal data has been reaching a boiling point. It is hoped that the birth and rapid development of Web3 will help people reach this goal through decentralized, distributed, and self-governing storage on the blockchain.
The mission sounds attractive, but it is not attractive enough for people to learn complicated blockchain technology yet. People need to feel connected and will feel tired of being isolated in the virtual world. Therefore, a strong and robust social relation graph is necessary for Web3 applications to reach a larger group of audience. Web2 companies can reach users via phone numbers and emails to keep users active and grow their user base through app stores and online ads. However, Web3 projects do not have a centralized database to store user information, and most DApps (decentralized apps) have their communities in Telegram, Discord, or other third-party platforms. Thus, traditional growth strategies are no longer working in this new era.
Relation Link Tool Suite hopes to build a multi-chain decentralized Web3 social graph to solve the issue. By design, there are four tools that are supposed to solve different pain points:
- Relation Graph access and query API enables users to connect to social graphs. The tool will be the most useful to developers who are hoping to add social attributes to their products. Through the built-in relationship protocol, users can create and manage their on-chain friends and followers list. Developers can also perform source code queries of authorized data to obtain relationship data results. With this tool, the lack of networking effects, a key bottleneck of growth widely existing among Web3 projects, should be partially solved.
- Relation Dashboard API is used to query Relation’s network-wide public data, including information on data controllers, gas consumption, DataSpace creation count, log security monitoring, and more.
- Modular social function components hope to support developers to independently call every modular feature on the Relation One social app, including P2P chat, group chat, invite sharing, stranger game matching, friend grouping, leaderboards, DAO, and more. With modular social function components, the next generation of DApps will be able to add social entertainment attributes, while keeping their community construction within their own apps instead of relying on other third-party platforms, and thereby a closed loop of user experience can be concluded.
- Multi-chain smart contract wallet solution: Relation Link Tool Suite develops a multi-chain smart contract wallet solution that allows multiple private keys to be stored and managed on Data Space for signing by the user’s unique identity authority. Instead of importing various private keys multiple times, users can avoid the redundant operation through a single authentication method. Given different DApps operating on different chains, the solution will simplify the usage across chains and integrate users’ relation graph that is currently everywhere.
The benefits for developers of those four tools are straightforward – developers can find, connect, analyze, and gain insights into Web3 relational data. From here, blockchain startups can quickly reach key seed users, save market launch expenses and reduce customer acquisition costs, while more mature teams can save human resources, money, and time from dirty data to focus more on their own business logic to create better value for the users.
SEE ALSO: StepN: Stable Tokenomics is the Key
If the story stopped here, the whole logic would remain the same as traditional SaaS suites in the Web2 world. Users act on products to provide data, and products get iterated from data. However, the key philosophy of Web3 is to reward everyone that contributes value to the system, including users who contribute their social graphs, which is widely known as X-to-earn. Relation Labs follows the rule and proposes a data-to-earn model. All social graphs generated by the tool suite will be stored in a decentralized manner, empowering data producers with 100% ownership. If users are willing to provide data value to DApps or related interests by giving authorization, they deserve to earn tokens for the data they contribute. The more data users contribute, the higher the value, the greater income they can earn, and the more value-added services of the platform’s recommended index they can enjoy. In other words, they can still exchange some personal information for better user experiences as in the Web2 era, but users can control how much information they are willing to reveal and how much they can earn.
I once discussed the role of a growth product manager in the Web3 era with several friends. Many of them mentioned a big transition for those who have been used to the Web2 workflow is from data-driven to intuition-driven, since Web3 is still at a very primitive stage. However, developers have witnessed the power of data, and they will not abandon data’s potential to bring exponential compound growth to the product. Data are not criminal, data analysis is not criminal, but plundering data that should have belonged to users is criminal. Web3 still needs data. When talented data experts are here, when frameworks for data analysis are here, people just need a tool to grab data and a tokenomics system to pay for data fairly.