In the Web3 data ecosystem, the growth path of small roles (individual users, small and medium projects, offline merchants) often faces the bottleneck of 'data capability lag'—as business develops, their needs for data analysis, resource docking, and tool usage will continuously upgrade, but existing data services are mostly 'fixed models,' unable to dynamically match growth stages: individuals from 'novice' to 'experienced users' still use basic data tools; small and medium projects from 'startup' to 'expansion' lack suitable resource support; offline merchants from 'single store' to 'chain' cannot keep up with scale expansion in data management. This 'asynchronous development of data capabilities and business growth' leads to small roles 'failing at critical growth nodes,' missing development opportunities. Chainbase, as a decentralized data infrastructure, is building a 'growth-oriented data service network' through a full-cycle system of 'growth stage identification - dynamic demand matching - service flexibility upgrade,' allowing small roles to advance their data flow capabilities in sync with their business, avoiding 'falling behind during growth.'
I. The 'Data Capability Gap' in the Growth of Small Roles in Web3: Three core pain points
The growth of small roles is a dynamic process, but the 'static nature' of existing data services cannot adapt to changing needs, leading to 'capability gaps' at different growth stages, constraining development speed.
1. Individual Users: Mismatched growth stages and tools, advancement unsupported
Individual users' participation in Web3 typically goes through three stages: 'novice - advanced - experienced,' but data tools are mostly 'generic,' failing to match stage needs: novices need 'zero-threshold task guidance tools' but receive a 'fully functional data platform' filled with jargon, making it difficult to start; advanced users want to try 'data combination monetization' (such as combining long-term authorization with short-term tasks) but cannot find 'revenue combination management tools' and must rely on manual trial and error; experienced users need 'data risk management tools' (such as multi-wallet data integration, revenue fluctuation warnings), but existing tools can only meet basic queries, failing to support in-depth operations. For instance, a user grows from a novice to an 'experienced participant earning 2000 C monthly,' needing to integrate revenue data from three wallets and set fluctuation warnings, but due to unsupported tools, can only manually tally every day, which is time-consuming and prone to error; an advanced user wanting to try 'niche public chain data arbitrage' misses the window due to a lack of targeted tools. Tools lagging behind growth results in individual users encountering a 'ceiling' in revenue growth.
2. Small and Medium Projects: Disconnection between development stages and resources, expansion without assistance
The lifecycle of small and medium projects includes 'startup - validation - expansion' stages, with significant differences in data resource needs at different stages, but existing resource support is mostly 'one-size-fits-all': the startup period needs 'low-cost data sources + lightweight development tools,' but can only apply for 'high-threshold enterprise-level resources,' which are too costly; during the validation period, 'small-scale merchant testing resources' are needed, but they cannot connect with precise target groups to validate product value; during the expansion period, 'cross-regional data sources + bulk merchant connection channels' are needed, but existing resources have limited coverage, making rapid expansion difficult. For example, a certain startup project wants to develop a 'restaurant NFT redemption tool' and needs low-cost access to multi-chain NFT data, but due to high resource thresholds, can only give up support for some blockchains, rendering the product's competitiveness inadequate; a validation period project wants to find 10 community coffee shops to test the tool, but takes 2 weeks to connect with only 2 stores, missing the best time for product iteration; a certain expansion period project wants to enter the Southeast Asian market but, lacking local data sources and merchant resources, puts its expansion plan on hold for 3 months. Resources lagging behind development cause small and medium projects to grow at a 'half-beat' slower pace.
3. Offline Merchants: Imbalance between scale stages and management capabilities, expansion lacks assurance
The growth of offline merchants often upgrades gradually from 'single store to multiple stores to chain,' but data management capabilities often lag behind scale expansion: during the single store period, 'simple redemption tools' can meet needs, during the multiple stores period, 'cross-store data synchronization tools' (such as member data sharing, universal discounts) are needed, but no suitable solutions are found; during the chain period, 'data middle-platform management tools' (such as regional customer flow analysis, multi-brand data integration) can only support single store operations, failing to enable scalable management. For example, a coffee shop expanded from one store to three, with member data scattered across store systems, and customers could not enjoy discounts when consuming across stores, leading to a 20% increase in member loss rate; a chain supermarket expanded to five stores and wanted to analyze consumption preferences in different regions to optimize product selection but could only rely on experience for decision-making due to data not being integrated, resulting in a 15% decrease in product selection accuracy. Inadequate management capabilities lagging behind scale turn merchants' expansion into a 'burden,' even dragging down operational efficiency.
II. Chainbase's 'Growth-Oriented Data Service' System: Dynamic Adaptation with Three Core Designs
Chainbase's innovation is not about providing 'more tools' but about building a service mechanism that 'automatically adapts to growth,' letting small roles receive precise data support at every growth node through 'stage recognition - demand matching - service upgrading.'
1. Individual Users: Growth ladder toolkit, capabilities progress with stages
To meet the growth needs of individual users, Chainbase has launched a 'ladder-type data toolkit' that dynamically matches tools according to 'novice - advanced - experienced' three stages, avoiding 'being ahead or behind':
• Novice Period: Zero-threshold entry tools: Includes '10-minute getting started tutorial' (using 'checking bills' to compare 'checking on-chain data'), 'one-click task matching tool' (automatically recommending low-difficulty, high-security basic tasks, such as 'marking simple on-chain transactions'), 'real-time revenue reminders' (notifying users immediately when task revenue is credited), helping novices quickly establish basic capabilities.
• Advancement Period: Combination value-added tools: Provide 'Revenue Combination Planning Tool' (automatically generates revenue schemes of 'long-term authorization + short-term tasks' based on user time and risk preferences), 'Niche Opportunity Discovery Module' (real-time push of niche public chain data tasks, high-yield arbitrage opportunities), 'Data Reuse Management Tool' (statistics on the number of times data is reused and revenue, optimizing authorization strategies), supporting users to shift from 'single revenue' to 'diversified value-added.'
• Experienced Period: Specialized control tools: Develop 'multi-wallet data integration dashboard' (real-time aggregation of revenue, authorization, and risk data from multiple wallets), 'revenue fluctuation warning system' (automatically alerts and recommends replacement directions when revenue from a certain type of data drops over 20%), 'data risk assessment tools' (regularly scans the security risks of authorization data, such as 'certain demand-side compliance qualifications expiring'), meeting the in-depth operational needs of experienced users.
The system automatically identifies the user's stage through 'growth behavior recognition': novices unlock advanced tools after completing 10 basic tasks; advanced users gain access to experienced tools when their monthly average revenue exceeds 1000 C. By May 2024, 5.55 million individual users have achieved capability advancement through the ladder toolkit, with the monthly average revenue increase for users at different stages reaching 30%-60%, and the growth cycle from novice to experienced shortened from 6 months to 3 months.
2. Small and Medium Projects: Phased resource support to assist growth throughout the cycle
To meet the lifecycle needs of small and medium projects, Chainbase has built a 'phased resource support system,' providing differentiated resources according to 'startup - validation - expansion':
• Startup Period: Low-cost launch resources: Provide '3 months of free trial basic data sources' (covering basic data interfaces for mainstream public chains), 'no-code development kits' (including tool templates, front-end components, improving development efficiency by 80%), '10,000 C startup subsidy' (for tool testing and initial promotion), lowering startup costs.
• Validation Period: Precise testing resources: Open the 'Vertical Scenario Merchant Pool' (such as 'Community Catering Merchant Pool' and 'Niche GameFi Guild Pool'), projects can apply for 10-20 precise testing targets; provide 'User Feedback Collection Tool' (automatically summarizes usage suggestions from testing users and generates optimization reports), helping projects quickly validate product value.
• Expansion Period: Resources for scalable expansion: Connect 'cross-regional data sources' (such as Southeast Asia, local public chain data in Latin America), 'bulk merchant connection channels' (cooperating with regional business associations to connect with 50+ merchants at once), 'localized operational support' (providing compliance guidelines and user preference analyses for target markets), supporting projects to rapidly expand markets.
Projects obtain corresponding resources through 'stage achievement certification': tools in the startup period unlock validation period resources after completing tests with 5 merchants; validation period users receive expansion period support after a repurchase rate exceeding 60%. Already, 32,000 small and medium projects have achieved growth through this system, with the cycle from startup to validation reduced from 3 months to 1 month, and the efficiency of merchant connection from validation to expansion increased by 70%. A certain 4-person project leveraged expansion period resources to cover 100 merchants in Southeast Asia within 3 months, tripling monthly revenue.
3. Offline Merchants: Scalable data management solutions adapted for scale expansion
In response to merchants' scale growth needs, Chainbase has designed a 'flexible data management solution' that dynamically upgrades functions along 'single store - multiple stores - chain':
• Single Store Period: Lightweight operational tools: Includes 'simple NFT redemption tools' (10 minutes to deploy, supports QR code redemption), 'basic member data dashboard' (statistics on member count, consumption frequency), 'event effectiveness analysis module' (automatically generates participation rates and revenue growth data for NFT events), meeting basic needs for single stores.
• Multiple Stores Period: Cross-store collaboration tools: Provides 'cross-store data synchronization system' (real-time sharing of member data and discount rules, allowing customers to enjoy benefits when consuming across stores), 'regional operational dashboard' (comparing NFT redemption rates and member growth across different stores, identifying operational differences), 'employee permission level management' (employees from different stores can only view their own store's data, ensuring security), solving cross-store collaboration issues.
• Chain Period: Data middle-platform tools: Develop 'holistic data integration platform' (integrating member, consumption, and customer flow data across multiple brands and regions), 'smart product selection/marketing module' (recommending products and customizing promotional activities based on regional consumption preferences), 'supply chain data linkage tools' (connecting supply chain systems to optimize inventory with sales data), supporting chain management.
Merchants upgrade automatically upon meeting scale standards: After single store membership exceeds 500, multi-store tools are automatically unlocked; after the number of stores exceeds 5, expansion period plans are pushed. Already, 200,000 offline merchants have achieved scale expansion through flexible plans, with cross-store consumption rates of members increasing by 80% during the multiple stores period, and product selection accuracy increasing by 30% during the chain period. A certain chain milk tea brand leveraged data middle-platform tools to increase the member repurchase rate from 35% to 55%, with regional revenue growing by 40%.
III. The Ecological Value of Growth-Oriented Services: Small Roles from 'Growth Bottlenecks' to 'Continuous Advancement'
Chainbase's 'Growth-Oriented Data Service' system is not about 'one-time resource provision,' but 'accompanying small players throughout their growth cycle,' making data capabilities a 'growth booster' rather than a 'bottleneck,' with value reflected in the advancement path of each role.
1. Individual Users: From 'Revenue Ceiling' to 'Continuous Growth'
Individual users are no longer limited by outdated tools, and through the ladder toolkit, can receive adaptive support at each growth stage: novices can quickly get started and avoid 'giving up due to difficulty'; advanced users can master diversified monetization and break through 'single revenue limitations'; experienced users can achieve fine-tuned operations, reducing 'revenue fluctuation risks.' For example, a user progresses from earning 300 C monthly as a novice to achieving a monthly income of 1200 C by utilizing an advanced toolkit for 'long-term authorization + niche tasks.' After entering the experienced stage, through multi-wallet integration and risk warnings, revenue stability increases by 70%; even if certain data revenue declines, strategies can be quickly adjusted to avoid significant losses.
2. Small and Medium Projects: From 'Lagging Behind' to 'Rapid Expansion'
Small and medium projects no longer miss development opportunities due to insufficient resources; phased resource support enables efficient progress in each cycle: low-cost startup during the startup period avoids 'giving up due to funding'; precise testing during the validation period enables rapid product iteration; scaled expansion during the expansion period seizes market opportunities. For example, a 3-person GameFi data project utilized free data sources to develop tools during the startup period and completed validation within a month; during the validation period, they connected with 20 guilds for testing, and after optimizing features, user satisfaction reached 90%; during the expansion period, leveraging Southeast Asian data sources and merchant channels, they served 50 guilds within 2 months, increasing monthly revenue from 5000 C to 20,000 C, growing twice as fast as the industry average.
3. Offline Merchants: From 'Expansion Burden' to 'Scale Dividend'
Merchants are no longer burdened by insufficient management capabilities, as flexible plans allow scale growth and data management to synchronize: the single store period lays a solid foundation, the multiple stores period achieves collaboration, and the chain period enjoys scale dividends. A certain community supermarket expanded from 1 store to 8 chains, accumulating 300 members during the single store period using simple tools; during the multiple stores period, cross-store data synchronization increased the cross-store consumption rate of members to 90%, and the member loss rate decreased by 15%; during the chain period, leveraging data middle-platform to analyze regional consumption preferences, optimizing product structure for different stores led to an overall revenue increase of 50%, truly converting 'scale expansion' into 'revenue growth.'
From an ecological perspective, growth-oriented services significantly enhance the 'role growth rate' in the Web3 data ecosystem: the proportion of experienced individual users rises from 10% to 35%, the lifespan of small and medium projects extends from 6 months to 18 months, and the chain ratio of offline merchants increases from 5% to 20%; more critically, the growth of small roles reinforces the ecosystem—experienced users engage in more complex data tasks, expansion projects cover more regions, and chain merchants provide richer scenarios, forming a positive cycle of 'small role growth - ecological prosperity - more role growth.'
IV. Long-term Significance: The Paradigm of 'Growth-Oriented Infrastructure' in the Web3 Data Ecosystem
The long-term vitality of the Web3 data ecosystem does not lie in 'serving how many roles' but in 'how many roles can be helped to grow'—when small roles can continuously advance, the ecosystem can form an 'endless' innovation capability. Chainbase's 'growth-oriented data service' system provides a new paradigm for Web3 infrastructure: infrastructure should not be a 'static tool collection' but a 'dynamic growth partner,' upgrading in sync with the needs of small roles, becoming the 'underlying capability' that supports long-term development.
The long-term significance of this paradigm is that it shifts Web3 from being 'short-term opportunity-driven' to 'long-term growth-driven'—small roles no longer rely on single tasks or short-term trends but achieve stable development through continuous capability advancement; it shifts the Web3 data ecosystem from 'homogeneous competition' to 'differentiated growth'—small roles at different stages can receive precise services without being entangled in 'using advanced tools' or 'being limited by outdated tools'; it drives Web3 from 'niche circles' to 'mass growth platforms'—whether individuals, projects, or merchants, everyone can find a suitable growth path in the ecosystem, growing from 'novice' to 'ecological co-builder.'
In the future, as growth-oriented services cover more segmented roles (such as Web3 creators, small merchants in rural areas), the Web3 data ecosystem may form a 'full-cycle growth network': every small role, from the first day of entering the ecosystem, can receive adaptive services and continue to advance with business development; ecosystem innovation is no longer led by the top but driven by the growth and breakthroughs of countless small roles. And Chainbase, as a 'growth-oriented infrastructure,' is the 'core support' of this network—it does not define growth paths but provides the 'data capability fuel' needed for growth, allowing every small role to achieve continuous breakthroughs from '0 to 1, from 1 to N' in the Web3 ecosystem, which is the key sign of the maturation of the Web3 ecosystem.
