The collaboration in the Web3 data ecosystem has long surpassed the initial stage of 'role connection' and entered the deep waters of 'scenario adaptation'—individual users, small projects, offline merchants, and other 'small roles' can achieve basic connections through platforms (e.g., individual authorizing data to projects, projects connecting to merchant needs), but due to 'disconnection between collaboration and scenario', it is difficult to generate actual value: individual on-chain data does not match the merchant's mother and baby scenario needs, and cannot be converted into discounts after authorization; project tools cannot be embedded in the peak processes of restaurants, making it burdensome for merchants; collaborative interaction does not align with small roles' scenario habits, leading to cumbersome operations and low participation rates. This 'superficial connection, substantively ineffective' collaboration traps small roles in a predicament of 'collaborating for the sake of collaboration', wasting ecological resources. As a decentralized data infrastructure, Chainbase is building a 'deep cultivation of scenarios' collaborative network through a three-dimensional system of 'scenario-based demand matching, process tool embedding, habitual interaction design', allowing the collaboration of small roles to truly embed into business scenarios, moving from 'having connections' to 'having value'.
1. The disconnection dilemma of Web3 small role data collaboration: three core obstacles.
The essence of the disconnection between collaboration and scenarios lies in 'collaborative design not aligning with the actual business scenarios of small roles'—demand matching ignores scenario attributes, tool embedding violates scenario processes, and interaction design deviates from scenario habits, leading collaboration to fail to integrate into the daily operations of small roles, remaining superficial.
1. Demand matching: data misalignment with scenario needs.
The collaborative needs of small roles have strong 'scenario attributes', but existing collaborative models are mostly 'general matching', ignoring scenario differences: individual users' on-chain data lack 'scenario tags' (e.g., 'mother and baby consumption-related transactions', 'pet product NFT holdings'), making it impossible to accurately match merchants' segmented scenarios (e.g., mother and baby stores need 'mother and baby consumption data', but are matched with 'game NFT data'); tools for small projects are categorized by 'function' (e.g., 'data visualization tools'), rather than 'scenario classification' (e.g., 'restaurant membership data dashboard'), making it difficult for merchants to find tools that fit their scenarios; offline merchants' need descriptions are vague (e.g., 'want to increase member repurchase'), without clarifying 'repurchase scenarios' (e.g., 'weekend parent-child activity repurchase', 'weekday lunch repurchase'), leading to insufficient specificity in the solutions provided by projects. For example, a mother and baby store wants to filter high-value members through Web3 data, but matches with individual users' 'game on-chain data', which cannot be used for operations; a small project developed 'retail data tools', but due to not segmenting 'convenience stores' and 'clothing stores' scenarios, convenience store merchants find many functions (e.g., clothing size analysis) useless and core needs (e.g., real-time inventory data) unmet. The misalignment of needs and scenarios causes collaboration to lose value from the start.
2. Tool embedding: conflict between processes and scenario habits.
Even if needs match, if project tools cannot be embedded in merchants' scenario processes, collaboration will fail: during peak hours at restaurants (e.g., lunch and dinner), it requires 'NFT redemption to be completed within 10 seconds', but project tools require three steps to operate, and staff have no time to use them when busy; convenience stores' 24-hour operations require 'unattended self-service redemption', but tools require staff manual confirmation, making them unusable at night; the operation of small project tools requires 'computer login to the backend', but merchants usually manage using mobile phones, making operation inconvenient. This 'conflict between tool processes and scenario habits' makes merchants 'want to use but can't': a community coffee shop tried to use the NFT redemption tool during the morning peak, but because each redemption required three steps of opening a computer, logging into the backend, and entering a verification code, it led to complaints from waiting customers and was discontinued after two days; a 24-hour convenience store's member data tool, because it requires computer operation, cannot check real-time member consumption data at night, rendering the tool a 'decoration'. Process conflicts prevent collaboration from being implemented in actual business.
3. Interaction design: operations and scenario capabilities do not match.
Small roles have varying scenario capabilities (e.g., merchant staff not understanding Web3 terminology, individual users unfamiliar with complex operations), but collaborative interaction design is often 'standardized', lacking adaptation to scenario capabilities: individual users participating in merchants' NFT activities must manually copy wallet addresses and switch between multiple platforms, leading to abandonment due to cumbersome operations; merchant staff using project tools find interfaces filled with 'on-chain hashes', 'contract addresses', and other technical jargon they cannot understand or operate; small projects communicating with merchants need to use 'API docking', 'data interfaces' and other technical language, making it difficult for merchants to understand and leading to low communication efficiency. For example, an elderly user wants to participate in the NFT discount activity at a community supermarket, but due to needing to 'connect wallet - authorize data - generate redemption code' in three steps, and lacking guidance on the interface, ultimately gives up; a community fruit store staff member using the project's member data tool cannot understand the definition of 'on-chain consumption frequency', making it impossible to identify high-value members, and the tool cannot be effective. The mismatch between interaction and capability makes collaboration difficult to sustain.
2. Chainbase's scenario-based collaboration solutions: Three-dimensional design achieves deep integration of 'collaboration-scenario'.
Chainbase's core innovation is to break out of the framework of 'universal collaboration', starting from 'the actual scenarios of small roles' to build a 'demand-tool-interaction' full-link scenario adaptation system, allowing collaboration to truly integrate into business processes.
1. Scenario-based matching of demands: tagging classification + intelligent recommendation, precisely connecting scenario needs.
To address the issue of misaligned needs, Chainbase builds a 'scenario-based demand matching hub', aligning needs and scenarios precisely through 'tagging classification + scenario algorithms':
• Role Tags: Scenario attribute visualization: add 'scenario tags' to individual users' on-chain data, such as 'mother and baby consumption data' (on-chain transactions for mother and baby products in the last 3 months), 'pet NFT holdings' (records of holding pet-related NFTs), which users can select on their own; add 'scenario classification tags' to tools for small projects, such as 'restaurant NFT redemption', 'convenience store self-service membership management', 'mother and baby store data filtering', rather than just functional classification; add 'scenario description tags' to offline merchants' needs, such as 'increase weekend parent-child activity repurchase', 'optimize weekday lunch discounts', to clarify scenario details.
• Intelligent matching: prioritize scenario algorithms: during matching, the algorithm prioritizes connecting based on 'scenario tags': the demand for 'high-value member screening' at mother and baby stores automatically matches individual users with 'mother and baby consumption data' tags; the demand for 'quick redemption during peak hours' at restaurants automatically recommends project tools with 'restaurant NFT quick redemption' tags; individual users' demand for 'simple NFT discounts' automatically matches merchants' activities with 'low operation threshold' tags. For example, if a mother and baby store needs to filter 'members who purchased mother and baby products on-chain in the last month', the system automatically matches 200 individual users with 'mother and baby consumption data' tags, achieving a demand matching accuracy rate of 92%.
As of May 2024, the scenario-based demand matching hub has added scenario tags for 5.35 million individual users, 295,000 small projects, and merchants, increasing the demand matching accuracy rate from 55% to 92%, and reducing the failure rate of collaboration due to demand misalignment from 40% to 8%.
2. Tool scenario embedding: process adaptation + lightweight transformation, integrating into business habits.
To address process conflict issues, Chainbase introduces a 'tool scenario transformation module', aligning tool processes with small role scenario habits:
• Process adaptation: optimize operation steps according to scenarios: for peak hours in restaurants, develop a 'one-button redemption module', where staff only need to scan the customer's NFT QR code to complete the redemption in one second, without multiple steps; for the 24-hour operation of convenience stores, launch a 'self-service redemption plugin', allowing customers to redeem NFTs themselves through the store's scanning gun, without staff involvement; for merchants managing on mobile, develop a 'mobile adaptation version of the tool', migrating all functions to a mobile mini-program, simplifying operation steps to within two.
• Function lightweighting: retain core scenario needs: eliminate functions unrelated to scenarios in tools, keeping only core needs: for the restaurant's membership data tool, retain only 'consumption frequency, NFT holdings, discount collection' as the three core data, delete 'on-chain transaction hash query' and other useless functions; for the mother and baby store's NFT activity tool, retain only 'NFT distribution, discount redemption, membership data statistics' functions to avoid redundant functions.
After the transformation of scenario-based tools, the efficiency of merchants' tools increased by 85%: the NFT redemption time at peak hours in restaurants was reduced from 30 seconds per transaction to 1 second per transaction, and the nighttime tool usage rate in convenience stores increased from 10% to 90%, with the daily usage of merchant tools tripling.
3. Interaction scenario design: capability adaptation + guidance optimization, lowering participation thresholds.
To solve the problem of mismatch between interaction and capability, Chainbase adopts 'scenario-based interaction design', making operations align with small roles' scenario capabilities:
• Language Adaptation: Scenario-based terminology conversion: convert Web3 technical terms into scenario-based language: 'on-chain consumption frequency' in merchant tools is changed to 'the number of times members shop on-chain', 'contract address' is changed to 'exclusive NFT number'; the personal user activity interface's 'connect wallet' is changed to 'bind your discount account', 'authorized data' is changed to 'agree to use your consumption records to redeem discounts'.
• Operational guidance: scenario-based real-time prompts: when individual users participate in activities, the interface pops up scenario-based guidance in real-time (e.g., 'click here to bind your wallet, just as simple as binding a bank card'); when merchant staff operate tools, each step has 'scenario explanations' (e.g., 'click 'redeem', scan the customer's NFT code, just like scanning a payment code'); when small projects communicate with merchants, the platform provides 'scenario-based communication templates', transforming 'API docking' into 'connecting the tool to your cash register system, just like docking with a takeaway platform'.
Scenario-based interaction design significantly lowers the participation threshold for small roles: the abandonment rate for individual user activities drops from 60% to 15%, the operational proficiency of merchant staff using tools is reduced from 3 days to 1 hour, and the communication efficiency between small projects and merchants increases by 70%.
3. The ecological value of scenario-based collaboration: small role collaboration transforms from 'ineffective' to 'efficient'.
Chainbase's scenario-based collaborative system allows small roles to collaborate not just as a 'superficial connection', but as a 'deep cooperation embedded in scenarios that create value', with value reflected in the business improvements of each role.
For individual users, collaboration transforms from 'cumbersome operations' to 'scenario-based convenience'. Users can quickly find activities that fit their habits (e.g., 'simple operation supermarket NFT discounts'), data can precisely match merchant scenario needs (e.g., 'mother and baby consumption data exchanged for discounts at mother and baby stores'), gaining actual benefits while participating in collaboration, with monthly scenario-based collaborative income increasing by 45%, and participation satisfaction reaching 90%.
For small projects, collaboration transforms from 'tool promotion' to 'scenario-based implementation'. The tools of projects can accurately connect with merchant scenario needs (e.g., 'quick redemption tool for restaurants'), embed into merchant business processes (e.g., operations during peak hours), and are no longer 'idle tools that merchants do not use'. A four-person project team developed a 'one-button redemption tool for restaurants', connecting with 50 restaurants through scenario-based collaboration, achieving a monthly income of 15,000 $C, with tool usage rates increasing from 20% to 95%.
For offline merchants, collaboration transforms from 'extra burden' to 'scenario-based operational support'. Merchants' tools can align with business habits (such as mobile operations, quick redemptions during peak hours), and data can serve specific scenarios (e.g., weekend parent-child activity repurchase), truly enhancing operational efficiency. A community mother and baby store in Shanghai matched 200 individual users tagged with 'mother and baby consumption data', launching an 'on-chain consumption bonus for mother and baby products' activity, increasing member repurchase rates by 40% and revenue by 35% within three months.
From an ecological perspective, scenario-based collaboration significantly increases the 'collaborative value density' of the Web3 data ecosystem: the proportion of effective collaboration rises from 30% to 80%, the actual business value generated from collaboration (such as merchant revenue growth, personal income increase) grows by 250%, forming a positive cycle of 'scenario demand - collaborative matching - value creation', shifting the ecosystem from a 'role connection network' to a 'scenario value network'.
4. Long-term significance: The 'scenario deep cultivation' paradigm of Web3 data collaboration.
The future of Web3 data collaboration lies not in 'how many roles are connected', but in 'how many scenarios can be adapted'—only when collaboration can be embedded in the actual business scenarios of small roles, solving specific problems, can the ecosystem truly land. The scenario-based collaboration promoted by Chainbase is essentially a paradigm upgrade of Web3 data collaboration from 'universal' to 'scenario-based', with the long-term significance of this paradigm being:
It brings Web3 collaboration from 'virtual concepts' to 'real scenarios'—when individual users redeem discounts with on-chain data in supermarkets, merchants use NFT redemption tools during peak hours in restaurants, and small projects develop self-service tools for convenience stores, Web3 is no longer a 'niche technology' but a practical tool integrated into daily life; it transforms small roles from 'collaborative bystanders' to 'scenario leaders'—the scenario demands of small roles become the core of collaborative design, rather than being technology-led, making ecological innovation more aligned with real needs; it shifts the Web3 ecosystem from 'technology-driven' to 'scenario-driven'—the vitality of the ecosystem no longer relies on technological updates but on deep adaptation to the scenarios of small roles, with collaborative value continuously increasing as scenario coverage expands.
In the future, as scenario-based collaboration covers more segmented fields (such as medical, education, and elderly care Web3 data collaboration), the Web3 data ecosystem may form a 'scenario-based collaboration network': each scenario has an adapted collaboration solution, and every small role can participate in collaboration and create value in familiar scenarios. Infrastructure like Chainbase is the 'scenario adaptation hub' of this network—it does not define scenarios but allows collaboration to actively adapt to scenarios through technology and design, ultimately driving the Web3 data ecosystem towards a mature stage of 'scenario-based, practical, and inclusive'.
