Group 1 - The core logic of the queue-free model is based on a "consumption equals queuing, queuing equals rebate" mechanism, creating a win-win ecosystem for consumers, merchants, and platforms [1] - The model operates on three main growth drivers: time priority principle, dynamic reward distribution, and traffic fission effect [1][3] - The queue-free model allows users to participate in a rebate system simply by making a purchase, without complex tasks [12][13] Group 2 - User participation requires a minimum spending threshold to ensure the reward pool remains substantial, preventing rapid dilution of funds [3][5] - The system employs a FIFO (First In, First Out) rule, ensuring transparency in the queuing process, where users can track their position and the status of the reward pool [5][6] - Users can exit the queue at any time, receiving 60% of their accumulated rebate as shopping credits, while 40% remains in the reward pool to support ongoing operations [6][13] Group 3 - Merchants can set their own rebate percentages, typically between 10% and 30%, allowing for flexible cost management based on industry profit margins [9][15] - The model encourages cross-industry alliances, enabling merchants to share customer traffic and enhance the reward pool through collective participation [10][16] - Data-driven optimization allows merchants to adjust their strategies based on real-time analytics, improving customer retention and sales performance [12][17] Group 4 - The platform ensures fund security through third-party supervision and compliance with legal frameworks, mitigating risks associated with fund misappropriation [14][19] - Transparency in operations is maintained by clearly communicating reward rules and fund flows to users, reducing the likelihood of disputes [21][22] - The potential for technological integration, such as blockchain, enhances trust and expands the model's applicability across various sectors [23]