- **Callback request = active buying intent.** It's not passive browsing; the lead is asking to talk to someone, which historically correlates with higher pipeline conversion and larger deal sizes. 请求回电属于主动购买信号，而非被动浏览；此类线索通常转化率更高、单笔订单金额更大。 - **Why C → B upgrade at 60:** Days 1–6 behavior accumulated a score of 50; the Day 7 callback request pushed the predicted score to 61, crossing the B-pool threshold (60). The AI treats this as a material jump in engagement quality and intent. C → B 升级逻辑：前6天累计50分，第7天主动请求回电使预测分升至61，跨越B池阈值60；AI判定其互动质量与购买意向发生实质性跃升。 - **Triggered actions (B-pool playbook):** Send tailored B2B proposal, create a sales follow-up task with SLA (e.g., 24h), route to success team for the requested callback, add to higher-frequency nurture sequence, and alert the account owner for potential A-pool acceleration. 触发动作（B池策略）：发送定制化B2B方案、生成带时效要求的销售跟进任务（如24小时内）、按请求转交成功团队回电、纳入更高频培育序列，并提醒客户负责人评估加速进入A池的可能。 - **Scoring logic chain:** Behavior (callback request) → AI score +11 → predicted 61 ≥ 60 → auto-upgrade C → B → proposal & follow-up tasks fire. This keeps high-intent leads from sitting in low-touch pools. 逻辑链路：行为（请求回电）→ AI评分+11 → 预测61≥60 → 自动C→B升级 → 触发方案发送与跟进任务；避免高意向线索滞留在低触达池。 - **Path to 100-unit distribution inquiry:** B-pool follow-up validates budget, scope, and timeline; if engagement continues and score approaches 120, upgrade to A pool, assign senior/enterprise sales, and position a volume-based distribution proposal aligned to a 100-unit rollout. 走向100套分销询盘的路径：B池跟进验证预算、范围与时间表；若互动持续、评分接近120，则升级A池，交由资深/大客户销售，并围绕100套部署设计批量分销方案。 - **Business impact:** Higher conversion velocity, better sales efficiency (only high-intent leads get sales time), and larger deal potential—moving from a single training inquiry to a scalable distribution opportunity. 业务影响：提升转化速度与销售效率（销售时间只投向高意向线索），并放大成交规模——从单次培训询盘升级为可复制放量的分销机会。