营销分析用户旅程时间轴图谱生成

{
  "workflow_id": "journey_timeline_graph_generator",
  "input": {
    "ratio": {
      "field_name": "ratio",
      "default": "16:9",
      "description": "生成图像的宽高比例，可选值：1:1、3:4、4:3、16:9、9:16",
      "example": "16:9",
      "required": false,
      "type": "string"
    },
    "report": {
      "field_name": "report",
      "default": "",
      "description": "用户行为分析报告原文，用于提取旅程节点与情绪曲线",
      "example": "【20:00 前后 · 旅程启动 — 进入活跃高峰】\n数据显示，用户群体高度集中于晚间 20:00 至 22:00 这一\"黄金两小时\"开启活跃。此时用户结束了一天的工作与琐事，处于身心放松、注意力回收的状态，购物意愿与浏览耐心同步攀升。这一时段构成了平台流量与潜在成交的核心窗口，是整条用户旅程的天然起点。\n\n【20:00–21:00 · 浏览探索 — 兴趣被唤醒】\n进入活跃期后，用户首先展开广泛的商品浏览。他们在首页推荐、分类频道与搜索结果间穿梭，通过商品图、详情页与评价反复比对，兴趣被逐步唤醒。此阶段用户心理以\"逛\"和\"种草\"为主，行为轨迹呈现高频点击、长停留的特征，是需求从模糊走向清晰的关键孵化期。\n\n【21:00 前后 · 加购决策 — 意向显性化】\n随着浏览深入，用户将心仪商品加入购物车，标志着购买意向由隐性转为显性。加购行为是旅程中极具价值的\"高意向信号\"，意味着用户已基本完成商品筛选与价值认同，距离成交仅一步之遥。此刻的用户带着较强的期待，准备推进至最后的支付环节。\n\n【21:00–22:00 · 支付受阻 — 旅程断点出现】\n然而，旅程在最关键的临门一脚处遭遇明显断层：支付转化率显著偏低。深入归因发现，核心痛点集中于支付页面加载缓慢——在用户决策意愿最强、情绪最饱满的瞬间，页面长时间的等待打断了流畅体验，催生焦虑与犹豫。本就处于晚间疲惫状态的用户极易因这一卡顿而放弃支付、关闭页面，导致大量高意向流量在最后一环白白流失，形成令人惋惜的\"煮熟的鸭子飞了\"式损耗。\n\n【旅程洞察与优化方向】\n纵观整条时间轴，用户旅程呈现出\"前段顺畅、后段断裂\"的鲜明特征：从活跃、浏览到加购一气呵成，意向稳步攀升，却在支付环节戛然受阻。这清晰表明，平台当前最大的转化瓶颈并非流量或意愿不足，而是支付体验的技术性卡点。\n\n建议优化聚焦三点：其一，针对晚间高并发场景优化支付页面加载性能，压缩首屏渲染时间，必要时引入预加载与缓存策略；其二，简化支付流程、减少跳转层级，让高意向用户\"趁热\"成交；其三，对加购未支付用户配置实时挽回机制（如限时优惠、消息提醒），把流失流量重新拉回旅程闭环。唯有打通支付这一\"最后一公里\"，才能将晚间黄金时段的旺盛意愿真正兑现为实际成交。",
      "required": true,
      "type": "string"
    },
    "demand": {
      "field_name": "demand",
      "default": "",
      "description": "对生成图的构图和配色要求（非必填），如科技感、蓝色调、横向时间轴",
      "example": "科技感，蓝色调，横向时间轴",
      "required": false,
      "type": "string"
    }
  },
  "steps": [
    {
      "point_code": "",
      "id": "step_1_intent_analyzer",
      "result": [],
      "api_code": "intent_analyzer",
      "backend_type": "prompt_api",
      "status": "PENDING",
      "name": "意图与需求深度解析",
      "action": "run",
      "params": {
        "ratio": "{{@input.ratio}}",
        "report": "{{@input.report}}",
        "demand": "{{@input.demand}}"
      }
    },
    {
      "point_code": "",
      "id": "step_2_journey_extractor",
      "result": [],
      "api_code": "journey_extractor",
      "backend_type": "prompt_api",
      "status": "PENDING",
      "name": "用户旅程结构化提取",
      "action": "run",
      "params": {
        "merge_context": {
          "core_theme": "{{@step_1_intent_analyzer.result.data.structured_analysis.semantic_structure.core_theme}}"
        },
        "report": "{{@input.report}}"
      },
      "depends_on": [
        "step_1_intent_analyzer"
      ]
    },
    {
      "point_code": "",
      "id": "step_3_timeline_prompt_engineer",
      "result": [],
      "api_code": "timeline_prompt_engineer",
      "backend_type": "prompt_api",
      "status": "PENDING",
      "name": "时间轴图谱提示词工程",
      "action": "run",
      "params": {
        "merge_context": {
          "visual_guidelines": "{{@step_1_intent_analyzer.result.data.structured_analysis.semantic_structure.core_theme}}"
        },
        "journey_nodes": "{{@step_2_journey_extractor.result.data.journey_nodes}}",
        "demand": "{{@input.demand}}"
      },
      "depends_on": [
        "step_2_journey_extractor"
      ]
    },
    {
      "point_code": "1",
      "id": "step_4_generate_image",
      "result": [],
      "api_code": "3373",
      "backend_type": "sys_api",
      "status": "PENDING",
      "name": "生成时间轴图谱图像",
      "action": "run",
      "params": {
        "prompt": "{{@step_3_timeline_prompt_engineer.result.data.optimized_prompt}}",
        "aspect_ratio": "{{@input.ratio}}"
      },
      "depends_on": [
        "step_3_timeline_prompt_engineer"
      ]
    },
    {
      "point_code": "",
      "id": "step_5_poll_image_status",
      "result": [],
      "api_code": "polling",
      "backend_type": "sys_api",
      "status": "PENDING",
      "name": "轮询图像生成状态",
      "action": "run",
      "params": {
        "result_url": "{{@step_4_generate_image.result.data.result_url}}"
      },
      "depends_on": [
        "step_4_generate_image"
      ],
      "polling": {
        "interval_seconds": 5,
        "timeout_seconds": 600,
        "success_condition": "{{@step_5_poll_image_status.result.data.task_status}} === 'SUCCEEDED'"
      }
    }
  ],
  "output": {
    "optimized_prompt": {
      "field_name": "optimized_prompt",
      "description": "用于生图的专业优化提示词",
      "value": "{{@step_3_timeline_prompt_engineer.result.data.optimized_prompt}}",
      "type": "string"
    },
    "timeline_image_url": {
      "field_name": "timeline_image_url",
      "description": "最终生成的用户旅程时间轴图谱图像URL",
      "value": "{{@step_5_poll_image_status.result.data.result_url}}",
      "type": "string"
    },
    "journey_nodes": {
      "field_name": "journey_nodes",
      "description": "结构化的用户旅程节点数据（包含步骤、行为、情绪、触点）",
      "value": "{{@step_2_journey_extractor.result.data.journey_nodes}}",
      "type": "array"
    }
  }
}