获取直播场次历史记录/Fetch live room history list

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获取直播场次历史记录/Fetch live room history list

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获取直播场次历史记录/Fetch live room history list

[中文]

用途:

  • 获取抖音创作者的直播场次历史记录
  • 查看指定时间范围内的所有直播场次数据
  • 支持查询正在进行的直播和历史直播记录
  • 此接口需要用户提供有效的抖音创作者平台Cookie
  • 使用 POST 方法,Cookie 在请求体中传输,更安全

请求体参数:

  • cookie: 用户的抖音创作者平台Cookie(必填,在请求体中传输)
  • start_date: 开始日期,格式为 YYYY-MM-DD(必填,例如: "2025-09-11")
  • end_date: 结束日期,格式为 YYYY-MM-DD(必填,例如: "2025-10-11")
  • limit: 每页数量限制,默认400,最多400条
  • need_living: 是否包含正在直播的场次(0=不包含, 1=包含,默认1)
  • download: 是否下载(0=不下载, 1=下载,默认0)

返回数据说明:

返回直播场次历史记录列表,数据位于 data.data.series 数组中,每个场次包含以下信息:

基本信息:

  • roomID: 直播间ID
  • roomTitle: 直播标题
  • coverUri: 直播封面图片URL
  • startTime: 开始时间(格式: "YYYY-MM-DD HH:mm:ss")
  • endTime: 结束时间(格式: "YYYY-MM-DD HH:mm:ss")
  • liveDurationWithoutPause: 直播时长(不含暂停时间,格式如: "1分钟5秒")
  • playStatus: 播放状态(4=已结束)

流量数据:

  • watchCnt: 总观看人次
  • serverWatchUcntTdDirect: 直接观看用户数(来自服务端统计)
  • pcu: 峰值同时在线人数(Peak Concurrent Users)
  • liveServerWatchDurationTdPavg: 平均观看时长

互动数据:

  • serverLikeCntTd: 点赞数
  • clientCommentUcntTd: 评论用户数
  • liveNewFollowUcnt: 新增关注数

消费/转化数据:

  • liveConsumeUcnt: 消费用户数
  • liveFansConsumeUcntTd: 粉丝消费用户数
  • roomLiveEarnScore: 直播收益积分

数据价值:

  • 历史回顾: 查看所有直播场次的完整记录
  • 数据对比: 对比不同场次的表现差异
  • 趋势分析: 分析直播效果的变化趋势
  • 优化方向: 找出高转化场次的共同特点
  • 时间规划: 根据历史数据优化直播时间
  • 内容策略: 根据不同主题的效果调整内容

应用场景:

  1. 定期复盘: 每周/每月查看直播数据进行总结
  2. 效果评估: 评估不同时段、不同主题的直播效果
  3. 数据报表: 生成直播数据报表供团队分析
  4. 策略优化: 基于历史数据制定下一步直播策略
  5. KPI追踪: 追踪直播相关的关键指标完成情况
  6. 趋势预测: 预测未来直播的潜在表现

注意事项:

  1. 时间范围: 建议查询时间不超过3个月,避免数据量过大
  2. 数量限制: 单次最多返回400条记录
  3. 数据延迟: 直播数据可能有1-2小时的延迟
  4. 正在直播: 设置need_living=1可以查看当前正在进行的直播
  5. Cookie有效性: 确保Cookie未过期,否则无法获取数据
  6. 日期格式: 必须使用YYYY-MM-DD格式,如2025-09-11

Cookie 获取方式:

  1. 登录抖音创作者平台 (https://creator.douyin.com)
  2. 打开浏览器开发者工具(F12)
  3. 切换到 Network 标签
  4. 刷新页面或进行操作
  5. 找到任意请求,复制 Cookie 请求头的值

[English]

Purpose:

  • Get Douyin creator's live room history list
  • View all live session data within a specified time range
  • Support querying ongoing and historical live sessions
  • This API requires users to provide valid Douyin Creator Platform Cookie
  • Use POST method, Cookie is transmitted in request body, more secure

Request Body Parameters:

  • cookie: User's Douyin Creator Platform Cookie (required, transmitted in request body)
  • start_date: Start date in YYYY-MM-DD format (required, e.g., "2025-09-11")
  • end_date: End date in YYYY-MM-DD format (required, e.g., "2025-10-11")
  • limit: Limit per page, default 400, max 400
  • need_living: Include ongoing live sessions (0=No, 1=Yes, default 1)
  • download: Download flag (0=No download, 1=Download, default 0)

Return Data Description:

Returns a list of live session history, data is located in data.data.series array, each session includes:

Basic Info:

  • roomID: Live room ID
  • roomTitle: Live title
  • coverUri: Live cover image URL
  • startTime: Start time (format: "YYYY-MM-DD HH:mm:ss")
  • endTime: End time (format: "YYYY-MM-DD HH:mm:ss")
  • liveDurationWithoutPause: Duration without pause (format: "1 minute 5 seconds")
  • playStatus: Play status (4=Ended)

Traffic Data:

  • watchCnt: Total watch count
  • serverWatchUcntTdDirect: Direct watch user count (from server statistics)
  • pcu: Peak Concurrent Users
  • liveServerWatchDurationTdPavg: Average watch duration

Engagement Data:

  • serverLikeCntTd: Likes count
  • clientCommentUcntTd: Comment user count
  • liveNewFollowUcnt: New followers count

Consumption/Conversion Data:

  • liveConsumeUcnt: Consuming user count
  • liveFansConsumeUcntTd: Fan consuming user count
  • roomLiveEarnScore: Live room earn score

Data Value:

  • History Review: View complete records of all live sessions
  • Data Comparison: Compare performance across sessions
  • Trend Analysis: Analyze changes in live performance
  • Optimization: Identify common traits of high-conversion sessions
  • Time Planning: Optimize live timing based on historical data
  • Content Strategy: Adjust content based on theme performance

Use Cases:

  1. Regular Review: Weekly/monthly live data summary
  2. Effect Evaluation: Evaluate performance by time and theme
  3. Data Reports: Generate reports for team analysis
  4. Strategy Optimization: Develop strategies based on data
  5. KPI Tracking: Track live-related KPIs
  6. Trend Prediction: Predict future live performance

Notes:

  1. Time Range: Recommended not to exceed 3 months
  2. Quantity Limit: Max 400 records per request
  3. Data Delay: 1-2 hours delay possible
  4. Ongoing Live: Set need_living=1 to include current live
  5. Cookie Validity: Ensure Cookie is not expired
  6. Date Format: Must use YYYY-MM-DD format

How to get Cookie:

  1. Login to Douyin Creator Platform (https://creator.douyin.com)
  2. Open browser developer tools (F12)
  3. Switch to Network tab
  4. Refresh page or perform operations
  5. Find any request and copy the Cookie header value

[示例/Example]

{
    "cookie": "Your_Cookie_Here",
    "start_date": "2025-09-11",
    "end_date": "2025-10-11",
    "limit": 400,
    "need_living": 1,
    "download": 0
}

返回数据示例/Response Example:

{
    "data": {
        "code": 0,
        "componentID": "",
        "data": {
            "series": [
                {
                    "clientCommentUcntTd": "0",
                    "coverUri": "https://p3-webcast-sign.douyinpic.com/...",
                    "endTime": "2025-11-20 13:52:20",
                    "liveConsumeUcnt": "1",
                    "liveDurationWithoutPause": "1分钟5秒",
                    "liveFansConsumeUcntTd": "1",
                    "liveNewFollowUcnt": "0",
                    "liveServerWatchDurationTdPavg": "0.5666666666666667",
                    "pcu": "1",
                    "playStatus": "4",
                    "roomID": "75746809889xxxxxx",
                    "roomLiveEarnScore": "1",
                    "roomTitle": "xxxxxxxx",
                    "serverLikeCntTd": "0",
                    "serverWatchUcntTdDirect": "1",
                    "startTime": "2025-11-20 13:51:15",
                    "watchCnt": "1"
                }
            ]
        },
        "meta": ""
    }
}

数据解读/Data Interpretation:

  • watchCnt: 总观看人次,反映直播的曝光度和吸引力
  • pcu: 峰值同时在线人数(Peak Concurrent Users),反映直播的热度峰值
  • liveServerWatchDurationTdPavg: 平均观看时长,反映内容的吸引力
  • liveNewFollowUcnt: 新增关注数,反映直播的转粉效果
  • roomLiveEarnScore: 直播收益积分,反映直播的收益能力
  • liveConsumeUcnt/liveFansConsumeUcntTd: 消费用户数/粉丝消费用户数,反映直播的转化能力
  • 互动率: (serverLikeCntTd+clientCommentUcntTd)/watchCnt,反映用户活跃度

优化建议/Optimization Suggestions:

  1. 高峰分析: 分析pcu最高出现的时间点,强化该时段的内容
  2. 留存优化: 提升liveServerWatchDurationTdPavg平均观看时长,增加内容的连贯性和吸引力
  3. 互动引导: 在直播中增加互动环节,提升serverLikeCntTd点赞数、clientCommentUcntTd评论数
  4. 转粉策略: 在直播中适时引导关注,提升liveNewFollowUcnt新增关注数
  5. 消费转化: 分析高roomLiveEarnScore场次的特点,优化直播策略
  6. 时间选择: 根据历史数据选择watchCnt观看人次最多的时段开播

Imported from a validated TikHub OpenAPI document. Pricing must be reviewed before enabling.

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