高级联动与窗口分析
目标
在基础仪表盘之外,使用 v4.1 的组合粒度表做更细的联动分析,回答“某个日期窗口、某个类目、某类用户分层的行为是否不同”。
建议仪表盘名称:
LZ-组6_高级联动与窗口分析
使用限制
date_window_category_segment_metrics 有 137 万行,适合按条件聚合,不建议全表明细展示。
推荐只做:
- 日期窗口趋势
- 类目 Top N
- 分层对比
- 条件聚合
不要直接把 137 万行全部放表格里。
图表1:连续日期窗口整体趋势
保存名称:
趋势-连续日期窗口行为
可视化:Line
SELECT
CONCAT(window_start, ' 至 ', window_end) AS `日期窗口`,
window_days AS `窗口天数`,
SUM(pv_count) AS `浏览量`,
SUM(cart_count) AS `加购量`,
SUM(buy_count) AS `购买行为数`,
SUM(buy_count) / NULLIF(SUM(pv_count), 0) AS `购买行为率`
FROM date_window_category_segment_metrics
GROUP BY window_start, window_end, window_days
ORDER BY window_start, window_end;
图表2:指定窗口类目购买 Top20
保存名称:
排行-窗口类目购买Top20
可视化:Bar
变量:
start_date:Date,显示名称可填“开始日期”end_date:Date,显示名称可填“结束日期”
SELECT
category_id AS `类目ID`,
SUM(pv_count) AS `浏览量`,
SUM(buy_count) AS `购买行为数`,
SUM(pv_buy_users) / NULLIF(SUM(pv_users), 0) AS `浏览到购买用户转化率`
FROM date_window_category_segment_metrics
WHERE window_start = {{start_date}}
AND window_end = {{end_date}}
GROUP BY category_id
ORDER BY `购买行为数` DESC
LIMIT 20;
默认可测试:
start_date:2017-11-25
end_date:2017-12-03
图表3:指定类目的用户分层趋势
保存名称:
趋势-指定类目分层行为
可视化:Line
变量:
category_id_param:Number,显示名称可填“类目ID”
SELECT
date AS `日期`,
CASE segment
WHEN 'non_buyer' THEN '未购买用户'
WHEN 'single_day_buyer' THEN '单日购买用户'
WHEN 'repeat_day_buyer' THEN '跨日复购用户'
WHEN 'high_frequency_buyer' THEN '高频购买用户'
ELSE segment
END AS `用户分层`,
pv_count AS `浏览量`,
cart_count AS `加购量`,
buy_count AS `购买行为数`,
pv_to_buy_user_rate AS `浏览到购买用户转化率`
FROM daily_category_segment_metrics
WHERE category_id = {{category_id_param}}
ORDER BY date, segment;
图表4:分层购买贡献
保存名称:
柱状-分层购买贡献
可视化:Bar
SELECT
CASE segment
WHEN 'non_buyer' THEN '未购买用户'
WHEN 'single_day_buyer' THEN '单日购买用户'
WHEN 'repeat_day_buyer' THEN '跨日复购用户'
WHEN 'high_frequency_buyer' THEN '高频购买用户'
ELSE segment
END AS `用户分层`,
SUM(pv_count) AS `浏览量`,
SUM(cart_count) AS `加购量`,
SUM(buy_count) AS `购买行为数`,
SUM(pv_buy_users) / NULLIF(SUM(pv_users), 0) AS `浏览到购买用户转化率`
FROM daily_category_segment_metrics
GROUP BY segment
ORDER BY `购买行为数` DESC;
图表5:高转化类目与用户分层组合
保存名称:
表格-高转化类目分层组合
可视化:Table
SELECT
category_id AS `类目ID`,
CASE segment
WHEN 'non_buyer' THEN '未购买用户'
WHEN 'single_day_buyer' THEN '单日购买用户'
WHEN 'repeat_day_buyer' THEN '跨日复购用户'
WHEN 'high_frequency_buyer' THEN '高频购买用户'
ELSE segment
END AS `用户分层`,
SUM(pv_users) AS `浏览用户数`,
SUM(buy_users) AS `购买用户数`,
SUM(pv_buy_users) / NULLIF(SUM(pv_users), 0) AS `浏览到购买用户转化率`,
SUM(pv_count) AS `浏览量`,
SUM(buy_count) AS `购买行为数`
FROM daily_category_segment_metrics
GROUP BY category_id, segment
HAVING SUM(pv_users) >= 1000
ORDER BY `浏览到购买用户转化率` DESC
LIMIT 100;
适合答辩的讲法
基础看板解决“整体发生了什么”,高级联动看板解决“在哪个窗口、哪个类目、哪类用户上更明显”。为了避免 UV 等不可加指标被错误拼接,v4.1 直接生成了日期、类目、用户分层组合粒度表,而不是在看板端临时拼表。