尊敬的用户，以下是基于您提供的用户行为数据，运用SQL语言进行产品转化漏斗分析的示例代码：

1. 分析各环节的用户留存数量与比率：

```sql

深入解读：业务数据分析十大常用技巧与方法

-- 用户点击下单按钮后的留存数量与比率

SELECT COUNT(DISTINCT device_id) AS retention_count,

COUNT(DISTINCT device_id) * 100.0 / (SELECT COUNT(DISTINCT device_id) FROM dwd_user_behavior WHERE action_id = 'click_order_button') AS retention_rate

FROM dwd_user_behavior

WHERE action_id = 'click_order_button';

-- 用户打开提交订单页后的留存数量与比率

SELECT COUNT(DISTINCT device_id) AS retention_count,

COUNT(DISTINCT device_id) * 100.0 / (SELECT COUNT(DISTINCT device_id) FROM dwd_user_behavior WHERE action_id = 'open_submit_order_page') AS retention_rate

FROM dwd_user_behavior

WHERE action_id = 'open_submit_order_page';

-- 用户点击提交订单按钮后的留存数量与比率

SELECT COUNT(DISTINCT device_id) AS retention_count,

COUNT(DISTINCT device_id) * 100.0 / (SELECT COUNT(DISTINCT device_id) FROM dwd_user_behavior WHERE action_id = 'click_submit_order_button') AS retention_rate

FROM dwd_user_behavior

WHERE action_id = 'click_submit_order_button';

-- 用户打开支付页后的留存数量与比率

SELECT COUNT(DISTINCT device_id) AS retention_count,

COUNT(DISTINCT device_id) * 100.0 / (SELECT COUNT(DISTINCT device_id) FROM dwd_user_behavior WHERE action_id = 'open_payment_page') AS retention_rate

FROM dwd_user_behavior

WHERE action_id = 'open_payment_page';

-- 用户点击确认支付后的留存数量与比率

SELECT COUNT(DISTINCT device_id) AS retention_count,

COUNT(DISTINCT device_id) * 100.0 / (SELECT COUNT(DISTINCT device_id) FROM dwd_user_behavior WHERE action_id = 'click_confirm_payment') AS retention_rate

FROM dwd_user_behavior

WHERE action_id = 'click_confirm_payment';

-- 用户跳转至支付成功页后的留存数量与比率

SELECT COUNT(DISTINCT device_id) AS retention_count,

COUNT(DISTINCT device_id) * 100.0 / (SELECT COUNT(DISTINCT device_id) FROM dwd_user_behavior WHERE action_id = 'open_payment_success_page') AS retention_rate

FROM dwd_user_behavior

WHERE action_id = 'open_payment_success_page';

```

2. 计算各环节之间的平均停留时长：

```sql

-- 从点击下单按钮到打开提交订单页的平均停留时长

SELECT AVG(DATEDIFF(day, LAG(action_time) OVER (ORDER BY action_time), action_time)) AS average_stay_time

FROM dwd_user_behavior

WHERE action_id IN ('click_order_button', 'open_submit_order_page');

-- 从打开提交订单页到点击提交订单按钮的平均停留时长

SELECT AVG(DATEDIFF(day, LAG(action_time) OVER (ORDER BY action_time), action_time)) AS average_stay_time

FROM dwd_user_behavior

WHERE action_id IN ('open_submit_order_page', 'click_submit_order_button');

-- 从点击提交订单按钮到打开支付页的平均停留时长

SELECT AVG(DATEDIFF(day, LAG(action_time) OVER (ORDER BY action_time), action_time)) AS average_stay_time

FROM dwd_user_behavior

WHERE action_id IN ('click_submit_order_button', 'open_payment_page');

-- 从打开支付页到点击确认支付的平均停留时长

SELECT AVG(DATEDIFF(day, LAG(action_time) OVER (ORDER BY action_time), action_time)) AS average_stay_time

FROM dwd_user_behavior

WHERE action_id IN ('open_payment_page', 'click_confirm_payment');

-- 从点击确认支付到跳转至支付成功页的平均停留时长

SELECT AVG(DATEDIFF(day, LAG(action_time) OVER (ORDER BY action_time), action_time)) AS average_stay_time

FROM dwd_user_behavior

WHERE action_id IN ('click_confirm_payment', 'open_payment_success_page');

```

请根据实际业务需求和数据结构对以上代码进行适当调整，并确保将`dwd_user_behavior`替换为实际的表名。