> For the complete documentation index, see [llms.txt](https://growingio.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://growingio.gitbook.io/docs/product-manual/product-analysis/retention/result.md).

# 留存分析结果解读

留存图中的数据是根据留存表来绘制的，我们针对留存表来说明一下数据统计口径。首先，需要明确的是，留存表中的每个绝对值，指的都是人数。

下面，我们把留存表分成 "汇总行"和"日期行"：

![](https://assets.growingio.com/docs/retention/%E5%9B%BE8%EF%BC%9Atable%E5%8C%BA%E5%88%86%E6%B1%87%E6%80%BB%E8%A1%8C%E4%B8%8E%E6%97%A5%E6%9C%9F%E8%A1%8C.png)

"汇总行"的数据是依据 "日期行"的数据来计算的。下面具体解读一下：

![](https://assets.growingio.com/docs/retention/%E5%9B%BE9%EF%BC%9A%E6%97%A5%E6%9C%9F%E8%A1%8C.png)

* **5722：**这个是日期行的 "用户量"一列，代表的是 9 月 18 日，"目标用户"中完成"起始行为"的用户量，这是后续用户留存的基数。图中给出的 "日颗粒度"，如果是周颗粒度，那么这个单元格中的用户量是当前自然周的获取的用户去重得到的独立用户量。
* **26.9%：**这个是日期行的留存率图中的留存率数据。 Tips 给出了统计口径；5722 个满足起始行为的用户，有 1537 个用户在第二天(09月/19日)完成了留存行为。次日留存率的计算：

  ```
        26.9% = 1537（人）/5722（人）
  ```

![图10：汇总行数据](https://assets.growingio.com/docs/retention/%E5%9B%BE10%EF%BC%9A%E6%B1%87%E6%80%BB%E8%A1%8C%E6%95%B0%E6%8D%AE.png)

* **117012：**这个是汇总行 "用户量"列。是日期行每一行的 "用户量"数据直接算数相加得到的，没有做去重。**需要特别注意，这个数据不是在选定的时间范围内的实际用户量，因为这个数据没有去重。**
* **12.2%：**这个是汇总行的留存率数据。这个留存率数据是日期行每一行数据加权平均得到的。具体算法是：

  ```
    12.2% = 每个日期行 "3日后" 列的用户量算数相加/ 对应每个日期行 "用户量" 列的用户量算数相加
  ```

  为了更好地理解计算口径，下面是一个示例：

![](https://docs.growingio.com/.gitbook/assets/liu-cun-shuai-ju-li-new.png)


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