网站点击率统计如何有助于提高可用性？
您是否注意到 facebook 中的几乎每个链接都有 ref 查询字符串？
我相信，通过该 ref，facebook 可以以某种方式跟踪和研究他们的用户行为。这可能是他们提高可用性的秘诀。
所以，我正在尝试同样的事情，更改 http://a.com/b.aspx 到 http://a.com/b.aspx?ref=c 并将每次点击记录到表中。
======================================================================== userid | page | ref | response_time | dtmTime ======================================================================== 54321 | profile.aspx | birthday | 123 | 2009-12-23 11:05:00 12345 | compose.aspx | search | 456 | 2009-12-23 11:05:02 54321 | payment.aspx | gift | 234 | 2009-12-23 11:05:01 12345 | chat.aspx | search | 567 | 2009-12-23 11:05:03 ..... | ............ | ........ | ... | ...................
我认为这是一个好的开始。我只是不知道如何处理这些信息。 是否有适当的方法来处理这些信息？
Have you noticed that almost every links in facebook have ref query string?
I belive that, with that ref, facebook somehow track and study their user behaviour. this could be their secret recipe of making a better usability.
So, I am trying out the same thing, change http://a.com/b.aspx
to
http://a.com/b.aspx?ref=c and log every hits into a table.
======================================================================== userid | page | ref | response_time | dtmTime ======================================================================== 54321 | profile.aspx | birthday | 123 | 2009-12-23 11:05:00 12345 | compose.aspx | search | 456 | 2009-12-23 11:05:02 54321 | payment.aspx | gift | 234 | 2009-12-23 11:05:01 12345 | chat.aspx | search | 567 | 2009-12-23 11:05:03 ..... | ............ | ........ | ... | ...................
I think it's a good start. I just don't know what to do with these informations.
Is there any appropriate methodology to process these informations?
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研究表明快速响应不仅是一种改进的方法网站的可用性。这也是提高转化率或网站使用率的一种方法。
人们根本不想等待。因此，我们跟踪响应时间百分位数我们的网站。此外，这些数据的良好可视化有助于衡量性能优化工作和监控服务器运行状况。
以下是使用 Google 图表生成的示例：
这看起来很糟糕！响应时间> 4000 毫秒肯定表明存在对可用性有相当大影响的性能问题。有时 800 毫秒百分位（我们认为这是我们应用程序的一个很好的指标）低至 77%。我们通常尝试将 800 毫秒的百分位设置为 95%。所以看起来前面还有一些严肃的工作......但是图像很好，不是吗？ ;)
Research has shown that fast responses are a way to improve not only usability of a website. It's also a way to improve conversion rates or site usage in general.
People simply don't want to wait. Therefore, we track response time percentiles for our sites. Additionally, nice visualization of this data helps with measuring performance optimization efforts and monitoring server health.
Here is an example generated using Google Charts:
That looks bad! Response times of > 4000 ms certainly indicate performance problems that have a considerable impact on usability. At times the 800 ms percentile (which we consider a good indicator for our apps) was as low as 77%. We typically try to get the 800 ms percentile at 95%. So this looks like there's some serious work ahead ... but the image is nice, isn't it? ;)
这是第二个答案前者仅涉及响应时间统计信息。
ref查询字符串允许识别来源，尤其是输入转化漏斗。因此，您可能会做出诸如“N 美元的收入来自用户点击页面 Y 上的链接 X”之类的陈述。现在您可以尝试将链接 X 修改为 X1 并查看是否会增加此页面的收入。这将是您进入 A/B 测试 和 多变量分析。 Google 网站优化工具正是用于此目的的工具。Here's a second answer as the former was only about response time statistics.
The
refquery string allows to identify the sources, especially of people entering a Conversion funnel. So you might make statements like "N $ of revenue come from users clicking link X on page Y". Now you could try to modify link X to X1 and see if it increases revenue from this page. That would be your first step into A/B Testing and Multivariate Analysis. Google Website Optimizer is a tool exactly for this purpose.Facebook 使用它们来观察用户界面的使用情况（我相信），这样他们就可以看到人们点击更多的位置（徽标或个人资料链接），并考虑相应地更改 UI，以便更好地进行交互。
您也许还可以使用它来查看常见的使用模式。例如，如果人们遵循某个链
配置文件 ->生日->现在->发送您可能会考虑添加一个功能或特性，以便在该人生日时在他们的个人资料上“发送礼物”。只是一个想法。Well facebook uses them for user interface usage observation (I believe) so they see where people click more (logo or profile link) and they consider changing the UI accordingly in order to make interaction better.
You might also be able to use it to see common patterns in usage. For instance, if people follow a certain chain
profile -> birthday -> present -> sendyou might consider adding in a function or feature to "send present" on their profile when it's that persons birthday. Just a thought.为了充分利用网站统计数据，您需要考虑用户想要实现的目标以及您希望他们实现的目标。这些是您网站的目标
对于电子商务网站来说，这是非常容易的。典型的目标可能是：
然后，您可以使用统计数据来查看人们是否完成了网站的目标。为此，您需要收集访问者信息，以便您可以查看他们访问过的所有页面。
一旦您可以查看用户访问过的所有页面以及他们访问这些页面的顺序，您就可以看到他们一直在做什么。您可以寻找他们原本打算买东西但后来没有购买的退出点。您可以识别不成功的产品搜索。你可以做各种各样的事情。然后，您可以尝试解决这些问题并观察统计数据，看看是否有帮助。
您收集的统计数据是一个好的开始，但收集良好的统计数据并整理它们很复杂。我建议使用现有的统计数据包，我个人使用 Google Analytics，但还有其他可用的。
To make the best use of your website statistics you need to think about what your users are trying to acheive and what you want them to achieve. These are your site's goals
For an ecomerce site this is failrly easy. Typical goals might be:
You can then use your stats to see if people are completing the site's goals. To do this you need to collect a visitors information together so you can see all the pages they have been to.
Once you can look at all the pages a user has visitted and the sequence they visitted them in you can see what they have been doing. You can look for drop out points where they were about to buy something and then didn't. You can identify product searches that were unsuccessful. You can do all sorts. You can then try and fix these issues and watch the stats to see if it has helped.
The stats you're collecting are a good start, but collecting good stats and collating them is complicated. I'd suggest using an existing stats package I personally use Google Analytics, but there are others available.