google-analytics - 破解 Google Analytics 进行多变量测试？

Question

我想在我的站点中实现 MVT（多变量测试），并想知道是否可以使用 Google Analytics 和一些服务器端代码来执行此操作，而不是依赖昂贵的解决方案。

有建议的方法吗？

一种想法是让服务器端代码随机绘制一个元组，其中包含将出现的元素替代项，并将其中一个 GATC 代码（例如活动内容）设置为其字符串表示形式。例如，代码为文本绘制选项 #2，为图像绘制选项 #3，并将活动内容设置为“text2_image3”。以后可以很容易地在 Excel 或其他工具中分析结果。

它会起作用吗？有更好的解决方案吗？

score 2 · Accepted Answer

2

于 2013-02-03T20:31:51.123 回答

score 2 · Accepted Answer

If you wanted to go with a homemade solution instead of existing services (e.g. Optimizely, experimently, or convert) I'd suggest the following:

Generate the code

Your server side code generates the recipes (layouts) for the user based on whatever metrics you want . This is commonly just a % of traffic split. Don't forget to include the unaltered version to compare your data to.
Give it an identifier

When your server side code generates the recipes, it should include the a specific value for a custom variable for that page. This unique value should include an identifier to each recipe displayed on the page. E.g. if you have menu A, headline D, and body image G you'd have A:D:G. If you had menu C, headline E, body image I, you'd have C:E:I.

The type of custom variable depends on your test. Session level would allow you to see how that specific recipe affected the user within a visit. A more standard method would be to set it to a visitor level would allow your recipes to have attribution on returning visits.
Run the test & analyze the results

From there, run the test, gather your data. Once you feel you have statistically significant results, you can stop the test and start to fully analyze your data.

The names of the recipes should be unique. For instance, I used A - C for the menu, D - F for the headline, and G - I for the body image. This allows you to create segments based off of that recipe.
Don't forget to include the control recipe IDs in your test!
If you're running multiple tests (even if not at the same time), I'd strongly suggest prefixing the custom variable value with the test name / identifier.

This is essentially what Google Experiments does with A/B testing on their backend.

score 0 · Accepted Answer

我发现了这个项目，虽然有点老，但似乎很有趣：https ://github.com/jamesyu/cohorts

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