From 068dd06727144559ff9624431d7818d93e848b20 Mon Sep 17 00:00:00 2001 From: Karl Hobley Date: Thu, 17 Dec 2020 12:50:53 +0000 Subject: [PATCH] Add a readme --- README.md | 41 +++++++++++++++++++++++++++++++++++++++++ screenshot.png | Bin 0 -> 203116 bytes 2 files changed, 41 insertions(+) create mode 100644 README.md create mode 100644 screenshot.png diff --git a/README.md b/README.md new file mode 100644 index 0000000..3c541ce --- /dev/null +++ b/README.md @@ -0,0 +1,41 @@ +# Wagtail A/B Testing + +An A/B testing package for Wagtail that allows creating A/B tests using revisions. + +Key features: + + - Create an A/B test on any page from within Wagtail + - Tests using page revisions (no need to create separate pages for the variants) + - Prevents users from editing the page while a test is in progress + - Calculates confidence using a Pearson's chi squared test + +![Screenshot of Wagtail A/B Testing](/screenshot.png) + +## Usage + +Any user with the "Create A/B test" permission (given to admins and moderators by default) should be able to create an A/B test by clicking "Save and create A/B test" from the page's action menu. + +This will show a diff of the content in the latest draft against the current live version of the page (as these will be tested). Once they've confirmed that, the user is taken to a form to insert the test name/hypothesis, select a goal, and a sample size. + +While the test is running, user's can pause/restart and end the test at any time. While the test is running/paused, nobody can edit the page as this may affect the accuracy of the test results. If you absolutely must edit the page while a test is running, you should cancel the test, edit the page, and start a new test. + +When the number of participants reaches the desired sample size, the test is stopped and the results are displayed to the user. At this point, the user may choose to publish the latest draft (aka the "variant") or revert back to the existing live version (aka the "control"). + +Wagtail A/B testing will also tell the user if one of the results is a clear winner or if there is no clear winner, this is worked out using a Chi Squared test that takes into account the total sample size (higher sample size means it will accept a smaller difference as a clear result) as well as the conversion rates. + + +## Installation + +Firstly, install the ``wagtail-ab-testing`` package from PyPI: + + pip install wagtail-ab-testing + +Then add it into ``INSTALLED_APPS``: + +```python +INSTALLED_APPS = [ + # ... + 'wagtail_ab_testing', + # ... +] +``` diff --git a/screenshot.png b/screenshot.png new file mode 100644 index 0000000000000000000000000000000000000000..e7c801771b0fce19476a93775ed99f7821f521fc GIT binary patch literal 203116 zcmeFZc|4T;_dh;TsBCS>8rl#lYuS>mQY2esDO;B8$-Y!V$yS!iRw1%YB|9@pA`)3+ 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