lab-rat

A JavaScript AB testing framework, ported from http://www.github.com/guardian/frontend.

AB testing's goal is to identify changes to web pages that increase or maximize an outcome of interest.

Goals

• 100% client-side.
• Basic segmentation of audience.
• Deterministic segmentation - allowing allocation of users in to tests based on some external key (Eg, user name)
• Fixed duration tests - that automatically close and delete their footprint.
• Isolation of each test audience - so a user can not accidently be in several tests at once.
• Agnostic of where the data is logged - most companies have their own customer data repoisitories.
• Minimal payload - ~1kb (minified + gzip) with no additional cookie overhead created.

Experiment profiles

Each AB test is represented by a JavaScript object describing the profile of the test to be undertaken.

var p = { 
    id: 'background', // A unique name for the test.
    audience: 0.1, // A percent of the users you want to run the test on, Eg. 0.1 = 10%.
    audienceOffset: 0.8, // A segment of the users you want to target the test at. 
    expiry: new Date(2015, 1, 1), // The end date of the test 
    variants: [ // An array of two functions - the first representing the control group, the second the variant.
        { 
            id: 'control',
            test: function () {
                document.body.style.backgroundColor = '#ffffff';
            }
        },
        {
            id: 'pink',
            test: function () {
                document.body.style.backgroundColor = '#c52720'; // this test turns the page background red
            }
        }
    ],
    canRun: function () { // Preconditions that all the test to run, or not
        return true;
    }
}

Demo

Compile the code and open the example.html file in ./demos

Running a test

With developer tools, we can feed the above profile in to the AB test framework, force our variant to 'pink', then run the test.

var a = new Ab(p, { variant: 'pink' })
a.run();

You should see the page background turn pink, and running the test on every subsequent visit will turn the page pink until the test has expired.

Allocate yourself in to the control group and re-run the test and the background should turn white.

var a = new Ab(p, { variant: 'control' })
a.run();

For the duration of the test we can track the data of that user (say, pages per visit or scroll depth) and compare with the control group to see if that variant had the positive impact we thought it would have.

Segmentation

You can inspect data the tests create in local storage.

Firstly, each test subject is allocated a persistant id (an integer) that is shared across tests.

localStorage.getItem('ab__uid'); // Eg, "3467"

Next, each test remembers the variant the user is in over mulitple sessions,

localStorage.getItem('ab__background'); // Eg, '{"id":"background","variant":"pink"}'

In the real world we want the test subjects allocated randomly in to a variants (or excluded from the test), so we don't specify the variant in the Ab constructor and invoke segment() instead, before running the experiment,

var a = new Ab(profile);
a.segment();
a.run();

The segment() function decides if a user should be in the test, and, if they are, splits the audience between a 'control' group and a number of 'variants'.

Segmentation is fairly trivial at the moment, but later it can be used to target certain types of users (Eg, every international user who has visited more than 3 times a week, or persona x).