An A/B testing engine
To use this engine, create one or more experiments and stick them in a container. Each experiment is composed of a bunch of variations which are randomly picked/served to you. Once you obtain a variation, use it to render some content or make some sort of a decision.
The container's job is to select the correct experiments for each visitor based on each experiment's targeting expression. Thusly, to get a variation one would call pick() twice, once on the container and once on the experiment.
Further information about the targeting experssion syntax can be found here: pickpick-targeting-compiler
Also, please take a look at our examples
npm i -S pickpick
Let's say we have a website with two pages buy and index and we want to run 3 experiments:
- on the
buypage testcolor button - on the
buypage testprice - on the
indexpage testtext
const { Experiment, ExperimentContainer } = require('pickpick')
// first create the experiments:
let e1 = Experiment.create({
name: 'buy page button color experiment',
id: '953d6fe0',
variations: [
{ object: '#ff0000', weight: 4 },
{ object: '#ff0000', weight: 1 },
{ object: '#00ff00', weight: 1 }
],
targeting: '_.path in ["buy", "index"]'
})
let e2 = Experiment.create({
name: 'buy page price experiment',
id: 'a40f09ac',
variations: [
{ object: 25 },
{ object: 35 },
{ object: 45 }
],
targeting: '_.path !== "home" && page !== "foo"'
})
let e3 = Experiment.create({
name: 'index text experiment',
id: 'ac49ef42',
variations: [
{ object: 'hi' },
{ object: 'hello' },
{ object: 'welcome' }
],
targeting: '_.path === "index"'
})
// now create a container:
let experiments = [e1, e2, e3]
let container = ExperimentContainer.create({ experiments })
// simulate a visitor that needs a determination about which variation of which experiment he gets:
let visitor = { page: 'index' }
for (let i = 0; i < 10; i++) {
let experiment = container.pick(visitor)
if (!experiment) {
// no experiment that targets this user
// handle this with defaults
console.log('default goes here')
} else {
console.log(`selected experiment '${experiment.name}' for '${JSON.stringify(visitor)}'`)
let variation = experiment.pick()
console.log(`selected variation is ${variation}`)
}
}An A/B test experiment contains one or more variations and a definition of targeting.
Experiments are serializable and can be created using classes from this engine or object literals. For example:
const { Experiment } = require('pickpick')
const e1 = Experiment.create({
name: 'my experiment',
id: 'foo',
variations: [
{ object: 1, weight: 1 },
{ object: 2, weight: 1 },
{ object: 3, weight: 1 }
],
targeting: '_.geo === "US"'
})$0Object$0.name$0.id$0.variations(optional, default[])$0.targeting(optional, defaultTargeting.default())$0.userData
randomly select one variation from the Variations set
Returns Variant the value contained within the selected variation
check if this experiment matches the input targeting
targetingObject
Returns Boolean
add another variation to this experiment
iterate over the variations contained in this experiment
Targeting
expressionString see pickpick-targeting-compiler for more detailsuserEnvironmentObject (optional, default{})
check if the input data is matched by this targeting instance
inputTargetingObject is normally a simple js object
Returns Boolean
access this Targeting's expression
Returns String
iterate over the features that participate in the targeting
check if a feature is part of this targeting instance
featureString a name of a feature, e.ggeo
Returns Boolean
A variation attaches weight to a piece of data. Variations are used in Experiments and ExperimentContainers
$0Object$0.object$0.weight(optional, default1)
lib/ExperimentContainer.js:38-239
Contains one or more experiments and routes traffic evenly to each of them based on their targeting. The following is an example of using a container to host several experiments, pick on thats appropriate for a single visitor's targeting and then access a variation from the selected experiment:
const { ExperimentContainer, Experiment } = require('pickpick')
const experiments = [
Experiment.create(...),
Experiment.create(...),
Experiment.create(...)
]
const container = ExperimentContainer.create({ experiments })
let experiment = container.pick({ geo: 'US', page: 'index.html '})
if (experiment) {
let variation = experiment.pick()
// do something with the variation data
} else {
console.log('no experiments that match this targeting were found')
}__seednumber just for testing / predictable engine results
lib/ExperimentContainer.js:77-102
Add an experiment to this container. Inside a container experiments must have unique ids. This method can accept different kinds of experiment expressions:
- an instance of Experiment:
container.add(Experiment.create(...))- An instance of Variation where it's object is an Experiment: ```js container.add(Variation.create(Experiment.create(...))) ````
- An instance of Variation where it's object is an Expriment defined as an object literal:
container.add(Variation.create({... experiment data ...}))- A variation object literal wrapping an experiment object literal, this is useful in deserialization scenarios:
container.add({ object: {... experiment data }, weight: 5 })experiments...any
lib/ExperimentContainer.js:131-151
The pick method accepts a targeting object and randomly selects an experiment from a set of experiments that match the targeting specification.
By default, selection is random and even, however, bias can be applied by specifying a weight when adding an experiment to the container (see ExperimentContainer.add())
Weights are considered at the moment of selection from the current set of matching experiments, therefor, careful planning of targeting is required to achieve accurate traffic distribution betwee experiments.
For example, consider two experiments, E1, that targets { geo: 'US', page: '*' } and E2 that targets
{ geo: 'US', page: 'index.html' }. If both had the weight 1, given the following stream
of visitors:
{ geo: 'US', page: 'sale.html' }
{ geo: 'US', page: 'index.html' }
{ geo: 'US', page: 'sale.html' }
{ geo: 'US', page: 'index.html' }
Then it is more likely that E1 will receive more traffic than E2 since E1 competes with E2 evenly on index.html
page but not on sale.html
targetingTargeting
Returns Experiment an experiment that matches this targeting or null if none is found.
lib/ExperimentContainer.js:159-161
An iterator over all the targeting features from all the experiments added to this container
Returns Iterator
lib/ExperimentContainer.js:175-177
iterate over all the experiments in this container:
let container = ExperimentContainer.create(...)
for (let experiment of container) {
console.log(experiment.id)
}
Returns ObjectIterator
lib/ExperimentContainer.js:184-188
check if this container contains the specified experiment
experimentExpriment
Returns Boolean
lib/ExperimentContainer.js:195-201
check if this container contains an experiment using an id
experimentIdString
Returns Boolean
lib/ExperimentContainer.js:208-215
serialize this container with all it's experiments
Returns Object