/AWS1/CL_EVY=>CREATEEXPERIMENT()

About CreateExperiment

Creates an Evidently experiment. Before you create an experiment, you must create the feature to use for the experiment.

An experiment helps you make feature design decisions based on evidence and data. An experiment can test as many as five variations at once. Evidently collects experiment data and analyzes it by statistical methods, and provides clear recommendations about which variations perform better.

You can optionally specify a segment to have the experiment consider only certain audience types in the experiment, such as using only user sessions from a certain location or who use a certain internet browser.

Don't use this operation to update an existing experiment. Instead, use UpdateExperiment.

Method Signature

IMPORTING

Required arguments:

IV_PROJECT TYPE /AWS1/EVYPROJECTREF /AWS1/EVYPROJECTREF

The name or ARN of the project that you want to create the new experiment in.

IV_NAME TYPE /AWS1/EVYEXPERIMENTNAME /AWS1/EVYEXPERIMENTNAME

A name for the new experiment.

IT_TREATMENTS TYPE /AWS1/CL_EVYTREATMENTCONFIG=>TT_TREATMENTCONFIGLIST TT_TREATMENTCONFIGLIST

An array of structures that describe the configuration of each feature variation used in the experiment.

IT_METRICGOALS TYPE /AWS1/CL_EVYMETRICGOALCONFIG=>TT_METRICGOALCONFIGLIST TT_METRICGOALCONFIGLIST

An array of structures that defines the metrics used for the experiment, and whether a higher or lower value for each metric is the goal.

Optional arguments:

IV_DESCRIPTION TYPE /AWS1/EVYDESCRIPTION /AWS1/EVYDESCRIPTION

An optional description of the experiment.

IV_RANDOMIZATIONSALT TYPE /AWS1/EVYRANDOMIZATIONSALT /AWS1/EVYRANDOMIZATIONSALT

When Evidently assigns a particular user session to an experiment, it must use a randomization ID to determine which variation the user session is served. This randomization ID is a combination of the entity ID and randomizationSalt. If you omit randomizationSalt, Evidently uses the experiment name as the randomizationSalt.

IV_SAMPLINGRATE TYPE /AWS1/EVYSPLITWEIGHT /AWS1/EVYSPLITWEIGHT

The portion of the available audience that you want to allocate to this experiment, in thousandths of a percent. The available audience is the total audience minus the audience that you have allocated to overrides or current launches of this feature.

This is represented in thousandths of a percent. For example, specify 10,000 to allocate 10% of the available audience.

IO_ONLINEABCONFIG TYPE REF TO /AWS1/CL_EVYONLINEABCONFIG /AWS1/CL_EVYONLINEABCONFIG

A structure that contains the configuration of which variation to use as the "control" version. tThe "control" version is used for comparison with other variations. This structure also specifies how much experiment traffic is allocated to each variation.

IV_SEGMENT TYPE /AWS1/EVYSEGMENTREF /AWS1/EVYSEGMENTREF

Specifies an audience segment to use in the experiment. When a segment is used in an experiment, only user sessions that match the segment pattern are used in the experiment.

IT_TAGS TYPE /AWS1/CL_EVYTAGMAP_W=>TT_TAGMAP TT_TAGMAP

Assigns one or more tags (key-value pairs) to the experiment.

Tags can help you organize and categorize your resources. You can also use them to scope user permissions by granting a user permission to access or change only resources with certain tag values.

Tags don't have any semantic meaning to Amazon Web Services and are interpreted strictly as strings of characters.

You can associate as many as 50 tags with an experiment.

For more information, see Tagging Amazon Web Services resources.

RETURNING

OO_OUTPUT TYPE REF TO /AWS1/CL_EVYCREEXPERIMENTRSP /AWS1/CL_EVYCREEXPERIMENTRSP