amazonka-evidently-2.0: Amazon CloudWatch Evidently SDK.
Copyright(c) 2013-2023 Brendan Hay
LicenseMozilla Public License, v. 2.0.
MaintainerBrendan Hay
Stabilityauto-generated
Portabilitynon-portable (GHC extensions)
Safe HaskellSafe-Inferred
LanguageHaskell2010

Amazonka.Evidently.CreateExperiment

Description

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.

Synopsis

Creating a Request

data CreateExperiment Source #

See: newCreateExperiment smart constructor.

Constructors

CreateExperiment' 

Fields

  • description :: Maybe Text

    An optional description of the experiment.

  • onlineAbConfig :: Maybe OnlineAbConfig

    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.

  • randomizationSalt :: Maybe Text

    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.

  • samplingRate :: Maybe Natural

    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.

  • segment :: Maybe Text

    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.

  • tags :: Maybe (HashMap Text Text)

    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.

     <p>You can associate as many as 50 tags with an experiment.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>
  • metricGoals :: NonEmpty MetricGoalConfig

    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.

  • name :: Text

    A name for the new experiment.

  • project :: Text

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

  • treatments :: [TreatmentConfig]

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

Instances

Instances details
ToJSON CreateExperiment Source # 
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ToHeaders CreateExperiment Source # 
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ToPath CreateExperiment Source # 
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ToQuery CreateExperiment Source # 
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AWSRequest CreateExperiment Source # 
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Associated Types

type AWSResponse CreateExperiment #

Generic CreateExperiment Source # 
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Associated Types

type Rep CreateExperiment :: Type -> Type #

Read CreateExperiment Source # 
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Show CreateExperiment Source # 
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NFData CreateExperiment Source # 
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Methods

rnf :: CreateExperiment -> () #

Eq CreateExperiment Source # 
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Hashable CreateExperiment Source # 
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type AWSResponse CreateExperiment Source # 
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type Rep CreateExperiment Source # 
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newCreateExperiment Source #

Create a value of CreateExperiment with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

CreateExperiment, createExperiment_description - An optional description of the experiment.

$sel:onlineAbConfig:CreateExperiment', createExperiment_onlineAbConfig - 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.

CreateExperiment, createExperiment_randomizationSalt - 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.

CreateExperiment, createExperiment_samplingRate - 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.

CreateExperiment, createExperiment_segment - 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.

CreateExperiment, createExperiment_tags - 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.

 <p>You can associate as many as 50 tags with an experiment.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

CreateExperiment, createExperiment_metricGoals - 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.

CreateExperiment, createExperiment_name - A name for the new experiment.

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

CreateExperiment, createExperiment_treatments - An array of structures that describe the configuration of each feature variation used in the experiment.

Request Lenses

createExperiment_description :: Lens' CreateExperiment (Maybe Text) Source #

An optional description of the experiment.

createExperiment_onlineAbConfig :: Lens' CreateExperiment (Maybe OnlineAbConfig) Source #

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.

createExperiment_randomizationSalt :: Lens' CreateExperiment (Maybe Text) Source #

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.

createExperiment_samplingRate :: Lens' CreateExperiment (Maybe Natural) Source #

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.

createExperiment_segment :: Lens' CreateExperiment (Maybe Text) Source #

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.

createExperiment_tags :: Lens' CreateExperiment (Maybe (HashMap Text Text)) Source #

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.

 <p>You can associate as many as 50 tags with an experiment.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html">Tagging Amazon Web Services resources</a>.</p>

createExperiment_metricGoals :: Lens' CreateExperiment (NonEmpty MetricGoalConfig) Source #

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.

createExperiment_name :: Lens' CreateExperiment Text Source #

A name for the new experiment.

createExperiment_project :: Lens' CreateExperiment Text Source #

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

createExperiment_treatments :: Lens' CreateExperiment [TreatmentConfig] Source #

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

Destructuring the Response

data CreateExperimentResponse Source #

See: newCreateExperimentResponse smart constructor.

Constructors

CreateExperimentResponse' 

Fields

Instances

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Generic CreateExperimentResponse Source # 
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Associated Types

type Rep CreateExperimentResponse :: Type -> Type #

Read CreateExperimentResponse Source # 
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Show CreateExperimentResponse Source # 
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NFData CreateExperimentResponse Source # 
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Eq CreateExperimentResponse Source # 
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type Rep CreateExperimentResponse Source # 
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type Rep CreateExperimentResponse = D1 ('MetaData "CreateExperimentResponse" "Amazonka.Evidently.CreateExperiment" "amazonka-evidently-2.0-Es2fJk98R0DAUPYaVkZSYC" 'False) (C1 ('MetaCons "CreateExperimentResponse'" 'PrefixI 'True) (S1 ('MetaSel ('Just "httpStatus") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Int) :*: S1 ('MetaSel ('Just "experiment") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedStrict) (Rec0 Experiment)))

newCreateExperimentResponse Source #

Create a value of CreateExperimentResponse with all optional fields omitted.

Use generic-lens or optics to modify other optional fields.

The following record fields are available, with the corresponding lenses provided for backwards compatibility:

$sel:httpStatus:CreateExperimentResponse', createExperimentResponse_httpStatus - The response's http status code.

$sel:experiment:CreateExperimentResponse', createExperimentResponse_experiment - A structure containing the configuration details of the experiment that you created.

Response Lenses

createExperimentResponse_experiment :: Lens' CreateExperimentResponse Experiment Source #

A structure containing the configuration details of the experiment that you created.