Eksperimen dalam kampanye

Eksperimen intra-kampanye digunakan untuk menguji fitur tertentu dalam satu kampanye. Tidak seperti eksperimen yang dikelola sistem, yang membagi traffic antara kampanye kontrol dan perlakuan, eksperimen intra-kampanye membagi traffic dalam kampanye, berdasarkan apakah fitur diaktifkan atau tidak.

Alur kerja ini didukung untuk nilai ExperimentType berikut:

ADOPT_AI_MAX
Menguji dampak fitur AI Maksimal pada kampanye Penelusuran.
ADOPT_BROAD_MATCH_KEYWORDS
Menguji dampak kata kunci pencocokan luas pada kampanye Penelusuran.
PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION
Khusus digunakan untuk menguji fitur Performa Maksimal: penyesuaian teks dan perluasan URL final. Memungkinkan AI Google mengirim traffic ke halaman landing yang relevan dan membuat aset teks agar lebih cocok dengan kueri penelusuran.

Penyiapan

  1. Tentukan Experiment (dengan status ditetapkan ke ENABLED), yang memberikan jenis eksperimen, ExperimentArm kontrol, dan ExperimentArm perlakuan:
    • Untuk ADOPT_AI_MAX dan ADOPT_BROAD_MATCH_KEYWORDS, grup kontrol dan grup perlakuan harus merujuk ke kampanye yang sama di campaigns.
    • Untuk PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION, hanya grup perlakuan yang menentukan kampanye Performa Maksimal di campaigns (biarkan campaigns tidak ditetapkan di grup kontrol).
  2. Untuk ADOPT_AI_MAX, buat update CampaignOperation dengan mask kolom untuk mengaktifkan ai_max_setting.enable_ai_max dan mengonfigurasi asset_automation_settings.

  3. Kirim permintaan GoogleAdsService.Mutate yang menyertakan operasi mutasi untuk membuat eksperimen dan grup eksperimen, serta (untuk ADOPT_AI_MAX) mengaktifkan fitur pengujian di kampanye.

Untuk ADOPT_AI_MAX dan ADOPT_BROAD_MATCH_KEYWORDS, traffic harus dibagi secara merata (50/50) dalam kampanye sehingga 50% traffic terekspos ke fitur yang diaktifkan (grup perlakuan) dan 50% tidak (grup kontrol). PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION mendukung pemisahan traffic kustom yang berjumlah total 100.

Java

// Create the experiment resource name using a temporary ID.
String experimentResourceName = ResourceNames.experiment(customerId, -1L);

// Create the experiment.
Experiment experiment =
    Experiment.newBuilder()
        .setResourceName(experimentResourceName)
        .setName("ADOPT_AI_MAX Experiment #" + UUID.randomUUID())
        .setType(ExperimentType.ADOPT_AI_MAX)
        .build();
MutateOperation experimentOperation =
    MutateOperation.newBuilder()
        .setExperimentOperation(ExperimentOperation.newBuilder().setCreate(experiment).build())
        .build();

// Create the control arm. Both arms in an intra-campaign experiment reference the same base
// campaign.
ExperimentArm controlArm =
    ExperimentArm.newBuilder()
        .setExperiment(experimentResourceName)
        .setName("Control Arm")
        .setControl(true)
        .setTrafficSplit(50)
        .addCampaigns(ResourceNames.campaign(customerId, campaignId))
        .build();
MutateOperation controlArmOperation =
    MutateOperation.newBuilder()
        .setExperimentArmOperation(
            ExperimentArmOperation.newBuilder().setCreate(controlArm).build())
        .build();

// Create the treatment arm.
ExperimentArm treatmentArm =
    ExperimentArm.newBuilder()
        .setExperiment(experimentResourceName)
        .setName("Treatment Arm")
        .setControl(false)
        .setTrafficSplit(50)
        .addCampaigns(ResourceNames.campaign(customerId, campaignId))
        .build();
MutateOperation treatmentArmOperation =
    MutateOperation.newBuilder()
        .setExperimentArmOperation(
            ExperimentArmOperation.newBuilder().setCreate(treatmentArm).build())
        .build();

// Create a campaign operation with an update mask to enable AI Max and configure asset
// automation settings.
// Note: For intra-campaign experiments, these settings are applied to the base campaign but are
// only active for the treatment traffic split.
Campaign campaign =
    Campaign.newBuilder()
        .setResourceName(ResourceNames.campaign(customerId, campaignId))
        .setAiMaxSetting(AiMaxSetting.newBuilder().setEnableAiMax(true).build())
        .addAssetAutomationSettings(
            AssetAutomationSetting.newBuilder()
                .setAssetAutomationType(AssetAutomationType.TEXT_ASSET_AUTOMATION)
                .setAssetAutomationStatus(AssetAutomationStatus.OPTED_IN)
                .build())
        .addAssetAutomationSettings(
            AssetAutomationSetting.newBuilder()
                .setAssetAutomationType(
                    AssetAutomationType.FINAL_URL_EXPANSION_TEXT_ASSET_AUTOMATION)
                .setAssetAutomationStatus(AssetAutomationStatus.OPTED_IN)
                .build())
        .build();

CampaignOperation campaignOp =
    CampaignOperation.newBuilder()
        .setUpdate(campaign)
        .setUpdateMask(FieldMasks.allSetFieldsOf(campaign))
        .build();
MutateOperation campaignMutateOperation =
    MutateOperation.newBuilder().setCampaignOperation(campaignOp).build();

// Send all mutate operations in a single Mutate request.
List<MutateOperation> mutateOperations =
    ImmutableList.of(
        experimentOperation,
        controlArmOperation,
        treatmentArmOperation,
        campaignMutateOperation);

try (GoogleAdsServiceClient googleAdsServiceClient =
    googleAdsClient.getLatestVersion().createGoogleAdsServiceClient()) {

  MutateGoogleAdsRequest request =
      MutateGoogleAdsRequest.newBuilder()
          .setCustomerId(Long.toString(customerId))
          .addAllMutateOperations(mutateOperations)
          .build();

  MutateGoogleAdsResponse response = googleAdsServiceClient.mutate(request);
      

C#

// Create the experiment resource name using a temporary ID.
string experimentResourceName = ResourceNames.Experiment(customerId, -1);

// Create the experiment.
MutateOperation experimentOperation = new MutateOperation()
{
    ExperimentOperation = new ExperimentOperation()
    {
        Create = new Experiment()
        {
            ResourceName = experimentResourceName,
            Name = $"ADOPT_AI_MAX Experiment #{ExampleUtilities.GetRandomString()}",
            Type = ExperimentType.AdoptAiMax
        }
    }
};

// Create the control arm. Both arms in an intra-campaign experiment
// reference the same base campaign.
MutateOperation controlArmOperation = new MutateOperation()
{
    ExperimentArmOperation = new ExperimentArmOperation()
    {
        Create = new ExperimentArm()
        {
            Experiment = experimentResourceName,
            Name = "Control Arm",
            Control = true,
            TrafficSplit = 50,
            Campaigns = { ResourceNames.Campaign(customerId, campaignId) }
        }
    }
};

// Create the treatment arm.
MutateOperation treatmentArmOperation = new MutateOperation()
{
    ExperimentArmOperation = new ExperimentArmOperation()
    {
        Create = new ExperimentArm()
        {
            Experiment = experimentResourceName,
            Name = "Treatment Arm",
            Control = false,
            TrafficSplit = 50,
            Campaigns = { ResourceNames.Campaign(customerId, campaignId) }
        }
    }
};

// Create a campaign operation with an update mask to enable AI Max and
// configure asset automation settings.
// Note: For intra-campaign experiments, these settings are applied to the
// base campaign but are only active for the treatment traffic split.
Campaign campaign = new Campaign()
{
    ResourceName = ResourceNames.Campaign(customerId, campaignId),
    AiMaxSetting = new Campaign.Types.AiMaxSetting { EnableAiMax = true }
};

campaign.AssetAutomationSettings.Add(new Campaign.Types.AssetAutomationSetting
{
    AssetAutomationType = AssetAutomationType.TextAssetAutomation,
    AssetAutomationStatus = AssetAutomationStatus.OptedIn
});

campaign.AssetAutomationSettings.Add(new Campaign.Types.AssetAutomationSetting
{
    AssetAutomationType = AssetAutomationType.FinalUrlExpansionTextAssetAutomation,
    AssetAutomationStatus = AssetAutomationStatus.OptedIn
});

MutateOperation campaignOperation = new MutateOperation()
{
    CampaignOperation = new CampaignOperation()
    {
        Update = campaign,
        UpdateMask = FieldMasks.AllSetFieldsOf(campaign)
    }
};

// Send all mutate operations in a single Mutate request.
List<MutateOperation> mutateOperations = new List<MutateOperation>
{
    experimentOperation,
    controlArmOperation,
    treatmentArmOperation,
    campaignOperation
};

MutateGoogleAdsResponse response = googleAdsService.Mutate(
    customerId.ToString(), mutateOperations);
      

PHP

This example is not yet available in PHP; you can take a look at the other languages.
    

Python

# Create the experiment resource name using a temporary ID.
experiment_resource_name = googleads_service.experiment_path(
    customer_id, "-1"
)

# Create the experiment.
experiment_operation = client.get_type("MutateOperation")
experiment = experiment_operation.experiment_operation.create
experiment.resource_name = experiment_resource_name
experiment.name = f"ADOPT_AI_MAX Experiment #{uuid4()}"
experiment.type_ = client.enums.ExperimentTypeEnum.ADOPT_AI_MAX

# Create the control arm. Both arms in an intra-campaign experiment
# reference the same base campaign.
control_arm_operation = client.get_type("MutateOperation")
control_arm = control_arm_operation.experiment_arm_operation.create
control_arm.experiment = experiment_resource_name
control_arm.name = "Control Arm"
control_arm.control = True
control_arm.traffic_split = 50
control_arm.campaigns.append(
    googleads_service.campaign_path(customer_id, campaign_id)
)

# Create the treatment arm.
treatment_arm_operation = client.get_type("MutateOperation")
treatment_arm = treatment_arm_operation.experiment_arm_operation.create
treatment_arm.experiment = experiment_resource_name
treatment_arm.name = "Treatment Arm"
treatment_arm.control = False
treatment_arm.traffic_split = 50
treatment_arm.campaigns.append(
    googleads_service.campaign_path(customer_id, campaign_id)
)

# Create a campaign operation with an update mask to enable AI Max and
# configure asset automation settings.
# Note: For intra-campaign experiments, these settings are applied to the
# base campaign but are only active for the treatment traffic split.
campaign_operation = client.get_type("MutateOperation")
campaign = campaign_operation.campaign_operation.update
campaign.resource_name = googleads_service.campaign_path(
    customer_id, campaign_id
)
campaign.ai_max_setting.enable_ai_max = True

for asset_automation_type_enum in [
    client.enums.AssetAutomationTypeEnum.TEXT_ASSET_AUTOMATION,
    client.enums.AssetAutomationTypeEnum.FINAL_URL_EXPANSION_TEXT_ASSET_AUTOMATION,
]:
    asset_automation_setting = client.get_type(
        "Campaign"
    ).AssetAutomationSetting()
    asset_automation_setting.asset_automation_type = (
        asset_automation_type_enum
    )
    asset_automation_setting.asset_automation_status = (
        client.enums.AssetAutomationStatusEnum.OPTED_IN
    )
    campaign.asset_automation_settings.append(asset_automation_setting)

client.copy_from(
    campaign_operation.campaign_operation.update_mask,
    protobuf_helpers.field_mask(None, campaign._pb),
)

# Send all mutate operations in a single Mutate request.
mutate_operations = [
    experiment_operation,
    control_arm_operation,
    treatment_arm_operation,
    campaign_operation,
]

response = googleads_service.mutate(
    customer_id=customer_id,
    mutate_operations=mutate_operations,
)
      

Ruby

# Create the experiment resource name using a temporary ID.
experiment_resource_name = client.path.experiment(customer_id, "-1")

# Create the experiment.
experiment_operation = client.operation.mutate do |m|
  m.experiment_operation = client.operation.create_resource.experiment do |e|
    e.resource_name = experiment_resource_name
    e.name = "ADOPT_AI_MAX Experiment #{(Time.new.to_f * 1000).to_i}"
    e.type = :ADOPT_AI_MAX
  end
end

# Create the control arm. Both arms in an intra-campaign experiment
# reference the same base campaign.
campaign_resource_name = client.path.campaign(customer_id, campaign_id)
control_arm_operation = client.operation.mutate do |m|
  m.experiment_arm_operation = client.operation.create_resource.experiment_arm do |arm|
    arm.experiment = experiment_resource_name
    arm.name = "Control Arm"
    arm.control = true
    arm.traffic_split = 50
    arm.campaigns << campaign_resource_name
  end
end

# Create the treatment arm.
treatment_arm_operation = client.operation.mutate do |m|
  m.experiment_arm_operation = client.operation.create_resource.experiment_arm do |arm|
    arm.experiment = experiment_resource_name
    arm.name = "Treatment Arm"
    arm.control = false
    arm.traffic_split = 50
    arm.campaigns << campaign_resource_name
  end
end

# Create a campaign operation with an update mask to enable AI Max and
# configure asset automation settings.
# Note: For intra-campaign experiments, these settings are applied to the
# base campaign but are only active for the treatment traffic split.
campaign_operation = client.operation.mutate do |m|
  m.campaign_operation = client.operation.update_resource.campaign(campaign_resource_name) do |c|
    c.ai_max_setting = client.resource.ai_max_setting do |aims|
      aims.enable_ai_max = true
    end

    [:TEXT_ASSET_AUTOMATION, :FINAL_URL_EXPANSION_TEXT_ASSET_AUTOMATION].each do |type|
      c.asset_automation_settings << client.resource.asset_automation_setting do |setting|
        setting.asset_automation_type = type
        setting.asset_automation_status = :OPTED_IN
      end
    end
  end
end

# Send all mutate operations in a single Mutate request.
mutate_operations = [
  experiment_operation,
  control_arm_operation,
  treatment_arm_operation,
  campaign_operation,
]

response = client.service.google_ads.mutate(
  customer_id: customer_id,
  mutate_operations: mutate_operations,
)
      

Perl

This example is not yet available in Perl; you can take a look at the other languages.
    

curl

Melaporkan eksperimen

Karena traffic kontrol dan perlakuan digabungkan dalam satu kampanye, Anda harus menggunakan pelaporan eksperimen langsung untuk membandingkan metrik antara grup kontrol dan grup perlakuan. Pelaporan tingkat kampanye standar hanya menampilkan metrik gabungan untuk seluruh kampanye dan tidak dapat membedakan kedua grup tersebut.

Kueri GAQL berikut mengambil statistik klik untuk ADOPT_AI_MAX eksperimen intra-kampanye selama 30 hari terakhir:

SELECT
  experiment.resource_name,
  experiment.name,
  metrics.clicks,
  metrics.control_clicks,
  metrics.clicks_point_estimate,
  metrics.clicks_p_value
FROM experiment
WHERE segments.date DURING LAST_30_DAYS
  AND experiment.type = 'ADOPT_AI_MAX'

Mempromosikan, meluluskan, atau mengakhiri eksperimen

Setelah mengevaluasi hasilnya, Anda dapat menyelesaikan eksperimen menggunakan ExperimentService:

  • Akhiri: Jika Anda tidak puas dengan hasilnya, gunakan EndExperiment. Fitur ini dinonaktifkan, dan kampanye kembali menayangkan semua traffic tanpa fitur eksperimental. Metode ini adalah operasi sinkron.
  • Promosikan (ADOPT_AI_MAX dan ADOPT_BROAD_MATCH_KEYWORDS): Jika Anda puas dengan hasil eksperimen intra-kampanye Penelusuran, gunakan PromoteExperiment. Tindakan ini akan menerapkan perubahan eksperimental sebagai status permanen baru kampanye. Metode ini adalah operasi asinkron; lihat Error asinkron untuk mengetahui detailnya.
  • Graduate (PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION): PromoteExperiment tidak didukung untuk PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION; sebagai gantinya, gunakan GraduateExperiment untuk menerapkan setelan penyesuaian teks dan perluasan URL final grup perlakuan secara langsung ke kampanye Performa Maksimal yang ada. Sertakan entri CampaignBudgetMapping di campaign_budget_mappings yang menentukan kampanye grup perlakuan (experiment_campaign) dan anggarannya (campaign_budget). Ini adalah operasi sinkron. (GraduateExperiment tidak didukung untuk ADOPT_AI_MAX atau ADOPT_BROAD_MATCH_KEYWORDS karena tidak ada kampanye perlakuan terpisah yang akan diluluskan.)