Eksperymenty w ramach kampanii służą do testowania konkretnej funkcji w ramach jednej kampanii. W przeciwieństwie do eksperymentów zarządzanych przez system, w których ruch jest dzielony między kampanie kontrolne i eksperymentalne, eksperymenty w ramach kampanii dzielą ruch wewnątrz kampanii w zależności od tego, czy funkcja jest włączona.
Ten proces jest obsługiwany w przypadku tych wartości ExperimentType:
ADOPT_AI_MAX- Testuje wpływ funkcji AI Max na kampanie w sieci wyszukiwania.
ADOPT_BROAD_MATCH_KEYWORDS- Testowanie wpływu słów kluczowych w dopasowaniu przybliżonym na kampanie w sieci wyszukiwania.
PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION- Służy on do testowania funkcji kampanii Performance Max: dostosowywania tekstu i rozwinięcia końcowego adresu URL. Umożliwia sztucznej inteligencji Google kierowanie ruchu na trafne strony docelowe i generowanie komponentów tekstowych lepiej dopasowanych do wyszukiwanych haseł.
Konfiguracja
- Zdefiniuj
Experiment(z parametremstatusustawionym naENABLED), podając typ eksperymentu, grupę kontrolnąExperimentArmi grupę eksperymentalnąExperimentArm:- W przypadku
ADOPT_AI_MAXiADOPT_BROAD_MATCH_KEYWORDSzarówno grupa kontrolna, jak i eksperymentalna muszą odwoływać się do tej samej kampanii wcampaigns. - W przypadku
PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSIONtylko grupa eksperymentalna określa kampanię Performance Max wcampaigns(pozostawcampaignsnieustawione w grupie kontrolnej).
- W przypadku
W przypadku
ADOPT_AI_MAXutwórz aktualizacjęCampaignOperationz maską pola, aby włączyćai_max_setting.enable_ai_maxi skonfigurowaćasset_automation_settings.Wyślij żądanie
GoogleAdsService.Mutate, które zawiera operacje mutate służące do utworzenia eksperymentu i grup eksperymentalnych oraz (w przypadkuADOPT_AI_MAX) do włączenia funkcji testowej w kampanii.
W przypadku ADOPT_AI_MAX i ADOPT_BROAD_MATCH_KEYWORDS ruch musi być podzielony równomiernie (50/50) w ramach kampanii, tak aby 50% ruchu było kierowane do włączonej funkcji (grupa eksperymentalna), a 50% – nie (grupa kontrolna).
PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION obsługuje niestandardowe podziały ruchu,
które sumują się do 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
Raport z eksperymentu
Ruch kontrolny i eksperymentalny są mieszane w ramach jednej kampanii, dlatego musisz używać raportów z eksperymentów bezpośrednich, aby porównywać dane między grupą kontrolną a grupą eksperymentalną. Standardowe raportowanie na poziomie kampanii pokazuje tylko zagregowane dane dla całej kampanii i nie pozwala rozróżnić tych 2 grup.
To zapytanie GAQL pobiera statystyki kliknięć dotyczące ADOPT_AI_MAX
eksperymentu w kampanii z ostatnich 30 dni:
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'
Przekształcanie eksperymentu w kampanię, kończenie eksperymentu lub stosowanie jego ustawień
Po ocenie wyników możesz zakończyć eksperyment za pomocą ExperimentService:
- Zakończenie: jeśli nie jesteś zadowolony(-a) z wyników, użyj
EndExperiment. Funkcja zostanie wyłączona, a kampania powróci do wyświetlania reklam w całym ruchu bez funkcji eksperymentalnej. Jest to operacja synchroniczna. - Promuj (
ADOPT_AI_MAXiADOPT_BROAD_MATCH_KEYWORDS): jeśli wyniki eksperymentu w ramach kampanii w sieci wyszukiwania są zadowalające, użyj metodyPromoteExperiment. Spowoduje to zastosowanie zmiany eksperymentalnej jako nowego stałego stanu kampanii. Jest to operacja asynchroniczna. Szczegółowe informacje znajdziesz w sekcji Błędy asynchroniczne. - Przekształć (
PMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION):PromoteExperimentnie jest obsługiwany w przypadkuPMAX_TEXT_CUSTOMIZATION_FINAL_URL_EXPANSION. Zamiast tego użyjGraduateExperiment, aby zastosować ustawienia dostosowywania tekstu i rozwinięcia końcowego adresu URL z kampanii eksperymentalnej w dotychczasowej kampanii Performance Max. Dodaj wpisCampaignBudgetMappingwcampaign_budget_mappings, podając kampanię z grupy eksperymentalnej (experiment_campaign) i jej budżet (campaign_budget). Jest to operacja synchroniczna. (GraduateExperimentnie jest obsługiwany w przypadkuADOPT_AI_MAXaniADOPT_BROAD_MATCH_KEYWORDS, ponieważ nie ma oddzielnej kampanii eksperymentalnej, którą można by przekształcić).