Recomendaciones

Video: Análisis detallado

Las recomendaciones pueden mejorar tus campañas de las siguientes maneras:

  • Presenta funciones nuevas y relevantes
  • Aproveche mejor su presupuesto con ofertas, palabras clave y anuncios mejorados
  • Aumentar el rendimiento y la eficacia de sus campañas en general

Para aumentar los niveles de optimización, puedes usar RecommendationService a fin de recuperar recomendaciones y, luego, aplicarlas o descartarlas según corresponda.

Nivel de optimización

Video: Análisis detallado

El nivel de optimización es una estimación de qué tan bien está configurada su cuenta de Google Ads para lograr el rendimiento esperado y está disponible en los niveles Customer y Campaign.

La Customer.optimization_score_weight solo está disponible para cuentas que no son de administrador y se usa a fin de calcular el nivel de optimización general de varias cuentas. Recupera el nivel de optimización y el peso del nivel de optimización de las cuentas y multiplícalos (Customer.optimization_score * Customer.optimization_score_weight) para calcular el nivel de optimización general.

Hay métricas relacionadas con la optimización disponibles para los informes customer y campaign:

  1. El metrics.optimization_score_url proporciona un vínculo directo a la cuenta para ver información sobre las recomendaciones relacionadas en la IU de Google Ads.
  2. El metrics.optimization_score_uplift indica cuánto aumentaría el nivel de optimización si se aplicaran todas las recomendaciones relacionadas.

optimization_score_uplift es solo una aproximación. Esto se debe a que el aumento de optimización se calcula de forma individual para cada recomendación, y el efecto combinado de implementar varias recomendaciones puede no ser una suma estricta de cada una por separado.

Tipos de recomendación

Video: Cómo controlar tipos no compatibles

La API de Google Ads es totalmente compatible con los siguientes tipos de recomendación:

RecommendationType Descripción
CAMPAIGN_BUDGET Corrija las campañas limitadas por el presupuesto
KEYWORD Agregue palabras clave nuevas
TEXT_AD Agregue sugerencias de anuncios
TARGET_CPA_OPT_IN Realice ofertas con el CPA objetivo
MAXIMIZE_CONVERSIONS_OPT_IN Realice ofertas con Maximizar conversiones
ENHANCED_CPC_OPT_IN Realice ofertas con el CPC avanzado.
SEARCH_PARTNERS_OPT_IN Expanda el alcance con los socios de búsqueda de Google
MAXIMIZE_CLICKS_OPT_IN Realice ofertas con Maximizar clics
OPTIMIZE_AD_ROTATION Utilice rotaciones de anuncios optimizadas
CALLOUT_EXTENSION Agregar extensiones de texto destacado a la campaña
SITELINK_EXTENSION Agregar extensiones de vínculos a sitios a la campaña
CALL_EXTENSION Agregar extensiones de llamada a la campaña
KEYWORD_MATCH_TYPE (deprecated) Cómo cambiar los tipos de concordancia de palabras clave
MOVE_UNUSED_BUDGET Transfiera los elementos no utilizados a presupuestos limitados
TARGET_ROAS_OPT_IN Realice ofertas con el ROAS objetivo
FORECASTING_CAMPAIGN_BUDGET Corrija las campañas que podrían estar limitadas por el presupuesto en el futuro
RESPONSIVE_SEARCH_AD Agregar nuevo anuncio de búsqueda responsivo
MARGINAL_ROI_CAMPAIGN_BUDGET Ajuste el presupuesto de la campaña para aumentar el ROI
USE_BROAD_MATCH_KEYWORD Utilice la concordancia amplia para las campañas basadas en conversiones con las ofertas automáticas.
RESPONSIVE_SEARCH_AD_ASSET Agregue elementos de anuncios de búsqueda responsivos a un anuncio
UPGRADE_SMART_SHOPPING_CAMPAIGN_TO_PERFORMANCE_MAX Cómo actualizar una campaña de Shopping inteligente a una campaña de máximo rendimiento
RESPONSIVE_SEARCH_AD_IMPROVE_AD_STRENGTH Mejore la calidad de los anuncios de búsqueda responsivos

Recuperar recomendaciones

Video: Codificación en vivo

Al igual que la mayoría de las otras entidades de la API de Google Ads, los objetos Recommendation se recuperan mediante GoogleAdsService.SearchStream con una consulta del lenguaje de consultas de Google Ads.

Para cada tipo de recomendación, los detalles de la recomendación se proporcionan en un campo recommendation específico con un tipo específico:

RecommendationType recommendation Tipo
CAMPAIGN_BUDGET campaign_budget_recommendation CampaignBudgetRecommendation
KEYWORD keyword_recommendation KeywordRecommendation
TEXT_AD text_ad_recommendation TextAdRecommendation
TARGET_CPA_OPT_IN target_cpa_opt_in_recommendation TargetCpaOptInRecommendation
MAXIMIZE_CONVERSIONS_OPT_IN maximize_conversions_opt_in_recommendation MaximizeConversionsOptInRecommendation
ENHANCED_CPC_OPT_IN enhanced_cpc_opt_in_recommendation EnhancedCpcOptInRecommendation
SEARCH_PARTNERS_OPT_IN search_partners_opt_in_recommendation SearchPartnersOptInRecommendation
MAXIMIZE_CLICKS_OPT_IN maximize_clicks_opt_in_recommendation MaximizeClicksOptInRecommendation
OPTIMIZE_AD_ROTATION optimize_ad_rotation_recommendation OptimizeAdRotationRecommendation
CALLOUT_EXTENSION callout_extension_recommendation CalloutExtensionRecommendation
SITELINK_EXTENSION sitelink_extension_recommendation SitelinkExtensionRecommendation
CALL_EXTENSION call_extension_recommendation CallExtensionRecommendation
KEYWORD_MATCH_TYPE (obsoleta) keyword_match_type_recommendation KeywordMatchTypeRecommendation
MOVE_UNUSED_BUDGET move_unused_budget_recommendation MoveUnusedBudgetRecommendation
TARGET_ROAS_OPT_IN target_roas_opt_in_recommendation TargetRoasOptInRecommendation
FORECASTING_CAMPAIGN_BUDGET forecasting_campaign_budget_recommendation CampaignBudgetRecommendation
RESPONSIVE_SEARCH_AD responsive_search_ad_recommendation ResponsiveSearchAdRecommendation
MARGINAL_ROI_CAMPAIGN_BUDGET marginal_roi_campaign_budget_recommendation CampaignBudgetRecommendation
USE_BROAD_MATCH_KEYWORD use_broad_match_keyword_recommendation UseBroadMatchKeywordRecommendation
RESPONSIVE_SEARCH_AD_ASSET responsive_search_ad_asset_recommendation ResponsiveSearchAdAssetRecommendation

El siguiente código de muestra recupera todas las recomendaciones disponibles y descartadas del tipo TEXT_AD de una cuenta y, también, imprime algunos de sus detalles:

Java

private void runExample(GoogleAdsClient googleAdsClient, long customerId) {
  try (GoogleAdsServiceClient googleAdsServiceClient =
      googleAdsClient.getLatestVersion().createGoogleAdsServiceClient()) {
    String query =
        "SELECT recommendation.type, "
            + "recommendation.campaign, "
            + "recommendation.text_ad_recommendation "
            + "FROM recommendation "
            + "WHERE recommendation.type = TEXT_AD";

    // Creates a request that will retrieve all recommendations using pages of the
    // specified page size.
    SearchGoogleAdsRequest request =
        SearchGoogleAdsRequest.newBuilder()
            .setCustomerId(Long.toString(customerId))
            .setPageSize(PAGE_SIZE)
            .setQuery(query)
            .build();
    // Issues the search request.
    SearchPagedResponse searchPagedResponse = googleAdsServiceClient.search(request);

    // Iterates over all rows in all pages and prints the requested field values for the
    // recommendation in each row.
    for (GoogleAdsRow googleAdsRow : searchPagedResponse.iterateAll()) {
      Recommendation recommendation = googleAdsRow.getRecommendation();
      Ad recommendedAd = recommendation.getTextAdRecommendation().getAd();

      System.out.printf(
          "Recommendation ('%s') was found for campaign '%s':%n",
          recommendation.getResourceName(), recommendation.getCampaign());
      if (recommendedAd.hasExpandedTextAd()) {
        ExpandedTextAdInfo eta = recommendedAd.getExpandedTextAd();
        System.out.printf(
            "\tHeadline 1 = '%s'%n" + "\tHeadline 2 = '%s'%n" + "\tDescription = '%s'%n",
            eta.getHeadlinePart1(), eta.getHeadlinePart2(), eta.getDescription());
      }
      if (recommendedAd.getDisplayUrl() != null) {
        System.out.printf("\tDisplay URL = '%s'%n", recommendedAd.getDisplayUrl());
      }
      for (String url : recommendedAd.getFinalUrlsList()) {
        System.out.printf("\tFinal URL = '%s'%n", url);
      }
      for (String url : recommendedAd.getFinalMobileUrlsList()) {
        System.out.printf("\tFinal Mobile URL = '%s'%n", url);
      }
    }
  }
}
      

C#

public void Run(GoogleAdsClient client, long customerId)
{
    // Get the GoogleAdsServiceClient .
    GoogleAdsServiceClient service = client.GetService(Services.V11.GoogleAdsService);

    string query =
        @"SELECT
        recommendation.type,
        recommendation.campaign,
        recommendation.text_ad_recommendation
    FROM
        recommendation
    WHERE
        recommendation.type = TEXT_AD";

    // Create a request that will retrieve all recommendations using pages of the
    // specified page size.
    SearchGoogleAdsRequest request = new SearchGoogleAdsRequest()
    {
        CustomerId = customerId.ToString(),
        PageSize = PAGE_SIZE,
        Query = query
    };

    try
    {
        // Issue the search request.
        PagedEnumerable<SearchGoogleAdsResponse, GoogleAdsRow> searchPagedResponse =
            service.Search(customerId.ToString(), query);

        // Iterates over all rows in all pages and prints the requested field values
        // for the recommendation in each row.
        foreach (GoogleAdsRow googleAdsRow in searchPagedResponse)
        {
            Recommendation recommendation = googleAdsRow.Recommendation;
            // ...
        }
    }
    catch (GoogleAdsException e)
    {
        Console.WriteLine("Failure:");
        Console.WriteLine($"Message: {e.Message}");
        Console.WriteLine($"Failure: {e.Failure}");
        Console.WriteLine($"Request ID: {e.RequestId}");
        throw;
    }
}
      

PHP

public static function runExample(GoogleAdsClient $googleAdsClient, int $customerId)
{
    $googleAdsServiceClient = $googleAdsClient->getGoogleAdsServiceClient();
    // Creates a query that retrieves recommendations for text ads.
    $query = 'SELECT recommendation.type, recommendation.campaign, '
        . 'recommendation.text_ad_recommendation '
        . 'FROM recommendation '
        . 'WHERE recommendation.type = TEXT_AD';

    // Issues a search request by specifying page size.
    $response =
        $googleAdsServiceClient->search($customerId, $query, ['pageSize' => self::PAGE_SIZE]);

    // Iterates over all rows in all pages and prints the requested field values for
    // the recommendation in each row.
    foreach ($response->iterateAllElements() as $googleAdsRow) {
        /** @var GoogleAdsRow $googleAdsRow */
        $recommendation = $googleAdsRow->getRecommendation();
        printf(
            "Recommendation with resource name '%s' was found for campaign "
            . "with resource name '%s':%s",
            $recommendation->getResourceName(),
            $recommendation->getCampaign(),
            PHP_EOL
        );
        $recommendedAd = $recommendation->getTextAdRecommendation()->getAd();
        if (!is_null($recommendedAd->getExpandedTextAd())) {
            $recommendedExpandedTextAd = $recommendedAd->getExpandedTextAd();
            printf(
                "\tHeadline part 1 is '%s'.%s",
                $recommendedExpandedTextAd->getHeadlinePart1(),
                PHP_EOL
            );
            printf(
                "\tHeadline part 2 is '%s'.%s",
                $recommendedExpandedTextAd->getHeadlinePart2(),
                PHP_EOL
            );
            printf(
                "\tDescription is '%s'%s",
                $recommendedExpandedTextAd->getDescription(),
                PHP_EOL
            );
        }
        if (!is_null($recommendedAd->getDisplayUrl())) {
            printf("\tDisplay URL is '%s'.%s", $recommendedAd->getDisplayUrl(), PHP_EOL);
        }
        foreach ($recommendedAd->getFinalUrls() as $finalUrl) {
            /** @var string $finalUrl */
            printf("\tFinal URL is '%s'.%s", $finalUrl, PHP_EOL);
        }
        foreach ($recommendedAd->getFinalMobileUrls() as $finalMobileUrl) {
            /** @var string $finalMobileUrl */
            printf("\tFinal Mobile URL is '%s'.%s", $finalMobileUrl, PHP_EOL);
        }
    }
}
      

Python

def main(client, customer_id):
    ga_service = client.get_service("GoogleAdsService")

    query = """
        SELECT
          recommendation.type,
          recommendation.campaign,
          recommendation.text_ad_recommendation
        FROM recommendation
        WHERE recommendation.type = TEXT_AD"""

    search_request = client.get_type("SearchGoogleAdsStreamRequest")
    search_request.customer_id = customer_id
    search_request.query = query
    stream = ga_service.search_stream(request=search_request)

    for batch in stream:
        for row in batch.results:
            recommendation = row.recommendation
            recommended_ad = recommendation.text_ad_recommendation.ad
            print(
                f'Recommendation ("{recommendation.resource_name}") '
                f'was found for campaign "{recommendation.campaign}".'
            )

            if recommended_ad.display_url:
                print(f'\tDisplay URL = "{recommended_ad.display_url}"')

            for url in recommended_ad.final_urls:
                print(f'\tFinal URL = "{url}"')

            for url in recommended_ad.final_mobile_urls:
                print(f'\tFinal Mobile URL = "{url}"')
      

Ruby

def get_text_ad_recommendations(customer_id)
  # GoogleAdsClient will read a config file from
  # ENV['HOME']/google_ads_config.rb when called without parameters
  client = Google::Ads::GoogleAds::GoogleAdsClient.new

  ga_service = client.service.google_ads

  query = <<~QUERY
    SELECT recommendation.type, recommendation.campaign,
        recommendation.text_ad_recommendation
    FROM recommendation
    WHERE recommendation.type = TEXT_AD
  QUERY

  response = ga_service.search(
    customer_id: customer_id,
    query: query,
    page_size: PAGE_SIZE,
  )

  response.each do |row|
    recommendation = row.recommendation
    recommended_ad = recommendation.text_ad_recommendation.ad

    puts "Recommendation ('#{recommendation.resource_name}') was found for "\
        "campaign '#{recommendation.campaign}'."
    if recommended_ad.expanded_text_ad
      eta = recommended_ad.expanded_text_ad
      puts "\tHeadline 1 = '#{eta.headline_part1}'\n\tHeadline2 = '#{eta.headline_part2}'\n" +
          "\tDescription = '#{eta.description}'"
    end
    if recommended_ad.display_url
      puts "\tDisplay URL = '#{recommended_ad.display_url}'"
    end
    recommended_ad.final_urls.each do |url|
      puts "\tFinal Url = '#{url}'"
    end
    recommended_ad.final_mobile_urls.each do |url|
      puts "\tFinal Mobile Url = '#{url}'"
    end
  end
end
      

Perl

sub get_text_ad_recommendations {
  my ($api_client, $customer_id) = @_;

  # Creates the search query.
  my $search_query =
    "SELECT recommendation.type, recommendation.campaign, " .
    "recommendation.text_ad_recommendation " .
    "FROM recommendation WHERE recommendation.type = TEXT_AD";

  # Create a search Google Ads request that will retrieve all recommendations for
  # text ads using pages of the specified page size.
  my $search_request =
    Google::Ads::GoogleAds::V11::Services::GoogleAdsService::SearchGoogleAdsRequest
    ->new({
      customerId => $customer_id,
      query      => $search_query,
      pageSize   => PAGE_SIZE
    });

  # Get the GoogleAdsService.
  my $google_ads_service = $api_client->GoogleAdsService();

  my $iterator = Google::Ads::GoogleAds::Utils::SearchGoogleAdsIterator->new({
    service => $google_ads_service,
    request => $search_request
  });

  # Iterate over all rows in all pages and print the requested field values for
  # the recommendation in each row.
  while ($iterator->has_next) {
    my $google_ads_row = $iterator->next;
    my $recommendation = $google_ads_row->{recommendation};
    printf
      "Recommendation '%s' was found for campaign '%s':\n",
      $recommendation->{resourceName},
      $recommendation->{campaign};

    my $recommended_ad = $recommendation->{textAdRecommendation}{ad};
    if ($recommended_ad->{expandedTextAd}) {
      my $recommended_expanded_text_ad = $recommended_ad->{expandedTextAd};

      printf "\tHeadline part 1 is '%s'.\n" .
        "\tHeadline part 2 is '%s'.\n" . "\tDescription is '%s'.\n",
        $recommended_expanded_text_ad->{headlinePart1},
        $recommended_expanded_text_ad->{headlinePart2},
        $recommended_expanded_text_ad->{description};
    }

    if ($recommended_ad->{displayUrl}) {
      printf "\tDisplay URL is '%s'.\n", $recommended_ad->{displayUrl};
    }

    foreach my $final_url (@{$recommended_ad->{finalUrls}}) {
      printf "\tFinal URL is '%s'.\n", $final_url;
    }

    foreach my $final_mobile_url (@{$recommended_ad->{finalMobileUrls}}) {
      printf "\tFinal Mobile URL is '%s'.\n", $final_mobile_url;
    }
  }

  return 1;
}
      

Toma medidas

Se puede aplicar o descartar cualquier recomendación recuperada.

Según el tipo de recomendación, estas pueden cambiar diariamente o varias veces al día. Cuando eso sucede, el resource_name de un objeto de recomendación puede quedar obsoleto después de que se recupera la recomendación.

Te recomendamos que tomes medidas con respecto a las recomendaciones poco después de la recuperación.

Cómo aplicar recomendaciones

Video: Análisis detallado

La configuración de las cuentas para la aplicación automática de recomendaciones no es compatible con la API de Google Ads. Sin embargo, puedes implementar un comportamiento similar para los tipos de recomendaciones que son totalmente compatibles con la API de Google Ads. Consulta el ejemplo de código DetectAndApplyRecommendations para obtener más información.

Puedes aplicar recomendaciones activas o descartadas con el método ApplyRecommendation de RecommendationService.

Los tipos de recomendaciones pueden tener parámetros obligatorios u opcionales. La mayoría de las recomendaciones incluyen valores recomendados que se usan de forma predeterminada; consulta los detalles de las recomendaciones.

Usa el campo apply_parameters de ApplyRecommendationOperation para aplicar recomendaciones con valores de parámetros específicos. Cada tipo de recomendación adecuado tiene su propio campo:

RecommendationType apply_parameters Tipo
CAMPAIGN_BUDGET campaign_budget CampaignBudgetParameters
KEYWORD keyword KeywordParameters
TEXT_AD text_ad TextAdParameters
TARGET_CPA_OPT_IN target_cpa_opt_in TargetCpaOptInParameters
MAXIMIZE_CONVERSIONS_OPT_IN - -
ENHANCED_CPC_OPT_IN - -
SEARCH_PARTNERS_OPT_IN - -
MAXIMIZE_CLICKS_OPT_IN - -
OPTIMIZE_AD_ROTATION - -
CALLOUT_EXTENSION callout_extension CalloutExtensionParameters
SITELINK_EXTENSION sitelink_extension SitelinkExtensionParameters
CALL_EXTENSION call_extension CallExtensionParameters
KEYWORD_MATCH_TYPE (obsoleta) - -
MOVE_UNUSED_BUDGET move_unused_budget MoveUnusedBudgetParameters
TARGET_ROAS_OPT_IN target_roas_opt_in TargetRoasOptInParameters
FORECASTING_CAMPAIGN_BUDGET campaign_budget CampaignBudgetParameters
RESPONSIVE_SEARCH_AD responsive_search_ad ResponsiveSearchAdParameters
MARGINAL_ROI_CAMPAIGN_BUDGET campaign_budget CampaignBudgetParameters
USE_BROAD_MATCH_KEYWORD use_broad_match_keyword UseBroadMatchKeywordRecommendation
RESPONSIVE_SEARCH_AD_ASSET responsive_search_ad_asset ResponsiveSearchAdAssetParameters

En el siguiente ejemplo de código, se ilustra cómo aplicar una recomendación con los parámetros de aplicación recomendados:

Java

private void runExample(
    GoogleAdsClient googleAdsClient, long customerId, String recommendationId) {
  String recommendationResourceName = ResourceNames.recommendation(customerId, recommendationId);

  ApplyRecommendationOperation.Builder operationBuilder =
      ApplyRecommendationOperation.newBuilder().setResourceName(recommendationResourceName);
  // Each recommendation types has optional parameters to override the recommended values.
  // This is an example to override a recommended ad when a TextAdRecommendation is applied.
  // Please read
  // https://developers.google.com/google-ads/api/reference/rpc/latest/ApplyRecommendationOperation
  // for details.
  // Note that additional import statements are needed for this example to work. And also, please
  // replace INSERT_AD_ID_HERE with a valid ad ID below.
  //
  // Ad overrideAd = Ad.newBuilder().setId(Long.parseLong("INSERT_AD_ID_HERE")).build();
  // operationBuilder.setTextAd(TextAdParameters.newBuilder().
  //     setAd(overrideAd).build()).build();
  List<ApplyRecommendationOperation> operations = new ArrayList<>();
  operations.add(operationBuilder.build());

  try (RecommendationServiceClient recommendationServiceClient =
      googleAdsClient.getLatestVersion().createRecommendationServiceClient()) {
    ApplyRecommendationResponse response =
        recommendationServiceClient.applyRecommendation(Long.toString(customerId), operations);
    System.out.printf("Applied %d recommendation:%n", response.getResultsCount());
    for (ApplyRecommendationResult result : response.getResultsList()) {
      System.out.println(result.getResourceName());
    }
  }
}
      

C#

public void Run(GoogleAdsClient client, long customerId, long recommendationId)
{
    // Get the RecommendationServiceClient.
    RecommendationServiceClient service = client.GetService(
        Services.V11.RecommendationService);

    ApplyRecommendationOperation operation = new ApplyRecommendationOperation()
    {
        ResourceName = ResourceNames.Recommendation(customerId, recommendationId),

        // Each recommendation types has optional parameters to override the recommended
        // values. For example, you can override a recommended ad when a
        // TextAdRecommendation is applied, as shown below.
        // Please read https://developers.google.com/google-ads/api/reference/rpc/latest/ApplyRecommendationOperation
        // for details.
        // TextAd = new TextAdParameters() {
        //   Ad = new Ad() {
        //     Id = long.Parse("INSERT_AD_ID_HERE")
        //   }
        // }
    };

    try
    {
        ApplyRecommendationResponse response = service.ApplyRecommendation(
            customerId.ToString(), new ApplyRecommendationOperation[] {
                operation
            });
        Console.WriteLine($"Applied {0} recommendation(s):", response.Results.Count);
        foreach (ApplyRecommendationResult result in response.Results)
        {
            Console.WriteLine($"- {result.ResourceName}");
        }
    }
    catch (GoogleAdsException e)
    {
        Console.WriteLine("Failure:");
        Console.WriteLine($"Message: {e.Message}");
        Console.WriteLine($"Failure: {e.Failure}");
        Console.WriteLine($"Request ID: {e.RequestId}");
        throw;
    }
}
      

PHP

public static function runExample(
    GoogleAdsClient $googleAdsClient,
    int $customerId,
    string $recommendationId
) {
    $recommendationResourceName =
        ResourceNames::forRecommendation($customerId, $recommendationId);

    $applyRecommendationOperation = new ApplyRecommendationOperation();
    $applyRecommendationOperation->setResourceName($recommendationResourceName);

    // Each recommendation type has optional parameters to override the recommended values.
    // This is an example to override a recommended ad when a TextAdRecommendation is applied.
    // For details, please read
    // https://developers.google.com/google-ads/api/reference/rpc/latest/ApplyRecommendationOperation.
    /*
    $overridingAd = new Ad([
        'id' => 'INSERT_AD_ID_AS_INTEGER_HERE'
    ]);
    $applyRecommendationOperation->setTextAd(new TextAdParameters(['ad' => $overridingAd]));
    */
    // Issues a mutate request to apply the recommendation.
    $recommendationServiceClient = $googleAdsClient->getRecommendationServiceClient();
    $response = $recommendationServiceClient->applyRecommendation(
        $customerId,
        [$applyRecommendationOperation]
    );
    /** @var Recommendation $appliedRecommendation */
    $appliedRecommendation = $response->getResults()[0];

    printf(
        "Applied recommendation with resource name: '%s'.%s",
        $appliedRecommendation->getResourceName(),
        PHP_EOL
    );
}
      

Python

def main(client, customer_id, recommendation_id):
    recommendation_service = client.get_service("RecommendationService")

    apply_recommendation_operation = client.get_type(
        "ApplyRecommendationOperation"
    )

    apply_recommendation_operation.resource_name = (
        recommendation_service.recommendation_path(
            customer_id, recommendation_id
        )
    )

    # This is where we override the recommended ad when a TextAdRecommendation is applied.
    # override_ad = client.get_type("Ad")
    # override_ad.resource_name = "INSERT_AD_ID_HERE"
    # apply_recommendation_operation.text_ad.ad = override_ad

    recommendation_response = recommendation_service.apply_recommendation(
        customer_id=customer_id, operations=[apply_recommendation_operation]
    )

    print(
        "Applied recommendation with resource name: "
        f"'{recommendation_response.results[0].resource_name}'"
    )
      

Ruby

def apply_recommendation(customer_id, recommendation_id)
  # GoogleAdsClient will read a config file from
  # ENV['HOME']/google_ads_config.rb when called without parameters
  client = Google::Ads::GoogleAds::GoogleAdsClient.new

  recommendation_resource =
      client.path.recommendation(customer_id, recommendation_id)
  apply_recommendation_operation = client.operation.apply_recommendation
  apply_recommendation_operation.resource_name = recommendation_resource

  # Each recommendation type has optional parameters to override the recommended
  # values. This is an example to override a recommended ad when a
  # TextAdRecommendation is applied.
  # For details, please read
  # https://developers.google.com/google-ads/api/reference/rpc/google.ads.google_ads.v1.services#google.ads.google_ads.v1.services.ApplyRecommendationOperation
  #
  # text_ad_parameters = client.resource.text_ad_parameters do |tap|
  #   tap.ad = client.resource.ad do |ad|
  #     ad.id = "INSERT_AD_ID_AS_INTEGER_HERE"
  #   end
  # end
  # apply_recommendation_operation.text_ad = text_ad_parameters

  # Issues a mutate request to apply the recommendation.
  recommendation_service = client.service.recommendation
  response = recommendation_service.apply_recommendation(
    customer_id: customer_id,
    operations: [apply_recommendation_operation],
  )
  applied_recommendation = response.results.first

  puts "Applied recommendation with resource name: '#{applied_recommendation.resource_name}'."
end
      

Perl

sub apply_recommendation {
  my ($api_client, $customer_id, $recommendation_id) = @_;

  my $recommendation_resource_name =
    Google::Ads::GoogleAds::V11::Utils::ResourceNames::recommendation(
    $customer_id, $recommendation_id);

  # Create an apply recommendation operation.
  my $apply_recommendation_operation =
    Google::Ads::GoogleAds::V11::Services::RecommendationService::ApplyRecommendationOperation
    ->new({
      resourceName => $recommendation_resource_name
    });

  # Each recommendation type has optional parameters to override the recommended values.
  # This is an example to override a recommended ad when a TextAdRecommendation is applied.
  # For details, please read
  # https://developers.google.com/google-ads/api/reference/rpc/latest/ApplyRecommendationOperation.
  #
  # my $overriding_ad = Google::Ads::GoogleAds::V11::Resources::Ad->new({
  #   id => "INSERT_AD_ID_AS_INTEGER_HERE"
  # });
  # my $text_ad_parameters =
  #   Google::Ads::GoogleAds::V11::Services::RecommendationService::TextAdParameters
  #   ->new({ad => $overriding_ad});
  # $apply_recommendation_operation->{textAd} = $text_ad_parameters;

  # Apply the recommendation.
  my $apply_recommendation_response =
    $api_client->RecommendationService()->apply({
      customerId => $customer_id,
      operations => [$apply_recommendation_operation]});

  printf "Applied recommendation with resource name: '%s'.\n",
    $apply_recommendation_response->{results}[0]{resourceName};

  return 1;
}
      

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Aplicar parámetros

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Descarta recomendaciones

Video: Análisis detallado

Puedes descartar recomendaciones con el RecommendationService. La estructura del código es similar a la de cómo aplicar recomendaciones, pero en su lugar usas DismissRecommendationOperation y RecommendationService.DismissRecommendation.

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A granel

Errores

Pruebas