优化得分和建议

视频：深入探究

建议可通过以下几种方式提升广告系列的效果：

  • 推出新的相关功能
  • 通过改进出价、关键字和广告，获得更高的投入回报
  • 提升广告系列的整体效果和效率

如需提高优化得分，您可以使用 RecommendationService 检索建议，然后相应地采纳或拒绝这些建议。您还可以使用 RecommendationSubscriptionService 订阅自动采纳建议。

优化得分

视频：优化得分

优化得分是一个估算的分值，反映了您的 Google Ads 账号在设置方面的优化程度，可在 Customer 和 Campaign 一级查看。

Customer.optimization_score_weight 仅适用于非经理账号，用于计算多个账号的整体优化得分。检索账号的优化得分和优化得分权重，然后将它们相乘 (Customer.optimization_score * Customer.optimization_score_weight) 以计算总体优化得分。

customer 和 campaign 报告提供与优化相关的指标：

  1. metrics.optimization_score_url 会提供指向相应账号的深层链接，以便您在 Google Ads 界面中查看相关建议的相关信息。
  2. metrics.optimization_score_uplift 表示采纳所有相关建议后优化得分会提高多少。这是一个基于所有可用建议的整体估算值，而不仅仅是每个建议的提升幅度得分的总和。

如需对返回的推荐进行分组和排序，您可以在查询中使用 segments.recommendation_type 按推荐类型对这两个指标进行细分。

推荐类型

完全受支持的建议类型

RecommendationType 说明
CAMPAIGN_BUDGET 修正受预算限制的广告系列
KEYWORD 添加新关键字
TEXT_AD 添加推荐广告
TARGET_CPA_OPT_IN 采用“目标每次转化费用”出价策略
MAXIMIZE_CONVERSIONS_OPT_IN 采用“尽可能提高转化次数”出价策略
MAXIMIZE_CONVERSION_VALUE_OPT_IN 采用“尽可能提高转化价值”出价策略
ENHANCED_CPC_OPT_IN 采用“智能点击付费”出价策略
MAXIMIZE_CLICKS_OPT_IN 采用“尽可能争取更多点击次数”出价策略
OPTIMIZE_AD_ROTATION 使用优化型广告轮播
MOVE_UNUSED_BUDGET 将未使用的预算转移到受限预算
TARGET_ROAS_OPT_IN 采用“目标广告支出回报率”出价策略
FORECASTING_CAMPAIGN_BUDGET 修正预计未来会受预算限制的广告系列
RESPONSIVE_SEARCH_AD 添加新的自适应搜索广告
MARGINAL_ROI_CAMPAIGN_BUDGET 调整广告系列预算以提高投资回报率
USE_BROAD_MATCH_KEYWORD 为采用自动出价的以促成转化为目标的广告系列使用广泛匹配
RESPONSIVE_SEARCH_AD_ASSET 向广告添加自适应搜索广告素材资源
RESPONSIVE_SEARCH_AD_IMPROVE_AD_STRENGTH 提升自适应搜索广告的广告效力
DISPLAY_EXPANSION_OPT_IN 更新广告系列以使用展示广告系列扩展功能
SEARCH_PARTNERS_OPT_IN 利用 Google 搜索网络合作伙伴扩大覆盖面
CUSTOM_AUDIENCE_OPT_IN 创建自定义受众群体
IMPROVE_DEMAND_GEN_AD_STRENGTH 提升需求开发广告系列中广告的效力
UPGRADE_SMART_SHOPPING_CAMPAIGN_TO_PERFORMANCE_MAX 将智能购物广告系列升级为效果最大化广告系列
UPGRADE_LOCAL_CAMPAIGN_TO_PERFORMANCE_MAX 将旧版本地广告系列升级为效果最大化广告系列
SHOPPING_MIGRATE_REGULAR_SHOPPING_CAMPAIGN_OFFERS_TO_PERFORMANCE_MAX 将常规购物广告系列宣传的产品迁移到现有的效果最大化广告系列
MIGRATE_DYNAMIC_SEARCH_ADS_CAMPAIGN_TO_PERFORMANCE_MAX 将动态搜索广告系列迁移到效果最大化广告系列
PERFORMANCE_MAX_OPT_IN 在您的账号中制作效果最大化广告系列
IMPROVE_PERFORMANCE_MAX_AD_STRENGTH 将效果最大化广告系列的素材资源组效力提升至“极佳”评分
PERFORMANCE_MAX_FINAL_URL_OPT_IN 为效果最大化广告系列启用“最终到达网址扩展”功能
RAISE_TARGET_CPA_BID_TOO_LOW 如果目标每次转化费用过低且转化次数很少或没有转化，请提高目标每次转化费用
FORECASTING_SET_TARGET_ROAS 在预计会增加流量的季节性活动之前提高预算，并将出价策略从“尽可能提高转化价值”更改为“目标广告支出回报率”
LEAD_FORM_ASSET 向广告系列添加潜在客户表单素材资源
CALLOUT_ASSET 在广告系列一级或客户一级添加宣传信息素材资源
SITELINK_ASSET 在广告系列一级或客户一级添加站内链接素材资源
CALL_ASSET 在广告系列一级或客户一级添加电话素材资源
SHOPPING_ADD_AGE_GROUP 为因缺少年龄段而被降级的商品添加年龄段属性
SHOPPING_ADD_COLOR 为因缺少颜色而被降级的商品添加颜色
SHOPPING_ADD_GENDER 为因缺少适用性别而被降级的商品添加适用性别
SHOPPING_ADD_GTIN 为因缺少 GTIN 而被降级的商品添加 GTIN（全球贸易项目代码）
SHOPPING_ADD_MORE_IDENTIFIERS 为因缺少标识码而被降级的商品添加更多标识码
SHOPPING_ADD_SIZE 为因缺少尺码而被降级的商品添加尺码
SHOPPING_ADD_PRODUCTS_TO_CAMPAIGN 为广告系列添加要投放的产品
SHOPPING_FIX_DISAPPROVED_PRODUCTS 解决商品被拒登的问题
SHOPPING_TARGET_ALL_OFFERS 制作一个定位所有商品的全包型广告系列
SHOPPING_FIX_SUSPENDED_MERCHANT_CENTER_ACCOUNT 解决 Merchant Center 账号中止问题
SHOPPING_FIX_MERCHANT_CENTER_ACCOUNT_SUSPENSION_WARNING 解决 Merchant Center 账号中止警告问题
DYNAMIC_IMAGE_EXTENSION_OPT_IN 在账号中启用动态图片附加信息
RAISE_TARGET_CPA 提高目标每次转化费用
LOWER_TARGET_ROAS 降低目标广告支出回报率
FORECASTING_SET_TARGET_CPA 在预计会带来更多流量的季节性活动之前，为未指定目标每次转化费用的广告系列设置目标每次转化费用
SET_TARGET_CPA 为未指定目标每次转化费用的广告系列设置目标每次转化费用
SET_TARGET_ROAS 为未指定目标广告支出回报率的广告系列设置目标广告支出回报率
REFRESH_CUSTOMER_MATCH_LIST 更新过去 90 天内未更新的客户名单
IMPROVE_GOOGLE_TAG_COVERAGE 在更多网页上部署 Google 代码
KEYWORD_MATCH_TYPE（已弃用） 已废弃，请改用 USE_BROAD_MATCH_KEYWORD

观看此视频了解详情

处理不受支持的类型

检索推荐内容

视频：实时编码

与 Google Ads API 中的大多数其他实体一样，您可以将 GoogleAdsService.SearchStream 与 Google Ads 查询语言查询搭配使用，以提取 Recommendation 对象。

对于每种类型的建议，系统都会在特定于建议的字段中提供详细信息。例如，CAMPAIGN_BUDGET 建议详情位于 campaign_budget_recommendation 字段中，并封装在 CampaignBudgetRecommendation 对象中。

在 recommendation 联合字段中查找所有特定于推荐的字段。

建议影响

某些建议类型会填充建议的 impact 字段。RecommendationImpact 包含对应用建议对账号效果的影响的估算值。impact.base_metrics 和 impact.potential_metrics 字段中提供了以下推荐指标：

  • impressions

  • clicks

  • cost_micros

  • conversions

  • all_conversions

  • video_views

代码示例

以下示例代码会从账号中检索类型为 KEYWORD 的所有可用和已关闭的建议，并输出其中的部分详细信息：

Java

try (GoogleAdsServiceClient googleAdsServiceClient =
        googleAdsClient.getLatestVersion().createGoogleAdsServiceClient();
    RecommendationServiceClient recommendationServiceClient =
        googleAdsClient.getLatestVersion().createRecommendationServiceClient()) {
  // Creates a query that retrieves keyword recommendations.
  String query =
      "SELECT recommendation.resource_name, "
          + "  recommendation.campaign, "
          + "  recommendation.keyword_recommendation "
          + "FROM recommendation "
          + "WHERE recommendation.type = KEYWORD";
  // Constructs the SearchGoogleAdsStreamRequest.
  SearchGoogleAdsStreamRequest request =
      SearchGoogleAdsStreamRequest.newBuilder()
          .setCustomerId(Long.toString(customerId))
          .setQuery(query)
          .build();

  // Issues the search stream request to detect keyword recommendations that exist for the
  // customer account.
  ServerStream<SearchGoogleAdsStreamResponse> stream =
      googleAdsServiceClient.searchStreamCallable().call(request);

  // Creates apply operations for all the recommendations found.
  List<ApplyRecommendationOperation> applyRecommendationOperations = new ArrayList<>();
  for (SearchGoogleAdsStreamResponse response : stream) {
    for (GoogleAdsRow googleAdsRow : response.getResultsList()) {
      Recommendation recommendation = googleAdsRow.getRecommendation();
      System.out.printf(
          "Keyword recommendation '%s' was found for campaign '%s'%n",
          recommendation.getResourceName(), recommendation.getCampaign());
      KeywordInfo keyword = recommendation.getKeywordRecommendation().getKeyword();
      System.out.printf("\tKeyword = '%s'%n", keyword.getText());
      System.out.printf("\tMatch type = '%s'%n", keyword.getMatchType());

      // Creates an ApplyRecommendationOperation that will apply this recommendation, and adds
      // it to the list of operations.
      applyRecommendationOperations.add(buildRecommendationOperation(recommendation));
    }
  }
DetectAndApplyRecommendations.java

C#

// Get the GoogleAdsServiceClient.
GoogleAdsServiceClient googleAdsService = client.GetService(
    Services.V18.GoogleAdsService);

// Creates a query that retrieves keyword recommendations.
string query = "SELECT recommendation.resource_name, " +
    "recommendation.campaign, recommendation.keyword_recommendation " +
    "FROM recommendation WHERE " +
    $"recommendation.type = KEYWORD";

List<ApplyRecommendationOperation> operations =
    new List<ApplyRecommendationOperation>();

try
{
    // Issue a search request.
    googleAdsService.SearchStream(customerId.ToString(), query,
        delegate (SearchGoogleAdsStreamResponse resp)
        {
            Console.WriteLine($"Found {resp.Results.Count} recommendations.");
            foreach (GoogleAdsRow googleAdsRow in resp.Results)
            {
                Recommendation recommendation = googleAdsRow.Recommendation;
                Console.WriteLine("Keyword recommendation " +
                    $"{recommendation.ResourceName} was found for campaign " +
                    $"{recommendation.Campaign}.");

                if (recommendation.KeywordRecommendation != null)
                {
                    KeywordInfo keyword =
                        recommendation.KeywordRecommendation.Keyword;
                    Console.WriteLine($"Keyword = {keyword.Text}, type = " +
                        "{keyword.MatchType}");
                }

                operations.Add(
                    BuildApplyRecommendationOperation(recommendation.ResourceName)
                );
            }
        }
    );
}
catch (GoogleAdsException e)
{
    Console.WriteLine("Failure:");
    Console.WriteLine($"Message: {e.Message}");
    Console.WriteLine($"Failure: {e.Failure}");
    Console.WriteLine($"Request ID: {e.RequestId}");
    throw;
}
DetectAndApplyRecommendations.cs

PHP

$googleAdsServiceClient = $googleAdsClient->getGoogleAdsServiceClient();
// Creates a query that retrieves keyword recommendations.
$query = 'SELECT recommendation.resource_name, recommendation.campaign, '
    . 'recommendation.keyword_recommendation '
    . 'FROM recommendation '
    . 'WHERE recommendation.type = KEYWORD ';
// Issues a search request to detect keyword recommendations that exist for the
// customer account.
$response =
    $googleAdsServiceClient->search(SearchGoogleAdsRequest::build($customerId, $query));

$operations = [];
// Iterates over all rows in all pages and prints the requested field values for
// the recommendation in each row.
foreach ($response->iterateAllElements() as $googleAdsRow) {
    /** @var GoogleAdsRow $googleAdsRow */
    $recommendation = $googleAdsRow->getRecommendation();
    printf(
        "Keyword recommendation with resource name '%s' was found for campaign "
        . "with resource name '%s':%s",
        $recommendation->getResourceName(),
        $recommendation->getCampaign(),
        PHP_EOL
    );
    if (!is_null($recommendation->getKeywordRecommendation())) {
        $keyword = $recommendation->getKeywordRecommendation()->getKeyword();
        printf(
            "\tKeyword = '%s'%s\ttype = '%s'%s",
            $keyword->getText(),
            PHP_EOL,
            KeywordMatchType::name($keyword->getMatchType()),
            PHP_EOL
        );
    }
    // Creates an ApplyRecommendationOperation that will be used to apply this
    // recommendation, and adds it to the list of operations.
    $operations[] = self::buildRecommendationOperation($recommendation->getResourceName());
}
DetectAndApplyRecommendations.php

Python

googleads_service = client.get_service("GoogleAdsService")
query = f"""
    SELECT
      recommendation.campaign,
      recommendation.keyword_recommendation
    FROM recommendation
    WHERE
      recommendation.type = KEYWORD"""

# Detects keyword recommendations that exist for the customer account.
response = googleads_service.search(customer_id=customer_id, query=query)

operations = []
for row in response.results:
    recommendation = row.recommendation
    print(
        f"Keyword recommendation ('{recommendation.resource_name}') "
        f"was found for campaign '{recommendation.campaign}."
    )

    keyword = recommendation.keyword_recommendation.keyword
    print(
        f"\tKeyword = '{keyword.text}'\n" f"\tType = '{keyword.match_type}'"
    )

    # Create an ApplyRecommendationOperation that will be used to apply
    # this recommendation, and add it to the list of operations.
    operations.append(
        build_recommendation_operation(client, recommendation.resource_name)
    )
detect_and_apply_recommendations.py

Ruby

query = <<~QUERY
  SELECT recommendation.resource_name, recommendation.campaign,
      recommendation.keyword_recommendation
  FROM recommendation
  WHERE recommendation.type = KEYWORD
QUERY

google_ads_service = client.service.google_ads

response = google_ads_service.search(
  customer_id: customer_id,
  query: query,
)

operations = response.each do |row|
  recommendation = row.recommendation

  puts "Keyword recommendation ('#{recommendation.resource_name}') was found for "\
    "campaign '#{recommendation.campaign}'."

  if recommendation.keyword_recommendation
    keyword = recommendation.keyword_recommendation.keyword
    puts "\tKeyword = '#{keyword.text}'"
    puts "\ttype = '#{keyword.match_type}'"
  end

  build_recommendation_operation(client, recommendation.resource_name)
end
detect_and_apply_recommendations.rb

Perl

# Create the search query.
my $search_query =
  "SELECT recommendation.resource_name, " .
  "recommendation.campaign, recommendation.keyword_recommendation " .
  "FROM recommendation " .
  "WHERE recommendation.type = KEYWORD";

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

my $search_stream_handler =
  Google::Ads::GoogleAds::Utils::SearchStreamHandler->new({
    service => $google_ads_service,
    request => {
      customerId => $customer_id,
      query      => $search_query
    }});

# Create apply operations for all the recommendations found.
my $apply_recommendation_operations = ();
$search_stream_handler->process_contents(
  sub {
    my $google_ads_row = shift;
    my $recommendation = $google_ads_row->{recommendation};
    printf "Keyword recommendation '%s' was found for campaign '%s'.\n",
      $recommendation->{resourceName}, $recommendation->{campaign};
    my $keyword = $recommendation->{keywordRecommendation}{keyword};
    printf "\tKeyword = '%s'\n",    $keyword->{text};
    printf "\tMatch type = '%s'\n", $keyword->{matchType};
    # Creates an ApplyRecommendationOperation that will apply this recommendation, and adds
    # it to the list of operations.
    push @$apply_recommendation_operations,
      build_recommendation_operation($recommendation);
  });
detect_and_apply_recommendations.pl

采取行动

您可以应用或忽略任何检索到的建议。

这些建议可能每天更改一次，甚至一天更改多次，具体取决于建议类型。如果发生这种情况，建议对象的 resource_name 会在完成建议检索后过时。

您最好在检索后尽快根据建议采取行动。

采纳建议

视频：采纳建议

您可以使用 RecommendationService 的 ApplyRecommendation 方法应用有效的或被拒绝的建议。

推荐类型可以有必需参数或可选参数。大多数建议都附带默认使用的推荐值。

并非所有建议类型都支持为账号设置自动采纳建议。不过，您可以针对 Google Ads API 完全支持的建议类型实现类似行为。如需了解详情，请参阅 DetectAndApplyRecommendations 代码示例。

使用 ApplyRecommendationOperation 的 apply_parameters 联合字段，可应用具有特定参数值的建议。每种合适的建议类型都有自己的字段。apply_parameters 字段中未列出的任何推荐类型都不会使用这些参数值。

代码示例

以下代码演示了如何构建 ApplyRecommendationOperation，以及如何替换建议值（如果您想将其替换为自己的值）。

Java

/** Creates and returns an ApplyRecommendationOperation to apply the given recommendation. */
private ApplyRecommendationOperation buildRecommendationOperation(Recommendation recommendation) {
  // If you have a recommendation ID instead of a resource name, you can create a resource name
  // like this:
  // String resourceName = ResourceNames.recommendation(customerId, recommendationId);

  // Creates a builder to construct the operation.
  Builder operationBuilder = ApplyRecommendationOperation.newBuilder();

  // Each recommendation type has optional parameters to override the recommended values. Below is
  // an example showing how to override a recommended ad when a TextAdRecommendation is applied.
  // operationBuilder.getTextAdBuilder().getAdBuilder().setResourceName("INSERT_AD_RESOURCE_NAME");

  // Sets the operation's resource name to the resource name of the recommendation to apply.
  operationBuilder.setResourceName(recommendation.getResourceName());
  return operationBuilder.build();
}
DetectAndApplyRecommendations.java

C#

private ApplyRecommendationOperation BuildApplyRecommendationOperation(
    string recommendationResourceName
)
{
    // If you have a recommendation_id instead of the resource_name you can create a
    // resource name from it like this:
    // string recommendationResourceName =
    //    ResourceNames.Recommendation(customerId, recommendationId)

    // 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.
    /*
    Ad overridingAd = new Ad()
    {
        Id = "INSERT_AD_ID_AS_LONG_HERE"
    };
    applyRecommendationOperation.TextAd = new TextAdParameters()
    {
        Ad = overridingAd
    };
    */

    ApplyRecommendationOperation applyRecommendationOperation =
    new ApplyRecommendationOperation()
    {
        ResourceName = recommendationResourceName
    };

    return applyRecommendationOperation;
}
DetectAndApplyRecommendations.cs

PHP

private static function buildRecommendationOperation(
    string $recommendationResourceName
): ApplyRecommendationOperation {
    // If you have a recommendation_id instead of the resource name, you can create a resource
    // name from it like this:
    /*
    $recommendationResourceName =
        ResourceNames::forRecommendation($customerId, $recommendationId);
    */

    // 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.
    $applyRecommendationOperation = new ApplyRecommendationOperation();
    $applyRecommendationOperation->setResourceName($recommendationResourceName);
    return $applyRecommendationOperation;
}
DetectAndApplyRecommendations.php

Python

def build_recommendation_operation(client, recommendation):
    """Creates a ApplyRecommendationOperation to apply the given recommendation.

    Args:
        client: an initialized GoogleAdsClient instance.
        customer_id: a client customer ID.
        recommendation: a resource name for the recommendation to be applied.
    """
    # If you have a recommendation ID instead of a resource name, you can create
    # a resource name like this:
    #
    # googleads_service = client.get_service("GoogleAdsService")
    # resource_name = googleads_service.recommendation_path(
    #   customer_id, recommendation.id
    # )

    operation = client.get_type("ApplyRecommendationOperation")

    # Each recommendation type has optional parameters to override the
    # recommended values. Below is an example showing how to override a
    # recommended ad when a TextAdRecommendation is applied.
    #
    # operation.text_ad.ad.resource_name = "INSERT_AD_RESOURCE_NAME"
    #
    # For more details, see:
    # https://developers.google.com/google-ads/api/reference/rpc/latest/ApplyRecommendationOperation#apply_parameters

    operation.resource_name = recommendation
    return operation
detect_and_apply_recommendations.py

Ruby

def build_recommendation_operation(client, recommendation)
  # If you have a recommendation_id instead of the resource_name
  # you can create a resource name from it like this:
  # recommendation_resource =
  #    client.path.recommendation(customer_id, recommendation_id)

  operations = client.operation.apply_recommendation
  operations.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.
  #
  # 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
  # operation.text_ad = text_ad_parameters
  #
  # For more details, see:
  # https://developers.google.com/google-ads/api/reference/rpc/latest/ApplyRecommendationOperation#apply_parameters

  return operation
end
detect_and_apply_recommendations.rb

Perl

sub build_recommendation_operation {
  my ($recommendation) = @_;

  # If you have a recommendation ID instead of a resource name, you can create a resource
  # name like this:
  # my $recommendation_resource_name =
  #   Google::Ads::GoogleAds::V18::Utils::ResourceNames::recommendation(
  #   $customer_id, $recommendation_id);

  # Each recommendation type has optional parameters to override the recommended values.
  # Below is an example showing how to override a recommended ad when a TextAdRecommendation
  # is applied.
  # my $overriding_ad = Google::Ads::GoogleAds::V18::Resources::Ad->new({
  #   id => "INSERT_AD_ID_AS_INTEGER_HERE"
  # });
  # my $text_ad_parameters =
  #   Google::Ads::GoogleAds::V18::Services::RecommendationService::TextAdParameters
  #   ->new({ad => $overriding_ad});
  # $apply_recommendation_operation->{textAd} = $text_ad_parameters;

  # Create an apply recommendation operation.
  my $apply_recommendation_operation =
    Google::Ads::GoogleAds::V18::Services::RecommendationService::ApplyRecommendationOperation
    ->new({
      resourceName => $recommendation->{resourceName}});

  return $apply_recommendation_operation;
}
detect_and_apply_recommendations.pl

以下示例调用 ApplyRecommendation，发送在上一个代码中创建的应用建议操作。

Java

// Issues a mutate request to apply the recommendations.
ApplyRecommendationResponse applyRecommendationsResponse =
    recommendationServiceClient.applyRecommendation(
        Long.toString(customerId), applyRecommendationOperations);
for (ApplyRecommendationResult applyRecommendationResult :
    applyRecommendationsResponse.getResultsList()) {
  System.out.printf(
      "Applied recommendation with resource name: '%s'.%n",
      applyRecommendationResult.getResourceName());
}
DetectAndApplyRecommendations.java

C#

private void ApplyRecommendation(GoogleAdsClient client, long customerId,
    List<ApplyRecommendationOperation> operations)
{
    // Get the RecommendationServiceClient.
    RecommendationServiceClient recommendationService = client.GetService(
        Services.V18.RecommendationService);

    ApplyRecommendationRequest applyRecommendationRequest = new ApplyRecommendationRequest()
    {
        CustomerId = customerId.ToString(),
    };

    applyRecommendationRequest.Operations.AddRange(operations);

    ApplyRecommendationResponse response =
        recommendationService.ApplyRecommendation(applyRecommendationRequest);
    foreach (ApplyRecommendationResult result in response.Results)
    {
        Console.WriteLine("Applied a recommendation with resource name: " +
            result.ResourceName);
    }
}
DetectAndApplyRecommendations.cs

PHP

private static function applyRecommendations(
    GoogleAdsClient $googleAdsClient,
    int $customerId,
    array $operations
): void {
    // Issues a mutate request to apply the recommendations.
    $recommendationServiceClient = $googleAdsClient->getRecommendationServiceClient();
    $response = $recommendationServiceClient->applyRecommendation(
        ApplyRecommendationRequest::build($customerId, $operations)
    );
    foreach ($response->getResults() as $appliedRecommendation) {
        /** @var Recommendation $appliedRecommendation */
        printf(
            "Applied a recommendation with resource name: '%s'.%s",
            $appliedRecommendation->getResourceName(),
            PHP_EOL
        );
    }
}
DetectAndApplyRecommendations.php

Python

def apply_recommendations(client, customer_id, operations):
    """Applies a batch of recommendations.

    Args:
        client: an initialized GoogleAdsClient instance.
        customer_id: a client customer ID.
        operations: a list of ApplyRecommendationOperation messages.
    """
    # Issues a mutate request to apply the recommendations.
    recommendation_service = client.get_service("RecommendationService")
    response = recommendation_service.apply_recommendation(
        customer_id=customer_id, operations=operations
    )

    for result in response.results:
        print(
            "Applied a recommendation with resource name: "
            f"'{result[0].resource_name}'."
        )
detect_and_apply_recommendations.py

Ruby

def apply_recommendations(client, customer_id, operations)
  # Issues a mutate request to apply the recommendation.
  recommendation_service = client.service.recommendation

  response = recommendation_service.apply_recommendation(
    customer_id: customer_id,
    operations: [operations],
  )

  response.results.each do |applied_recommendation|
    puts "Applied recommendation with resource name: '#{applied_recommendation.resource_name}'."
  end
end
detect_and_apply_recommendations.rb

Perl

# Issue a mutate request to apply the recommendations.
my $apply_recommendation_response =
  $api_client->RecommendationService()->apply({
    customerId => $customer_id,
    operations => $apply_recommendation_operations
  });

foreach my $result (@{$apply_recommendation_response->{results}}) {
  printf "Applied recommendation with resource name: '%s'.\n",
    $result->{resourceName};
}
detect_and_apply_recommendations.pl

观看以下视频了解详情

应用参数

批量

错误

测试

拒绝建议

视频：忽略建议

您可以使用 RecommendationService 忽略建议。代码结构与应用建议类似，但您需要使用 DismissRecommendationOperation 和 RecommendationService.DismissRecommendation。

观看以下视频了解详情

批量

错误

测试

自动采纳建议

您可以使用 RecommendationSubscriptionService 自动采纳特定类型的建议。

如需订阅特定类型的推荐，请创建一个 RecommendationSubscription 对象，将 type 字段设置为受支持的推荐类型之一，并将 status 字段设置为 ENABLED。

订阅支持的推荐类型

  • ENHANCED_CPC_OPT_IN
  • KEYWORD
  • KEYWORD_MATCH_TYPE
  • LOWER_TARGET_ROAS
  • MAXIMIZE_CLICKS_OPT_IN
  • OPTIMIZE_AD_ROTATION
  • RAISE_TARGET_CPA
  • RESPONSIVE_SEARCH_AD
  • RESPONSIVE_SEARCH_AD_IMPROVE_AD_STRENGTH
  • SEARCH_PARTNERS_OPT_IN
  • SEARCH_PLUS_OPT_IN
  • SET_TARGET_CPA
  • SET_TARGET_ROAS
  • TARGET_CPA_OPT_IN
  • TARGET_ROAS_OPT_IN
  • USE_BROAD_MATCH_KEYWORD

检索订阅

如需获取有关账号的推荐订阅的信息，请查询 recommendation_subscription 资源。

如需查看自动应用的更改，请查询 change_event 资源，并将 change_event.client_type 过滤为 GOOGLE_ADS_RECOMMENDATIONS_SUBSCRIPTION。

在广告系列制作过程中提供的建议

您可以使用 RecommendationService.GenerateRecommendationsRequest 在制作广告系列时针对一组给定的建议类型生成建议。

GenerateRecommendations 接受以下输入：客户 ID、广告渠道类型（必须为 SEARCH 或 PERFORMANCE_MAX）、要生成的推荐类型列表，以及根据指定类型而异的各种数据点。它会根据您提供的数据输出 Recommendation 对象的列表。如果没有足够的数据来为请求的 recommendation_types 生成建议，或者广告系列已处于建议状态，则结果集中不会包含针对该类型的建议。请确保您的应用能够处理为请求的推荐类型未返回任何推荐的情况。

下表介绍了 GenerateRecommendations 支持的建议类型，以及您必须提供哪些字段才能收到该类型的建议。最佳实践是，在收集与请求的推荐类型相关的所有信息后发送 GenerateRecommendations 请求。如需详细了解必需字段和可选字段（包括嵌套字段），请参阅参考文档。

RecommendationType 必填字段 可选字段
CAMPAIGN_BUDGET（从 v18 开始） 对于搜索广告系列和效果最大化广告系列，以下字段均为必填字段：
  • final_url
  • bidding_strategy_type
仅限搜索广告系列，还需要提供以下字段：
  • country_code
  • language_code
  • positive_location_id 或 negative_location_id
  • ad_group_info.keywords
  • bidding_info.
    bidding_strategy_target_info.
    target_impression_share_info    （如果出价策略设置为 TARGET_IMPRESSION_SHARE）
  • asset_group_info
  • budget_info
KEYWORD
  • seed_info
  • ad_group_info
MAXIMIZE_CLICKS_OPT_IN
  • conversion_tracking_status
  • bidding_info
MAXIMIZE_CONVERSIONS_OPT_IN
  • conversion_tracking_status
  • bidding_info
MAXIMIZE_CONVERSION_VALUE_OPT_IN
  • conversion_tracking_status
  • bidding_info
SET_TARGET_CPA
  • conversion_tracking_status
  • bidding_info
SET_TARGET_ROAS
  • conversion_tracking_status
  • bidding_info
SITELINK_ASSET
注意：返回的 SitelinkAssetRecommendation 对象将包含空列表。如果 GenerateRecommendations 响应包含 SitelinkAssetRecommendation，则可以将其视为向广告系列添加至少一个站内链接素材资源的信号。
  • campaign_sitelink_count
TARGET_CPA_OPT_IN
  • conversion_tracking_status
  • bidding_info
TARGET_ROAS_OPT_IN
  • conversion_tracking_status
  • bidding_info

使用流程示例

假设贵公司是一家广告代理机构，为用户提供广告系列制作工作流，并且您希望在此流程中向用户提供建议。您可以使用 GenerateRecommendationsRequest 按需生成建议，并将这些建议纳入到广告系列制作界面中。

使用流程可能如下所示：

  1. 用户前来您的应用以制作效果最大化广告系列。

  2. 在广告系列制作流程中，用户会提供一些初始信息。例如，他们提供详细信息来构建单个 SitelinkAsset，并选择 TARGET_SPEND 作为智能出价策略。

  3. 您发送一个 GenerateRecommendationsRequest，用于设置以下字段：

    • campaign_sitelink_count：设为 1，即进行中的广告系列中的站内链接素材资源的数量。

    • bidding_info：将嵌套的 bidding_strategy_type 字段设置为 TARGET_SPEND。

    • conversion_tracking_status：设置为此客户的 ConversionTrackingStatus。如需有关如何检索此字段的指导，请参阅转化管理的入门指南。

    • recommendation_types：设置为 [SITELINK_ASSET, MAXIMIZE_CLICKS_OPT_IN]。

    • advertising_channel_type：设置为 PERFORMANCE_MAX。

    • customer_id：设置为创建广告系列的客户的 ID。

  4. 您可以采用 GenerateRecommendationsResponse 中的建议（在本例中，是 SitelinkAssetRecommendation 和 MaximizeClicksOptInRecommendation），并在广告系列制作界面中显示这些建议，以便向用户推荐。如果用户接受建议，那么在用户完成广告系列构建流程后，您就可以将建议纳入广告系列制作请求中。