建议可以改善您的 您的广告系列:
- 引入相关的新功能
- 通过改进出价、关键字和广告获得更多的投入回报
- 提高广告系列的整体效果和效率
若要提高优化得分,您可以使用
RecommendationService
(用于检索)
然后相应地采纳或拒绝这些建议从 v15 开始
Google Ads API 后,您还可以订阅自动应用
使用 RecommendationSubscriptionService
进行推荐。
优化得分
优化得分是
预估您的 Google Ads 账号在设置方面的优化程度和可用情况
在Customer
和
Campaign
级。
通过
Customer.optimization_score_weight
仅适用于非经理账号,用于计算
多个账号的优化得分。检索优化得分并
将账号的优化得分权重相乘
(Customer.optimization_score * Customer.optimization_score_weight
) 可计算
整体优化得分。
针对customer
和campaign
,可以使用与优化相关的指标
报告:
- 通过
metrics.optimization_score_url
提供了指向账号的深层链接,用于查看 Google Ads 界面中的建议。 - 通过
metrics.optimization_score_uplift
表示:如果所有相关选项都相关, 建议。这是一个估算值 建议的总体情况,而不仅仅是各条建议的总提升幅度得分 建议。
如需对返回的建议进行分组和排序,您可以对这两项内容进行细分
在您的segments.recommendation_type
查询。
推荐类型
完全支持的建议类型
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 |
使用目标每次转化费用出价 |
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”出价策略进行出价 |
ENHANCED_CPC_OPT_IN |
使用智能点击付费出价 |
MAXIMIZE_CLICKS_OPT_IN |
采用“尽可能争取更多点击次数”出价策略 |
OPTIMIZE_AD_ROTATION |
采用优化型广告轮播设置 |
MOVE_UNUSED_BUDGET |
将未使用的预算转移到受限的预算 |
TARGET_ROAS_OPT_IN |
采用“目标广告支出回报率”出价策略 |
FORECASTING_CAMPAIGN_BUDGET |
在 未来 |
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 |
使用广泛匹配 匹配(适用于采用自动出价的基于转化的广告系列) |
RESPONSIVE_SEARCH_AD_ASSET |
为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“将展示广告网络也纳入投放范围” |
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_DISCOVERY_AD_STRENGTH |
提升需求开发广告系列中的广告效力 |
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定位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果提升到 “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 |
在目标每次转化费用过低且 很少或根本没有转化 |
FORECASTING_SET_TARGET_ROAS |
在季节性活动开始前提高预算 预测会提高流量并更改出价策略 从“尽可能提高转化价值”改为“目标广告支出回报率” |
LEAD_FORM |
向广告系列添加潜在客户表单素材资源 |
CALLOUT_ASSET |
在广告系列或客户一级添加宣传信息素材资源 |
SITELINK_ASSET |
将站内链接素材资源添加到广告系列或客户级 |
CALL_ASSET |
在广告系列或客户一级添加电话素材资源 |
SHOPPING_ADD_AGE_GROUP |
为因以下原因而被降位的商品添加 age group [年龄段] 属性: 缺少年龄段 |
SHOPPING_ADD_COLOR |
为因缺少商品而降位的商品添加颜色 颜色 |
SHOPPING_ADD_GENDER |
请为因缺失而降位的商品添加性别 性别 |
SHOPPING_ADD_GTIN |
为降位的商品添加 GTIN(全球贸易项目代码) 因为缺少 GTIN |
SHOPPING_ADD_MORE_IDENTIFIERS |
为因缺失而被降位的商品添加更多标识码 标识符 |
SHOPPING_ADD_SIZE |
请为因缺失商品而降位的商品添加尺寸 尺码 |
SHOPPING_ADD_PRODUCTS_TO_CAMPAIGN |
为要投放的广告系列添加产品 |
SHOPPING_FIX_DISAPPROVED_PRODUCTS |
解决产品被拒登的问题 |
SHOPPING_TARGET_ALL_OFFERS |
制作定位到所有优惠的全包型广告系列 |
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 |
目标广告支出回报率降幅 |
FORECASTING_SET_TARGET_CPA |
为没有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,即: 预计会带来更多流量的季节性活动开始之前 |
SET_TARGET_CPA |
为没有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 |
为没有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 天 |
IMPROVE_GOOGLE_TAG_COVERAGE |
在更多网页上部署 Google 代码 |
CALLOUT_EXTENSION (已弃用) |
已弃用,请改用 CALLOUT_ASSET |
SITELINK_EXTENSION (已弃用) |
已弃用,请改用 SITELINK_ASSET |
CALL_EXTENSION (已弃用) |
已弃用,请改用 CALL_ASSET |
KEYWORD_MATCH_TYPE (已弃用) |
已弃用,请改用 USE_BROAD_MATCH_KEYWORD |
观看此视频了解详情
处理不支持的类型
检索推荐内容
与 Google Ads API 中的大多数其他实体一样,Recommendation
对象使用
GoogleAdsService.SearchStream
。
对于每种类型的建议
建议字段。例如,CAMPAIGN_BUDGET
项建议
请查看
campaign_budget_recommendation
字段,并封装在
CampaignBudgetRecommendation
对象。
在
recommendation
并集字段。
对建议的影响
某些建议类型会填充
impact
字段。
RecommendationImpact
包含估算广告对账号效果可能产生的影响,
来采纳建议以下
推荐指标
(在 impact.base_metrics
和 impact.potential_metrics
字段中提供):
impressions
clicks
cost_micros
conversions
all_conversions
(从 Google Ads API v16 开始提供)video_views
代码示例
以下示例代码可检索所有可用和已拒绝的建议
类型的 KEYWORD
,并输出其部分详细信息:
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)); } }
C#
// Get the GoogleAdsServiceClient. GoogleAdsServiceClient googleAdsService = client.GetService( Services.V17.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; }
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()); }
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) )
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
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); });
采取行动
您可以应用或忽略任何检索到的建议。
系统每天都会提供不同的建议,具体取决于建议类型
甚至每天多次出现这种情况时
对象的 resource_name
可以
会在检索到建议后过时。
最好在检索后尽快对建议采取措施。
采纳建议
您可以通过
ApplyRecommendation
方法的
RecommendationService
。
建议类型可以包含必需参数或可选参数。大多数人 建议附带默认使用的推荐值。
无法为自动采纳建议设置账号
支持所有建议类型。不过,您也可以实现类似的
Google Ads API 完全支持的建议类型的行为。
参阅 DetectAndApplyRecommendations
代码
示例了解详情。
使用
apply_parameters
ApplyRecommendationOperation
的并集字段,以对其应用建议
特定的参数值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建议类型均不使用
这些参数值
代码示例
以下代码演示了如何构建
ApplyRecommendationOperation
和
如果您要将建议的值替换为
。
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(); }
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; }
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; }
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
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
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::V17::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::V17::Resources::Ad->new({ # id => "INSERT_AD_ID_AS_INTEGER_HERE" # }); # my $text_ad_parameters = # Google::Ads::GoogleAds::V17::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::V17::Services::RecommendationService::ApplyRecommendationOperation ->new({ resourceName => $recommendation->{resourceName}}); return $apply_recommendation_operation; }
下一个示例会调用
ApplyRecommendation
、
发送在上一步骤中创建的应用建议操作
代码。
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()); }
C#
private void ApplyRecommendation(GoogleAdsClient client, long customerId, List<ApplyRecommendationOperation> operations) { // Get the RecommendationServiceClient. RecommendationServiceClient recommendationService = client.GetService( Services.V17.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); } }
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 ); } }
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}'." )
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
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}; }
观看这些视频,了解详情
应用参数
批量
错误
测试
拒绝建议
您可以使用
RecommendationService
。代码
结构与采纳建议类似,但改用
DismissRecommendationOperation
和
RecommendationService.DismissRecommendation
。
观看这些视频,了解详情
批量
错误
测试
自动采纳建议
从 Google Ads API v15 开始,您可以使用
RecommendationSubscriptionService
来自动采纳特定类型的建议
如需订阅特定的推荐类型,请创建一个
RecommendationSubscription
对象,
将 type
字段设为以下其中一项:
支持的建议
types,并设置
status
字段设为 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
如需获取账号推荐订阅的相关信息,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,用于过滤
change_client_type
至
GOOGLE_ADS_RECOMMENDATIONS_SUBSCRIPTION
。
广告系列制作方面的建议
从 Google Ads API v16 版开始,您可以使用
RecommendationService.GenerateRecommendationsRequest
在广告系列制作期间针对指定的一组数据生成建议,
建议类型。
GenerateRecommendations
接受客户 ID(一个广告渠道)作为输入内容
该类型必须是
SEARCH
或
PERFORMANCE_MAX
,
要生成的建议类型列表,以及根据相关数据
指定的类型。它会根据Recommendation
您提供的数据。如果数据不足,无法生成建议
针对所请求的
recommendation_types
、
或者,如果广告系列已处于建议状态,则结果集不会
包含针对该类型的建议请确保您的应用会处理
未针对所请求的建议返回任何建议的情况
。
下表介绍了
GenerateRecommendations
支持,以及您必须提供的字段才能接收
建议。按照最佳做法,
收集到所有信息之后的 GenerateRecommendations
请求
与所请求的建议类型有关如需了解更多详情,请参阅
必填字段和选填字段(包括嵌套字段),请查阅
参考文档。
RecommendationType | 必填字段 | 可选字段 |
---|---|---|
KEYWORD |
|
|
MAXIMIZE_CLICKS_OPT_IN |
|
|
MAXIMIZE_CONVERSIONS_OPT_IN |
|
|
MAXIMIZE_CONVERSION_VALUE_OPT_IN |
|
|
SET_TARGET_CPA |
|
|
SET_TARGET_ROAS |
|
|
SITELINK_ASSET
注意:返回的 SitelinkAssetRecommendation
对象将包含空列表。如果 GenerateRecommendations
包含 SitelinkAssetRecommendation ,其可以是
视作向广告系列添加至少一个站内链接素材资源的信号。 |
|
|
TARGET_CPA_OPT_IN |
|
|
TARGET_ROAS_OPT_IN |
|
使用流程示例
假设您的公司是一家广告代理机构
并且希望向用户提供建议
会非常有用您可以使用
GenerateRecommendationsRequest
按需生成建议,并将这些建议
复制到广告系列制作界面中
使用流程可能如下所示:
用户进入您的应用制作效果最大化广告系列。
用户提供一些初始信息作为广告系列的一部分 构建流程。例如,它们提供了构建单个
SitelinkAsset
,他们选择TARGET_SPEND
用作智能出价 策略您发送一个
GenerateRecommendationsRequest
,它会设置以下字段:campaign_sitelink_count
: 已设置为1
,这是正在制作中的站内链接素材资源的数量 广告系列。bidding_info
: 将嵌套的bidding_strategy_type
字段设置为TARGET_SPEND
。conversion_tracking_status
:设置为ConversionTrackingStatus
。有关如何检索此字段的指导,请访问 开始前须知 转化管理指南recommendation_types
:设置为[SITELINK_ASSET, MAXIMIZE_CLICKS_OPT_IN]
。advertising_channel_type
:设置为PERFORMANCE_MAX
。customer_id
:可设置为制作广告系列的客户的 ID。
您可以在
GenerateRecommendationsResponse
- 在这个示例中,SitelinkAssetRecommendation
和MaximizeClicksOptInRecommendation
,并通过在您的广告系列中展示这些素材资源,向用户推荐这些素材资源 构建界面。如果用户接受了某个建议,您可以 在用户完成上述操作后,将代码添加到广告系列制作请求中。 广告系列制作流程