Class: Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1mainQueryMetricsResponseSliceDataPointConversationMeasure

Inherits:
Object
  • Object
show all
Includes:
Google::Apis::Core::Hashable, Google::Apis::Core::JsonObjectSupport
Defined in:
lib/google/apis/contactcenterinsights_v1/classes.rb,
lib/google/apis/contactcenterinsights_v1/representations.rb,
lib/google/apis/contactcenterinsights_v1/representations.rb

Overview

The measure related to conversations.

Instance Attribute Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(**args) ⇒ GoogleCloudContactcenterinsightsV1mainQueryMetricsResponseSliceDataPointConversationMeasure

Returns a new instance of GoogleCloudContactcenterinsightsV1mainQueryMetricsResponseSliceDataPointConversationMeasure.



21938
21939
21940
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21938

def initialize(**args)
   update!(**args)
end

Instance Attribute Details

#aa_supervisor_assigned_conversations_count ⇒ Fixnum

The number of conversations that were assigned to an AA human supervisor. Corresponds to the JSON property aaSupervisorAssignedConversationsCount

Returns:

  • (Fixnum) 


21626
21627
21628
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21626

def aa_supervisor_assigned_conversations_count
  @aa_supervisor_assigned_conversations_count
end

#aa_supervisor_dropped_conversations_count ⇒ Fixnum

The number of conversations that were dropped, i.e. escalated but not assigned to an AA human supervisor. Corresponds to the JSON property aaSupervisorDroppedConversationsCount

Returns:

  • (Fixnum) 


21632
21633
21634
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21632

def aa_supervisor_dropped_conversations_count
  @aa_supervisor_dropped_conversations_count
end

#aa_supervisor_escalated_conversations_count ⇒ Fixnum

The number of conversations that were escalated to an AA human supervisor for intervention. Corresponds to the JSON property aaSupervisorEscalatedConversationsCount

Returns:

  • (Fixnum) 


21638
21639
21640
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21638

def aa_supervisor_escalated_conversations_count
  @aa_supervisor_escalated_conversations_count
end

#aa_supervisor_monitored_conversations_count ⇒ Fixnum

The number of conversations scanned by the AA human supervisor. Corresponds to the JSON property aaSupervisorMonitoredConversationsCount

Returns:

  • (Fixnum) 


21643
21644
21645
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21643

def aa_supervisor_monitored_conversations_count
  @aa_supervisor_monitored_conversations_count
end

#aa_supervisor_transferred_to_human_agent_conv_count ⇒ Fixnum

The number of conversations transferred to a human agent. Corresponds to the JSON property aaSupervisorTransferredToHumanAgentConvCount

Returns:

  • (Fixnum) 


21648
21649
21650
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21648

def aa_supervisor_transferred_to_human_agent_conv_count
  @aa_supervisor_transferred_to_human_agent_conv_count
end

#ai_coach_suggestion_agent_message_trigger_count ⇒ Fixnum

Count of agent messages that triggered an Ai Coach Suggestion. Corresponds to the JSON property aiCoachSuggestionAgentMessageTriggerCount

Returns:

  • (Fixnum) 


21653
21654
21655
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21653

def ai_coach_suggestion_agent_message_trigger_count
  @ai_coach_suggestion_agent_message_trigger_count
end

#ai_coach_suggestion_agent_usage_count ⇒ Fixnum

Count of Ai Coach Suggestion that has been used by agents. Corresponds to the JSON property aiCoachSuggestionAgentUsageCount

Returns:

  • (Fixnum) 


21658
21659
21660
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21658

def ai_coach_suggestion_agent_usage_count
  @ai_coach_suggestion_agent_usage_count
end

#ai_coach_suggestion_agent_usage_ratio ⇒ Float

Proportion of Ai Coach Suggestion that has been used by agents. Corresponds to the JSON property aiCoachSuggestionAgentUsageRatio

Returns:

  • (Float) 


21663
21664
21665
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21663

def ai_coach_suggestion_agent_usage_ratio
  @ai_coach_suggestion_agent_usage_ratio
end

#ai_coach_suggestion_customer_message_trigger_count ⇒ Fixnum

Count of customer messages that triggered an Ai Coach Suggestion. Corresponds to the JSON property aiCoachSuggestionCustomerMessageTriggerCount

Returns:

  • (Fixnum) 


21668
21669
21670
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21668

def ai_coach_suggestion_customer_message_trigger_count
  @ai_coach_suggestion_customer_message_trigger_count
end

#ai_coach_suggestion_customer_message_trigger_ratio ⇒ Float

Proportion of customer messages that triggered an Ai Coach Suggestion. Corresponds to the JSON property aiCoachSuggestionCustomerMessageTriggerRatio

Returns:

  • (Float) 


21673
21674
21675
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21673

def ai_coach_suggestion_customer_message_trigger_ratio
  @ai_coach_suggestion_customer_message_trigger_ratio
end

#ai_coach_suggestion_message_trigger_count ⇒ Fixnum

Count of end_of_utterance trigger event messages that triggered an Ai Coach Suggestion. Corresponds to the JSON property aiCoachSuggestionMessageTriggerCount

Returns:

  • (Fixnum) 


21679
21680
21681
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21679

def ai_coach_suggestion_message_trigger_count
  @ai_coach_suggestion_message_trigger_count
end

#ai_coach_suggestion_message_trigger_ratio ⇒ Float

Proportion of end_of_utterance trigger event messages that triggered an Ai Coach Suggestion. Corresponds to the JSON property aiCoachSuggestionMessageTriggerRatio

Returns:

  • (Float) 


21685
21686
21687
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21685

def ai_coach_suggestion_message_trigger_ratio
  @ai_coach_suggestion_message_trigger_ratio
end

#average_agent_sentiment_score ⇒ Float

The average agent's sentiment score. Corresponds to the JSON property averageAgentSentimentScore

Returns:

  • (Float) 


21690
21691
21692
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21690

def average_agent_sentiment_score
  @average_agent_sentiment_score
end

#average_client_sentiment_score ⇒ Float

The average client's sentiment score. Corresponds to the JSON property averageClientSentimentScore

Returns:

  • (Float) 


21695
21696
21697
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21695

def average_client_sentiment_score
  @average_client_sentiment_score
end

#average_customer_satisfaction_rating ⇒ Float

The average customer satisfaction rating. Corresponds to the JSON property averageCustomerSatisfactionRating

Returns:

  • (Float) 


21700
21701
21702
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21700

def average_customer_satisfaction_rating
  @average_customer_satisfaction_rating
end

#average_duration ⇒ String

The average duration. Corresponds to the JSON property averageDuration

Returns:

  • (String) 


21705
21706
21707
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21705

def average_duration
  @average_duration
end

#average_qa_normalized_score ⇒ Float

The average normalized QA score for a scorecard. When computing the average across a set of conversations, if a conversation has been evaluated with multiple revisions of a scorecard, only the latest revision results will be used. Will exclude 0's in average calculation. Will be only populated if the request specifies a dimension of QA_SCORECARD_ID. Corresponds to the JSON property averageQaNormalizedScore

Returns:

  • (Float) 


21714
21715
21716
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21714

def average_qa_normalized_score
  @average_qa_normalized_score
end

#average_qa_question_normalized_score ⇒ Float

Average QA normalized score averaged for questions averaged across all revisions of the parent scorecard. Will be only populated if the request specifies a dimension of QA_QUESTION_ID. Corresponds to the JSON property averageQaQuestionNormalizedScore

Returns:

  • (Float) 


21721
21722
21723
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21721

def average_qa_question_normalized_score
  @average_qa_question_normalized_score
end

#average_silence_percentage ⇒ Float

The average silence percentage. Corresponds to the JSON property averageSilencePercentage

Returns:

  • (Float) 


21726
21727
21728
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21726

def average_silence_percentage
  @average_silence_percentage
end

#average_summarization_suggestion_edit_distance ⇒ Float

Average edit distance of the summarization suggestions. Edit distance (also called as levenshtein distance) is calculated by summing up number of insertions, deletions and substitutions required to transform the summization feedback to the original summary suggestion. Corresponds to the JSON property averageSummarizationSuggestionEditDistance

Returns:

  • (Float) 


21734
21735
21736
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21734

def average_summarization_suggestion_edit_distance
  @average_summarization_suggestion_edit_distance
end

#average_summarization_suggestion_normalized_edit_distance ⇒ Float

Normalized Average edit distance of the summarization suggestions. Edit distance (also called as levenshtein distance) is calculated by summing up number of insertions, deletions and substitutions required to transform the summization feedback to the original summary suggestion. Normalized edit distance is the average of (edit distance / summary length). Corresponds to the JSON property averageSummarizationSuggestionNormalizedEditDistance

Returns:

  • (Float) 


21743
21744
21745
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21743

def average_summarization_suggestion_normalized_edit_distance
  @average_summarization_suggestion_normalized_edit_distance
end

#average_turn_count ⇒ Float

The average turn count. Corresponds to the JSON property averageTurnCount

Returns:

  • (Float) 


21748
21749
21750
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21748

def average_turn_count
  @average_turn_count
end

#avg_conversation_client_turn_sentiment_ema ⇒ Float

The exponential moving average of the sentiment score of client turns in the conversation. Corresponds to the JSON property avgConversationClientTurnSentimentEma

Returns:

  • (Float) 


21754
21755
21756
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21754

def avg_conversation_client_turn_sentiment_ema
  @avg_conversation_client_turn_sentiment_ema
end

#contained_conversation_count ⇒ Fixnum

The number of conversations that were contained. Corresponds to the JSON property containedConversationCount

Returns:

  • (Fixnum) 


21759
21760
21761
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21759

def contained_conversation_count
  @contained_conversation_count
end

#contained_conversation_ratio ⇒ Float

The percentage of conversations that were contained. Corresponds to the JSON property containedConversationRatio

Returns:

  • (Float) 


21764
21765
21766
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21764

def contained_conversation_ratio
  @contained_conversation_ratio
end

#conversation_ai_coach_suggestion_count ⇒ Fixnum

Count of conversations that has Ai Coach Suggestions. Corresponds to the JSON property conversationAiCoachSuggestionCount

Returns:

  • (Fixnum) 


21769
21770
21771
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21769

def conversation_ai_coach_suggestion_count
  @conversation_ai_coach_suggestion_count
end

#conversation_ai_coach_suggestion_ratio ⇒ Float

Proportion of conversations that has Ai Coach Suggestions. Corresponds to the JSON property conversationAiCoachSuggestionRatio

Returns:

  • (Float) 


21774
21775
21776
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21774

def conversation_ai_coach_suggestion_ratio
  @conversation_ai_coach_suggestion_ratio
end

#conversation_count ⇒ Fixnum

The conversation count. Corresponds to the JSON property conversationCount

Returns:

  • (Fixnum) 


21779
21780
21781
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21779

def conversation_count
  @conversation_count
end

#conversation_suggested_summary_ratio ⇒ Float

Proportion of conversations that had a suggested summary. Corresponds to the JSON property conversationSuggestedSummaryRatio

Returns:

  • (Float) 


21784
21785
21786
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21784

def conversation_suggested_summary_ratio
  @conversation_suggested_summary_ratio
end

#conversation_total_agent_message_count ⇒ Fixnum

The agent message count. Corresponds to the JSON property conversationTotalAgentMessageCount

Returns:

  • (Fixnum) 


21789
21790
21791
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21789

def conversation_total_agent_message_count
  @conversation_total_agent_message_count
end

#conversation_total_customer_message_count ⇒ Fixnum

The customer message count. Corresponds to the JSON property conversationTotalCustomerMessageCount

Returns:

  • (Fixnum) 


21794
21795
21796
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21794

def conversation_total_customer_message_count
  @conversation_total_customer_message_count
end

#conversational_agents_average_audio_in_audio_out_latency ⇒ Float

The average latency of conversational agents' audio in audio out latency per interaction. This is computed as the average of the all the interactions' audio in audio out latencies in a conversation and averaged across conversations. Corresponds to the JSON property conversationalAgentsAverageAudioInAudioOutLatency

Returns:

  • (Float) 


21802
21803
21804
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21802

def conversational_agents_average_audio_in_audio_out_latency
  @conversational_agents_average_audio_in_audio_out_latency
end

#conversational_agents_average_end_to_end_latency ⇒ Float

The average latency of conversational agents' latency per interaction. This is computed as the average of the all the iteractions' end to end latencies in a conversation and averaged across conversations. The e2e latency is the time between the end of the user utterance and the start of the agent utterance on the interaction level. Corresponds to the JSON property conversationalAgentsAverageEndToEndLatency

Returns:

  • (Float) 


21811
21812
21813
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21811

def conversational_agents_average_end_to_end_latency
  @conversational_agents_average_end_to_end_latency
end

#conversational_agents_average_llm_call_latency ⇒ Float

The average latency of conversational agents' LLM call latency per interaction. This is computed as the average of the all the interactions LLM call latencies in a conversation and averaged across conversations. Corresponds to the JSON property conversationalAgentsAverageLlmCallLatency

Returns:

  • (Float) 


21818
21819
21820
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21818

def conversational_agents_average_llm_call_latency
  @conversational_agents_average_llm_call_latency
end

#conversational_agents_average_tts_latency ⇒ Float

The macro average latency of conversational agents' TTS latency per interaction. This is computed as the average of the all the interactions' TTS latencies in a conversation and averaged across conversations. Corresponds to the JSON property conversationalAgentsAverageTtsLatency

Returns:

  • (Float) 


21825
21826
21827
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21825

def conversational_agents_average_tts_latency
  @conversational_agents_average_tts_latency
end

#dialogflow_average_webhook_latency ⇒ Float

Average latency of dialogflow webhook calls. Corresponds to the JSON property dialogflowAverageWebhookLatency

Returns:

  • (Float) 


21830
21831
21832
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21830

def dialogflow_average_webhook_latency
  @dialogflow_average_webhook_latency
end

#dialogflow_conversations_escalation_count ⇒ Float

count of conversations that was handed off from virtual agent to human agent. Corresponds to the JSON property dialogflowConversationsEscalationCount

Returns:

  • (Float) 


21835
21836
21837
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21835

def dialogflow_conversations_escalation_count
  @dialogflow_conversations_escalation_count
end

#dialogflow_conversations_escalation_ratio ⇒ Float

Proportion of conversations that was handed off from virtual agent to human agent. Corresponds to the JSON property dialogflowConversationsEscalationRatio

Returns:

  • (Float) 


21841
21842
21843
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21841

def dialogflow_conversations_escalation_ratio
  @dialogflow_conversations_escalation_ratio
end

#dialogflow_interactions_no_input_ratio ⇒ Float

Proportion of dialogflow interactions that has empty input. Corresponds to the JSON property dialogflowInteractionsNoInputRatio

Returns:

  • (Float) 


21846
21847
21848
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21846

def dialogflow_interactions_no_input_ratio
  @dialogflow_interactions_no_input_ratio
end

#dialogflow_interactions_no_match_ratio ⇒ Float

Proportion of dialogflow interactions that has no intent match for the input. Corresponds to the JSON property dialogflowInteractionsNoMatchRatio

Returns:

  • (Float) 


21851
21852
21853
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21851

def dialogflow_interactions_no_match_ratio
  @dialogflow_interactions_no_match_ratio
end

#dialogflow_webhook_failure_ratio ⇒ Float

Proportion of dialogflow webhook calls that failed. Corresponds to the JSON property dialogflowWebhookFailureRatio

Returns:

  • (Float) 


21856
21857
21858
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21856

def dialogflow_webhook_failure_ratio
  @dialogflow_webhook_failure_ratio
end

#dialogflow_webhook_timeout_ratio ⇒ Float

Proportion of dialogflow webhook calls that timed out. Corresponds to the JSON property dialogflowWebhookTimeoutRatio

Returns:

  • (Float) 


21861
21862
21863
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21861

def dialogflow_webhook_timeout_ratio
  @dialogflow_webhook_timeout_ratio
end

#knowledge_assist_negative_feedback_ratio ⇒ Float

Proportion of knowledge assist (Proactive Generative Knowledge Assist) queries that had negative feedback. Corresponds to the JSON property knowledgeAssistNegativeFeedbackRatio

Returns:

  • (Float) 


21867
21868
21869
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21867

def knowledge_assist_negative_feedback_ratio
  @knowledge_assist_negative_feedback_ratio
end

#knowledge_assist_positive_feedback_ratio ⇒ Float

Proportion of knowledge assist (Proactive Generative Knowledge Assist) queries that had positive feedback. Corresponds to the JSON property knowledgeAssistPositiveFeedbackRatio

Returns:

  • (Float) 


21873
21874
21875
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21873

def knowledge_assist_positive_feedback_ratio
  @knowledge_assist_positive_feedback_ratio
end

#knowledge_assist_result_count ⇒ Fixnum

Count of knowledge assist results (Proactive Generative Knowledge Assist) shown to the user. Corresponds to the JSON property knowledgeAssistResultCount

Returns:

  • (Fixnum) 


21879
21880
21881
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21879

def knowledge_assist_result_count
  @knowledge_assist_result_count
end

#knowledge_assist_uri_click_ratio ⇒ Float

Proportion of knowledge assist (Proactive Generative Knowledge Assist) queries that had a URL clicked. Corresponds to the JSON property knowledgeAssistUriClickRatio

Returns:

  • (Float) 


21885
21886
21887
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21885

def knowledge_assist_uri_click_ratio
  @knowledge_assist_uri_click_ratio
end

#knowledge_search_agent_query_source_ratio ⇒ Float

Proportion of knowledge search (Generative Knowledge Assist) queries made by the agent compared to the total number of knowledge search queries made. Corresponds to the JSON property knowledgeSearchAgentQuerySourceRatio

Returns:

  • (Float) 


21891
21892
21893
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21891

def knowledge_search_agent_query_source_ratio
  @knowledge_search_agent_query_source_ratio
end

#knowledge_search_negative_feedback_ratio ⇒ Float

Proportion of knowledge search (Generative Knowledge Assist) queries that had negative feedback. Corresponds to the JSON property knowledgeSearchNegativeFeedbackRatio

Returns:

  • (Float) 


21897
21898
21899
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21897

def knowledge_search_negative_feedback_ratio
  @knowledge_search_negative_feedback_ratio
end

#knowledge_search_positive_feedback_ratio ⇒ Float

Proportion of knowledge search (Generative Knowledge Assist) queries that had positive feedback. Corresponds to the JSON property knowledgeSearchPositiveFeedbackRatio

Returns:

  • (Float) 


21903
21904
21905
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21903

def knowledge_search_positive_feedback_ratio
  @knowledge_search_positive_feedback_ratio
end

#knowledge_search_result_count ⇒ Fixnum

Count of knowledge search results (Generative Knowledge Assist) shown to the user. Corresponds to the JSON property knowledgeSearchResultCount

Returns:

  • (Fixnum) 


21909
21910
21911
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21909

def knowledge_search_result_count
  @knowledge_search_result_count
end

#knowledge_search_suggested_query_source_ratio ⇒ Float

Proportion of knowledge search (Generative Knowledge Assist) queries suggested compared to the total number of knowledge search queries made. Corresponds to the JSON property knowledgeSearchSuggestedQuerySourceRatio

Returns:

  • (Float) 


21915
21916
21917
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21915

def knowledge_search_suggested_query_source_ratio
  @knowledge_search_suggested_query_source_ratio
end

#knowledge_search_uri_click_ratio ⇒ Float

Proportion of knowledge search (Generative Knowledge Assist) queries that had a URL clicked. Corresponds to the JSON property knowledgeSearchUriClickRatio

Returns:

  • (Float) 


21921
21922
21923
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21921

def knowledge_search_uri_click_ratio
  @knowledge_search_uri_click_ratio
end

#qa_tag_scores ⇒ Array<Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1mainQueryMetricsResponseSliceDataPointConversationMeasureQaTagScore>

Average QA normalized score for all the tags. Corresponds to the JSON property qaTagScores

Returns:



21926
21927
21928
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21926

def qa_tag_scores
  @qa_tag_scores
end

#summarization_suggestion_edit_ratio ⇒ Float

Proportion of summarization suggestions that were manually edited. Corresponds to the JSON property summarizationSuggestionEditRatio

Returns:

  • (Float) 


21931
21932
21933
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21931

def summarization_suggestion_edit_ratio
  @summarization_suggestion_edit_ratio
end

#summarization_suggestion_result_count ⇒ Fixnum

Count of summarization suggestions results. Corresponds to the JSON property summarizationSuggestionResultCount

Returns:

  • (Fixnum) 


21936
21937
21938
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21936

def summarization_suggestion_result_count
  @summarization_suggestion_result_count
end

Instance Method Details

#update!(**args) ⇒ Object

Update properties of this object



21943
21944
21945
21946
21947
21948
21949
21950
21951
21952
21953
21954
21955
21956
21957
21958
21959
21960
21961
21962
21963
21964
21965
21966
21967
21968
21969
21970
21971
21972
21973
21974
21975
21976
21977
21978
21979
21980
21981
21982
21983
21984
21985
21986
21987
21988
21989
21990
21991
21992
21993
21994
21995
21996
21997
21998
21999
 
# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 21943

def update!(**args)
  @aa_supervisor_assigned_conversations_count = args[:aa_supervisor_assigned_conversations_count] if args.key?(:aa_supervisor_assigned_conversations_count)
  @aa_supervisor_dropped_conversations_count = args[:aa_supervisor_dropped_conversations_count] if args.key?(:aa_supervisor_dropped_conversations_count)
  @aa_supervisor_escalated_conversations_count = args[:aa_supervisor_escalated_conversations_count] if args.key?(:aa_supervisor_escalated_conversations_count)
  @aa_supervisor_monitored_conversations_count = args[:aa_supervisor_monitored_conversations_count] if args.key?(:aa_supervisor_monitored_conversations_count)
  @aa_supervisor_transferred_to_human_agent_conv_count = args[:aa_supervisor_transferred_to_human_agent_conv_count] if args.key?(:aa_supervisor_transferred_to_human_agent_conv_count)
  @ai_coach_suggestion_agent_message_trigger_count = args[:ai_coach_suggestion_agent_message_trigger_count] if args.key?(:ai_coach_suggestion_agent_message_trigger_count)
  @ai_coach_suggestion_agent_usage_count = args[:ai_coach_suggestion_agent_usage_count] if args.key?(:ai_coach_suggestion_agent_usage_count)
  @ai_coach_suggestion_agent_usage_ratio = args[:ai_coach_suggestion_agent_usage_ratio] if args.key?(:ai_coach_suggestion_agent_usage_ratio)
  @ai_coach_suggestion_customer_message_trigger_count = args[:ai_coach_suggestion_customer_message_trigger_count] if args.key?(:ai_coach_suggestion_customer_message_trigger_count)
  @ai_coach_suggestion_customer_message_trigger_ratio = args[:ai_coach_suggestion_customer_message_trigger_ratio] if args.key?(:ai_coach_suggestion_customer_message_trigger_ratio)
  @ai_coach_suggestion_message_trigger_count = args[:ai_coach_suggestion_message_trigger_count] if args.key?(:ai_coach_suggestion_message_trigger_count)
  @ai_coach_suggestion_message_trigger_ratio = args[:ai_coach_suggestion_message_trigger_ratio] if args.key?(:ai_coach_suggestion_message_trigger_ratio)
  @average_agent_sentiment_score = args[:average_agent_sentiment_score] if args.key?(:average_agent_sentiment_score)
  @average_client_sentiment_score = args[:average_client_sentiment_score] if args.key?(:average_client_sentiment_score)
  @average_customer_satisfaction_rating = args[:average_customer_satisfaction_rating] if args.key?(:average_customer_satisfaction_rating)
  @average_duration = args[:average_duration] if args.key?(:average_duration)
  @average_qa_normalized_score = args[:average_qa_normalized_score] if args.key?(:average_qa_normalized_score)
  @average_qa_question_normalized_score = args[:average_qa_question_normalized_score] if args.key?(:average_qa_question_normalized_score)
  @average_silence_percentage = args[:average_silence_percentage] if args.key?(:average_silence_percentage)
  @average_summarization_suggestion_edit_distance = args[:average_summarization_suggestion_edit_distance] if args.key?(:average_summarization_suggestion_edit_distance)
  @average_summarization_suggestion_normalized_edit_distance = args[:average_summarization_suggestion_normalized_edit_distance] if args.key?(:average_summarization_suggestion_normalized_edit_distance)
  @average_turn_count = args[:average_turn_count] if args.key?(:average_turn_count)
  @avg_conversation_client_turn_sentiment_ema = args[:avg_conversation_client_turn_sentiment_ema] if args.key?(:avg_conversation_client_turn_sentiment_ema)
  @contained_conversation_count = args[:contained_conversation_count] if args.key?(:contained_conversation_count)
  @contained_conversation_ratio = args[:contained_conversation_ratio] if args.key?(:contained_conversation_ratio)
  @conversation_ai_coach_suggestion_count = args[:conversation_ai_coach_suggestion_count] if args.key?(:conversation_ai_coach_suggestion_count)
  @conversation_ai_coach_suggestion_ratio = args[:conversation_ai_coach_suggestion_ratio] if args.key?(:conversation_ai_coach_suggestion_ratio)
  @conversation_count = args[:conversation_count] if args.key?(:conversation_count)
  @conversation_suggested_summary_ratio = args[:conversation_suggested_summary_ratio] if args.key?(:conversation_suggested_summary_ratio)
  @conversation_total_agent_message_count = args[:conversation_total_agent_message_count] if args.key?(:conversation_total_agent_message_count)
  @conversation_total_customer_message_count = args[:conversation_total_customer_message_count] if args.key?(:conversation_total_customer_message_count)
  @conversational_agents_average_audio_in_audio_out_latency = args[:conversational_agents_average_audio_in_audio_out_latency] if args.key?(:conversational_agents_average_audio_in_audio_out_latency)
  @conversational_agents_average_end_to_end_latency = args[:conversational_agents_average_end_to_end_latency] if args.key?(:conversational_agents_average_end_to_end_latency)
  @conversational_agents_average_llm_call_latency = args[:conversational_agents_average_llm_call_latency] if args.key?(:conversational_agents_average_llm_call_latency)
  @conversational_agents_average_tts_latency = args[:conversational_agents_average_tts_latency] if args.key?(:conversational_agents_average_tts_latency)
  @dialogflow_average_webhook_latency = args[:dialogflow_average_webhook_latency] if args.key?(:dialogflow_average_webhook_latency)
  @dialogflow_conversations_escalation_count = args[:dialogflow_conversations_escalation_count] if args.key?(:dialogflow_conversations_escalation_count)
  @dialogflow_conversations_escalation_ratio = args[:dialogflow_conversations_escalation_ratio] if args.key?(:dialogflow_conversations_escalation_ratio)
  @dialogflow_interactions_no_input_ratio = args[:dialogflow_interactions_no_input_ratio] if args.key?(:dialogflow_interactions_no_input_ratio)
  @dialogflow_interactions_no_match_ratio = args[:dialogflow_interactions_no_match_ratio] if args.key?(:dialogflow_interactions_no_match_ratio)
  @dialogflow_webhook_failure_ratio = args[:dialogflow_webhook_failure_ratio] if args.key?(:dialogflow_webhook_failure_ratio)
  @dialogflow_webhook_timeout_ratio = args[:dialogflow_webhook_timeout_ratio] if args.key?(:dialogflow_webhook_timeout_ratio)
  @knowledge_assist_negative_feedback_ratio = args[:knowledge_assist_negative_feedback_ratio] if args.key?(:knowledge_assist_negative_feedback_ratio)
  @knowledge_assist_positive_feedback_ratio = args[:knowledge_assist_positive_feedback_ratio] if args.key?(:knowledge_assist_positive_feedback_ratio)
  @knowledge_assist_result_count = args[:knowledge_assist_result_count] if args.key?(:knowledge_assist_result_count)
  @knowledge_assist_uri_click_ratio = args[:knowledge_assist_uri_click_ratio] if args.key?(:knowledge_assist_uri_click_ratio)
  @knowledge_search_agent_query_source_ratio = args[:knowledge_search_agent_query_source_ratio] if args.key?(:knowledge_search_agent_query_source_ratio)
  @knowledge_search_negative_feedback_ratio = args[:knowledge_search_negative_feedback_ratio] if args.key?(:knowledge_search_negative_feedback_ratio)
  @knowledge_search_positive_feedback_ratio = args[:knowledge_search_positive_feedback_ratio] if args.key?(:knowledge_search_positive_feedback_ratio)
  @knowledge_search_result_count = args[:knowledge_search_result_count] if args.key?(:knowledge_search_result_count)
  @knowledge_search_suggested_query_source_ratio = args[:knowledge_search_suggested_query_source_ratio] if args.key?(:knowledge_search_suggested_query_source_ratio)
  @knowledge_search_uri_click_ratio = args[:knowledge_search_uri_click_ratio] if args.key?(:knowledge_search_uri_click_ratio)
  @qa_tag_scores = args[:qa_tag_scores] if args.key?(:qa_tag_scores)
  @summarization_suggestion_edit_ratio = args[:summarization_suggestion_edit_ratio] if args.key?(:summarization_suggestion_edit_ratio)
  @summarization_suggestion_result_count = args[:summarization_suggestion_result_count] if args.key?(:summarization_suggestion_result_count)
end