Class: Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasure
- Inherits:
-
Object
- Object
- Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasure
- 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
-
#aa_supervisor_assigned_conversations_count ⇒ Fixnum
The number of conversations that were assigned to an AA human supervisor.
-
#aa_supervisor_dropped_conversations_count ⇒ Fixnum
The number of conversations that were dropped, i.e.
-
#aa_supervisor_escalated_conversations_count ⇒ Fixnum
The number of conversations that were escalated to an AA human supervisor for intervention.
-
#aa_supervisor_monitored_conversations_count ⇒ Fixnum
The number of conversations scanned by the AA human supervisor.
-
#aa_supervisor_transferred_to_human_agent_conv_count ⇒ Fixnum
The number of conversations transferred to a human agent.
-
#ai_coach_suggestion_agent_message_trigger_count ⇒ Fixnum
Count of agent messages that triggered an Ai Coach Suggestion.
-
#ai_coach_suggestion_agent_usage_count ⇒ Fixnum
Count of Ai Coach Suggestion that has been used by agents.
-
#ai_coach_suggestion_agent_usage_ratio ⇒ Float
Proportion of Ai Coach Suggestion that has been used by agents.
-
#ai_coach_suggestion_customer_message_trigger_count ⇒ Fixnum
Count of customer messages that triggered an Ai Coach Suggestion.
-
#ai_coach_suggestion_customer_message_trigger_ratio ⇒ Float
Proportion of customer messages that triggered an Ai Coach Suggestion.
-
#ai_coach_suggestion_message_trigger_count ⇒ Fixnum
Count of end_of_utterance trigger event messages that triggered an Ai Coach Suggestion.
-
#ai_coach_suggestion_message_trigger_ratio ⇒ Float
Proportion of end_of_utterance trigger event messages that triggered an Ai Coach Suggestion.
-
#average_agent_sentiment_score ⇒ Float
The average agent's sentiment score.
-
#average_client_sentiment_score ⇒ Float
The average client's sentiment score.
-
#average_customer_satisfaction_rating ⇒ Float
The average customer satisfaction rating.
-
#average_duration ⇒ String
The average duration.
-
#average_qa_normalized_score ⇒ Float
The average normalized QA score for a scorecard.
-
#average_qa_question_normalized_score ⇒ Float
Average QA normalized score averaged for questions averaged across all revisions of the parent scorecard.
-
#average_silence_percentage ⇒ Float
The average silence percentage.
-
#average_summarization_suggestion_edit_distance ⇒ Float
Average edit distance of the summarization suggestions.
-
#average_summarization_suggestion_normalized_edit_distance ⇒ Float
Normalized Average edit distance of the summarization suggestions.
-
#average_turn_count ⇒ Float
The average turn count.
-
#avg_conversation_client_turn_sentiment_ema ⇒ Float
The exponential moving average of the sentiment score of client turns in the conversation.
-
#contained_conversation_count ⇒ Fixnum
The number of conversations that were contained.
-
#contained_conversation_ratio ⇒ Float
The percentage of conversations that were contained.
-
#conversation_ai_coach_suggestion_count ⇒ Fixnum
Count of conversations that has Ai Coach Suggestions.
-
#conversation_ai_coach_suggestion_ratio ⇒ Float
Proportion of conversations that has Ai Coach Suggestions.
-
#conversation_count ⇒ Fixnum
The conversation count.
-
#conversation_suggested_summary_ratio ⇒ Float
Proportion of conversations that had a suggested summary.
-
#conversation_total_agent_message_count ⇒ Fixnum
The agent message count.
-
#conversation_total_customer_message_count ⇒ Fixnum
The customer message count.
-
#conversational_agents_average_audio_in_audio_out_latency ⇒ Float
The average latency of conversational agents' audio in audio out latency per interaction.
-
#conversational_agents_average_end_to_end_latency ⇒ Float
The average latency of conversational agents' latency per interaction.
-
#conversational_agents_average_llm_call_latency ⇒ Float
The average latency of conversational agents' LLM call latency per interaction.
-
#conversational_agents_average_tts_latency ⇒ Float
The macro average latency of conversational agents' TTS latency per interaction.
-
#dialogflow_average_webhook_latency ⇒ Float
Average latency of dialogflow webhook calls.
-
#dialogflow_conversations_escalation_count ⇒ Float
count of conversations that was handed off from virtual agent to human agent.
-
#dialogflow_conversations_escalation_ratio ⇒ Float
Proportion of conversations that was handed off from virtual agent to human agent.
-
#dialogflow_interactions_no_input_ratio ⇒ Float
Proportion of dialogflow interactions that has empty input.
-
#dialogflow_interactions_no_match_ratio ⇒ Float
Proportion of dialogflow interactions that has no intent match for the input.
-
#dialogflow_webhook_failure_ratio ⇒ Float
Proportion of dialogflow webhook calls that failed.
-
#dialogflow_webhook_timeout_ratio ⇒ Float
Proportion of dialogflow webhook calls that timed out.
-
#knowledge_assist_negative_feedback_ratio ⇒ Float
Proportion of knowledge assist (Proactive Generative Knowledge Assist) queries that had negative feedback.
-
#knowledge_assist_positive_feedback_ratio ⇒ Float
Proportion of knowledge assist (Proactive Generative Knowledge Assist) queries that had positive feedback.
-
#knowledge_assist_result_count ⇒ Fixnum
Count of knowledge assist results (Proactive Generative Knowledge Assist) shown to the user.
-
#knowledge_assist_uri_click_ratio ⇒ Float
Proportion of knowledge assist (Proactive Generative Knowledge Assist) queries that had a URL clicked.
-
#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.
-
#knowledge_search_negative_feedback_ratio ⇒ Float
Proportion of knowledge search (Generative Knowledge Assist) queries that had negative feedback.
-
#knowledge_search_positive_feedback_ratio ⇒ Float
Proportion of knowledge search (Generative Knowledge Assist) queries that had positive feedback.
-
#knowledge_search_result_count ⇒ Fixnum
Count of knowledge search results (Generative Knowledge Assist) shown to the user.
-
#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.
-
#knowledge_search_uri_click_ratio ⇒ Float
Proportion of knowledge search (Generative Knowledge Assist) queries that had a URL clicked.
-
#qa_tag_scores ⇒ Array<Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasureQaTagScore>
Average QA normalized score for all the tags.
-
#summarization_suggestion_edit_ratio ⇒ Float
Proportion of summarization suggestions that were manually edited.
-
#summarization_suggestion_result_count ⇒ Fixnum
Count of summarization suggestions results.
Instance Method Summary collapse
-
#initialize(**args) ⇒ GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasure
constructor
A new instance of GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasure.
-
#update!(**args) ⇒ Object
Update properties of this object.
Constructor Details
#initialize(**args) ⇒ GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasure
Returns a new instance of GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasure.
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8672 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8360 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8366 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8372 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8377 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8382 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8387 def @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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8392 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8397 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8402 def @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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8407 def @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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8413 def @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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8419 def @ai_coach_suggestion_message_trigger_ratio end |
#average_agent_sentiment_score ⇒ Float
The average agent's sentiment score.
Corresponds to the JSON property averageAgentSentimentScore
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8424 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8429 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8434 def @average_customer_satisfaction_rating end |
#average_duration ⇒ String
The average duration.
Corresponds to the JSON property averageDuration
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8439 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8448 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8455 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8460 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8468 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8477 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8482 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8488 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8493 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8498 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8503 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8508 def conversation_ai_coach_suggestion_ratio @conversation_ai_coach_suggestion_ratio end |
#conversation_count ⇒ Fixnum
The conversation count.
Corresponds to the JSON property conversationCount
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8513 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8518 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8523 def @conversation_total_agent_message_count end |
#conversation_total_customer_message_count ⇒ Fixnum
The customer message count.
Corresponds to the JSON property conversationTotalCustomerMessageCount
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8528 def @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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8536 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8545 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8552 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8559 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8564 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8569 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8575 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8580 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8585 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8590 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8595 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8601 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8607 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8613 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8619 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8625 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8631 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8637 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8643 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8649 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8655 def knowledge_search_uri_click_ratio @knowledge_search_uri_click_ratio end |
#qa_tag_scores ⇒ Array<Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1QueryMetricsResponseSliceDataPointConversationMeasureQaTagScore>
Average QA normalized score for all the tags.
Corresponds to the JSON property qaTagScores
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8660 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8665 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
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8670 def summarization_suggestion_result_count @summarization_suggestion_result_count end |
Instance Method Details
#update!(**args) ⇒ Object
Update properties of this object
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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 8677 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 |