Class: Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1alpha1QueryMetricsResponseSliceDataPointConversationMeasure

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) ⇒ GoogleCloudContactcenterinsightsV1alpha1QueryMetricsResponseSliceDataPointConversationMeasure

Returns a new instance of GoogleCloudContactcenterinsightsV1alpha1QueryMetricsResponseSliceDataPointConversationMeasure.



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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15310

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 14998

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15004

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15010

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15015

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15020

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15025

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15030

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15035

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15040

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15045

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15051

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15057

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15062

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15067

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15072

def average_customer_satisfaction_rating
  @average_customer_satisfaction_rating
end

#average_duration ⇒ String

The average duration. Corresponds to the JSON property averageDuration

Returns:

  • (String) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15077

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15086

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15093

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15098

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15106

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15115

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15120

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15126

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15131

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15136

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15141

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15146

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15151

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15156

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15161

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15166

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15174

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15183

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15190

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15197

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15202

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15207

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15213

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15218

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15223

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15228

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15233

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15239

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15245

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15251

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15257

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15263

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15269

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15275

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15281

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15287

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15293

def knowledge_search_uri_click_ratio
  @knowledge_search_uri_click_ratio
end

#qa_tag_scores ⇒ Array<Google::Apis::ContactcenterinsightsV1::GoogleCloudContactcenterinsightsV1alpha1QueryMetricsResponseSliceDataPointConversationMeasureQaTagScore>

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

Returns:



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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15298

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15303

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) 


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# File 'lib/google/apis/contactcenterinsights_v1/classes.rb', line 15308

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 15315

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