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Sample queries and dashboards in conversation diagnostics (preview)

  • 项目

[This article is prerelease documentation and is subject to change.]

Learn about the queries that you can use to retrieve the diagnostics data for unified routing from Application Insights.

Important

  • This is a preview feature.
  • Preview features aren’t meant for production use and might have restricted functionality. These features are subject to supplemental terms of use, and are available before an official release so that customers can get early access and provide feedback.

Fallback queues

Purpose: Diagnose number of work items routed to fallback queues.

Query


let _endTime = datetime(2024-11-21T22:29:53Z);  
let _startTime = datetime(2024-09-22T21:29:53Z);  

Traces  
| where timestamp >= _startTime and timestamp <= _endTime  
| extend customDim = parse_json(customDimensions)  
| extend conversationId = tostring(customDim["powerplatform.analytics.resource.id"]),   
         subscenario = tostring(customDim["powerplatform.analytics.subscenario"]),  
         queueResult = parse_json(tostring(customDim["omnichannel.result"])).DisplayName  
| where subscenario == "RTQ" and queueResult == "[Insert Your Fallback queue name]"   
| project timestamp, conversationId, queueResult

Overflow handling

Purpose: Diagnose number of work items where overflow is trigger.

Query


Traces  
| extend customDim = parse_json(customDimensions)  
| extend conversationId = tostring(customDim["powerplatform.analytics.resource.id"]),  
         subscenario = tostring(customDim["powerplatform.analytics.subscenario"])  
| extend omnichannelAdditionalInfo = tostring((customDim["omnichannel.additional_info"]))  
| where omnichannelAdditionalInfo contains "OverflowTrigger"  
| project timestamp, conversationId, subscenario, omnichannelAdditionalInfo

Representatives who reject new assignments

Purpose: Diagnose customer service representatives (service representatives or representatives) who reject new assignments (by conversationId).

Query

let _endTime = datetime(2024-11-21T22:32:51Z);  
let _startTime = datetime(2024-09-22T21:32:51Z);  
Traces  
| where timestamp >= _startTime and timestamp <= _endTime  
| extend customDim = parse_json(customDimensions)  
| extend conversationId = tostring(customDim["powerplatform.analytics.resource.id"]),   
         subscenario = tostring(customDim["powerplatform.analytics.subscenario"]),  
         agentId = tostring(customDim["omnichannel.target_agent.id"]) // Extract representative ID from custom dimensions  
| where subscenario == "AgentReject"  
| summarize agentRejectionCount = count() by conversationId, agentId // Count rejections per representative per conversation  
| summarize rejectionCount = sum(agentRejectionCount),   
            agentRejectionDetails = make_list(pack('agentId', agentId, 'rejectionCount', agentRejectionCount))   
    by conversationId // Aggregate results by conversation  
| where rejectionCount > 1 // Filter conversations with more than one rejection  
| project conversationId, rejectionCount, agentRejectionDetails

Purpose: Diagnose representatives who reject new assignments (by representatives).

Query

let _endTime = datetime(2024-11-21T22:33:55Z);  
let _startTime = datetime(2024-09-22T21:33:55Z);  
Traces  
| where timestamp >= _startTime and timestamp <= _endTime  
| extend customDim = parse_json(customDimensions)  
| extend conversationId = tostring(customDim["powerplatform.analytics.resource.id"]),   
         subscenario = tostring(customDim["powerplatform.analytics.subscenario"]),  
         agentId = tostring(customDim["omnichannel.target_agent.id"]) // Extract representative ID from custom dimensions  
| where subscenario == "AgentReject"  
| summarize agentRejectionCount = count() by conversationId, agentId // Count rejections per representative per conversation  
| summarize rejectionCount = sum(agentRejectionCount),   
            agentRejectionDetails = make_list(pack('agentId', agentId, 'rejectionCount', agentRejectionCount))   
    by conversationId // Aggregate results by conversation  
| where rejectionCount > 1 // Filter conversations with more than one rejection  
| project conversationId, rejectionCount, agentRejectionDetails

Representative assignment took longer than two minutes

Purpose: Diagnose conversations where representative assignment took longer than two minutes.

Query

let _endTime = datetime(2024-11-21T22:35:56Z);  
let _startTime = datetime(2024-09-22T21:35:56Z);  
// Extract relevant subscenarios  
let subscenarios = traces  
| where timestamp >= _startTime and timestamp <= _endTime  
| extend customDim = parse_json(customDimensions)  
| extend conversationId = tostring(customDim["powerplatform.analytics.resource.id"]),  
         subscenario = tostring(customDim["powerplatform.analytics.subscenario"])  
| where subscenario in ("RTQ", "AgentAccept")  
| project timestamp, conversationId, subscenario;  
// Find the latest RTQ before each AgentAccept  
let latestRTQsBeforeAgentAccept = subscenarios  
| where subscenario == "RTQ"  
| join kind=inner (  
    subscenarios  
    | where subscenario == "AgentAccept"  
    | project agentAcceptTime = timestamp, conversationId  
) on conversationId  
| where timestamp < agentAcceptTime // Ensure RTQ is before AgentAccept  
| summarize latestRTQTime = max(timestamp) by conversationId, agentAcceptTime;  
// Calculate assignment time  
latestRTQsBeforeAgentAccept  
| extend assignmentTime = agentAcceptTime - latestRTQTime  
| where assignmentTime > 2min   
| project conversationId, assignmentTime

Use Azure Data Explorer dashboards with Application Insights queries

Apart from using Kusto queries directly within the Azure portal, you can use Azure Data Explorer Dashboards to visualize the results of these queries and create interactive, real-time reports. It's a powerful way to monitor and analyze the telemetry data from your Dynamics 365 Customer Service, Contact Center environment at a glance. We created a dashboard that you can directly import into your Azure Data Explorer environment.

The dashboard file and the instructions to link it to your ApplicationInsights subscription are in the GitHub repo at https://github.com/microsoft/Dynamics-365-FastTrack-Implementation-Assets/.

The following image illustrates the layout of the dashboard based on sample data.

Screenshot of the Azure Data Expleror sample Dashboard.

After your dashboard is ready, you can do one of the following:

  • Share the dashboard with anyone in your organization by granting them access to view or edit the dashboard in Azure Data Explorer.
  • Alternatively, embed the dashboard into your own portal or website using the embedding features provided by Azure.

By integrating your analytics and insights data into an Azure Data Explorer dashboard, you can continuously monitor your Dynamics 365 Customer Service and Dynamics 365 Contact Center environments.

Configure conversation diagnostics
Subscenarios in conversation diagnostics