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Please give a quick overview of your product feature request or feedback and note who in your org is affected by this issue:In order for us to use Entity from the Zendesk CoPilot add-on effectively and for the Entity functionality to provide real added value for us, we would like the content of the agent signature to be ignored during entity detection.The agent signature contains information about which support unit a colleague belongs to, such as “Global <Product A> Support” or “EMEA <Product B> Support” or the public eMail for support group.However, <Product A> and <Product B> are values that should be recognized from the customer's ticket content via entity detection and should not be taken from the content of the agent signature.As can be seen in the following screenshots, Entity Detection in the ticket uses content from the agent's signature. What problem do you see this solving?Entity detection does not work as intended when using the “Values in all interactions” option because content from the agent's signature is included. When was the last time you were affected by this lack of functionality, or specific tool? What happened? How often does this problem occur and how does this impact your business?Since we cannot activate entities with the current state of implementation, we are constantly confronted with this limitation.As already mentioned, this leads either to a poor user experience or to a low degree of automation. Are you currently using a workaround to solve this problem?We are currently unaware of any workaround. What would be your ideal solution to this problem? How would it work or function?The ideal solution is for content from the agent signature to be automatically excluded from entity detection.Alternatively, it should be possible to configure whether content from the agent signature should really be included.
Feature Request: Agent-Level Acceptance Rate for MessagingCurrently, the Acceptance Rate metric in Zendesk messaging is only available at the ticket level, making it challenging to evaluate agent-level performance accurately. This feature request is to implement an Acceptance Rate metric for individual agents, similar to what exists for Live Chat.Description/Use Case:The requested feature would enable tracking and analyzing Acceptance Rate for messaging at the agent level, providing insights into how effectively individual agents are engaging with incoming conversation offers. For example, this metric would allow managers to:-Identify agents who are consistently missing messaging offers.-Measure and improve agent responsiveness for messaging, especially in high-traffic environments.-Benchmark agent performance and set clear KPIs for acceptance behavior. This functionality would align messaging performance monitoring the same with Live Chat, where agent-level Acceptance Rate is already available and highly valuable for performance evaluation.Business Impact of Current Limitation:The lack of agent-level Acceptance Rate tracking in Zendesk messaging creates the following challenges:-Inability to Track Agent Responsiveness: Managers cannot accurately identify which agents are failing to accept messaging conversations. This can lead to missed opportunities and inconsistent customer experiences.-Reduced Accountability: Without an agent-level metric, it’s harder to hold individual agents accountable for their responsiveness to messaging offers.-Performance Optimization Limitations: Teams are unable to provide targeted coaching or performance improvement plans for agents, potentially impacting overall team efficiency and customer satisfaction.Adding this metric would enhance Zendesk’s reporting capabilities and ensure that messaging workflows are as robust and measurable as those for Live Chat.
On Explore reports, Twilio's only metric for both calls and text is "Voice", please add more granular metadata.A workaround would be to use tags however these aren't available to Lite customers and these customers are then stuck and cannot access more granular data.
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