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Connector Improvement: Zendesk user role history

Answered
Ken Hurst-Brodie User

I'd like to be able to determine whether a ticket-comment was made by a user who was an agent or admin at the time of the comment. Ticket comments currently include the user_id of the user making the comment, and each user has a role (end-user, agent or admin), but as people change roles within our organization or leave altogether, the role field on a user becomes an unreliable indicator of the status of a comment-author at the time of the comment.

Please include either a new table for the role-history of a user (e.g. a user_id, timestamp, role tuple) or a field to ticket_comment indicating the role of the user making the comment at the time of the comment.

Determining the role of a commenter helps us measure the number of agent replies, earliest agent reply, time between agent replies, etc.

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Comments

4 comments

Date Votes
  • Official comment
    Ray User

    Hi Ken,

    Thanks for writing in. I think this makes a lot of sense! I'll add this to our Zendesk backlog. We'll be sure to keep this thread updated with developments, and likewise I'll keep an eye out for upvotes and new replies.

    Best,

    Ray

  • Kevin MacFarlane User

    Hi @...!

    We need this, especially when using the DBT package that uses the user role to determinate the sla_elapsed_time. We can't create reliable SLA reports since tickets answered by ex-agents are shown as if they were never replied by an agent but the SLA was achieved, which is inconsistent.

  • Clare Goldschein User

    Kevin MacFarlane @... I'm having the same issue! Really need to be able to understand user_role histories in order to properly report on SLAs around agent replies. 

  • Nick Barclay User

    Another vote for this - it's crucial to have this information otherwise any agent-based metrics such as various reply/response times, agent touches on a ticket etc, are all invalid. It makes most metrics in the zendesk__ticket_metrics dbt model useless when looking at historical data due to staff turnover.