Weekly coaching reviews for every Dixa support agent

By General Input

Every Monday we review a sample of last week's closed conversations, DM each agent private feedback, and log scores to a shared scorecard.

Integrations

  • Dixa
  • Google Sheets
  • Slack Bot

Type

Agentic Task

Categories

  • Customer Support
  • Operations

Every Monday at 8am, run a support quality review that coaches my Dixa agents instead of just reporting numbers about them.

Start by using the Dixa "Search conversations with filters" operation to pull every conversation that was closed in the last 7 days. Then use the Dixa "List teams" operation, and "List team members" for each team, to build a lookup of who handled what, including each agent's name and email address.

Group the closed conversations by the agent who handled them. Skip any agent with fewer than three closed conversations that week rather than scoring them on a thin sample. For every remaining agent, take a fixed sample of their conversations, five by default, spread across the week rather than all from a single day.

For each sampled conversation, read the full thread with the Dixa "List messages" operation and pull the customer's score with the Dixa "List ratings for a conversation" operation. Ratings are fetched one conversation at a time, so pace the requests to stay inside Dixa's limit of 10 requests per second. The per-agent sample cap is what keeps the total volume manageable, so do not remove it.

Score every sampled conversation against a plain quality rubric: greeting and tone, whether the customer's actual question was answered, resolution clarity, whether next steps were set, and whether the reply matched the urgency of the issue. Score each of the five on a 1 to 5 scale and write a one-line note explaining the score. For each agent, identify their single strongest and single weakest reply across the sample and capture each one as a verbatim quote, so the feedback is anchored in their own words rather than in a generalization.

Log one row per reviewed conversation to my Google Sheets QA scorecard using the "Append Values" operation. Each row should carry the review date, the agent name, the conversation id, the five rubric scores, the satisfaction rating, and the one-line note. Always append rather than overwrite, so quality trends build up week over week and I can compare an agent against their own past weeks.

Then coach privately. For each reviewed agent, take their Dixa email address and use the Slack Bot "Look Up User by Email" operation to find their Slack account, "Open a Conversation" to open a direct message with them, and "Send a Message" to deliver their personal review. Each message should give two specific things they did well and one concrete thing to change this week, including the verbatim quotes from their strongest and weakest reply. Keep the tone supportive and specific, never generic praise, and tie every comment to something they actually wrote.

Finally, post a short team-level roll-up to my support leads channel using the Slack Bot "Send a Message" operation. Cover the common misses across the whole sample and what the team should focus on this week. Do not name individual agents or their scores in the public channel. Individual feedback stays in direct messages, and the channel post stays at the level of themes and patterns.

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