CHATBOTS
Daily voice IVR deflection scorecard to Slack
Runs on a schedule to read the prior day's logged voice calls from Postgres, compute deflection rate, top intents, and escalation reasons.
How it runs
The automated pipeline, trigger to output.
- TriggerDaily schedule fires for prior-day window
- ActionQuery prior-day calls from PostgresPostgres
- LogicAggregate deflection rate, intents, escalations
- OutputPost scorecard to support Slack channelSlack
What it does
Gives support leaders a daily pulse on the voice agent without opening a dashboard. It rolls up yesterday's transcripts into a single scorecard: how many calls the bot deflected, what people asked about, and why calls escalated.
When to use it
Use it once your IVR deflection flows are logging transcripts to Postgres and you want a recurring readout. It pairs naturally with the deflection and handoff templates that write the underlying rows.
How it works
- 1A scheduled trigger fires each morning for the prior day's window.
- 2The flow queries Postgres for all calls in that window with their resolution flags and intents.
- 3A logic step aggregates deflection rate, top FAQ intents, and the most common escalation reasons.
- 4The results are formatted into a readable scorecard message.
- 5The scorecard is posted to the support leadership Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect SlackChannels, DMs, threads, mentions.
- 3Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 4Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 5Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run this workflow in your colony.
14-day trial. No DevOps. No Sales call. Provisioned in under a minute.