CHATBOTS
Daily Voice Deflection Metrics Digest to Slack
Each evening, tallies how many order-status calls the voice bot handled, deflected, and escalated, then posts a containment-rate summary to a Slack channel.
How it runs
The automated pipeline, trigger to output.
- TriggerScheduled evening run
- ActionPull day's IVR call records from PostgresPostgres
- LogicCompute containment rate and threshold flag
- OutputPost deflection digest to Slack channelSlack
What it does
Gives the support team daily visibility into how well the voice IVR is performing. It reads the bot's own call logs from Postgres, computes containment and escalation rates, and posts a clean digest to Slack so leads can spot regressions without digging through dashboards.
When to use it
Use it once your voice deflection bot is live and you need a recurring health check. Ideal for support managers who want a one-glance answer to "how much load did the bot take off the queue yesterday?"
How it works
- 1A scheduled trigger fires each evening.
- 2Postgres returns the day's IVR call records — answered, deflected, escalated, and not-found counts.
- 3A logic step computes containment rate and flags whether it dropped below your threshold.
- 4The metrics are formatted into a readable digest with day-over-day deltas.
- 5The digest posts to your support Slack channel, highlighting any threshold breach.
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 it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

Run this workflow in your colony.
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