MARKETING
Hourly spam-complaint rate watchdog
On a schedule, queries your spam-complaint table for the last hour, flags any sending domain over the 0.1% complaint threshold.
How it runs
The automated pipeline, trigger to output.
- TriggerHourly schedule fires
- ActionQuery complaints and deliveries by domainPostgres
- LogicAny domain over the 0.1% complaint rate?
- ActionOpen PagerDuty incident for breaching domainPagerDuty
- OutputAppend incident row to Airtable logAirtable
What it does
Every hour it tallies spam complaints per sending domain against messages delivered, and escalates the instant any domain breaches the inbox-provider complaint threshold (0.1%). Crossing that line is what gets you throttled or blocked at Gmail and Outlook, so it treats it as a page-worthy incident.
When to use it
Use it when you send from multiple domains or subdomains and need per-domain accountability. Ideal for teams running cold outreach, transactional, and marketing streams side by side where one stream's complaints can sink the others.
How it works
- 1A schedule fires every hour.
- 2The flow queries Postgres for complaints and deliveries grouped by sending domain over the last 60 minutes.
- 3It computes each domain's complaint rate and filters to those above 0.1%.
- 4If none breach, it exits quietly. If any do, it opens a PagerDuty incident with the domain and rate so on-call gets paged.
- 5It appends a row to an Airtable incident log capturing the domain, rate, sample size, and timestamp for the postmortem trail.
Set it up
What you configure once, before turning it on.
- 1Connect PostgresAny Postgres URL — query, write, migrate.
- 2Connect PagerDutyIncidents, on-call, escalations.
- 3Connect AirtableBases, tables, views, automations.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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