MARKETING
Flag Newsletter Cohorts With Decaying Open Rates
Each week, scans newsletter open-rate trends per signup cohort in BigQuery, flags cohorts whose rolling open rate has dropped below a churn-risk threshold.
How it runs
The automated pipeline, trigger to output.
- TriggerWeekly schedule after sends are logged
- ActionQuery open/send counts per cohortBigQuery
- LogicCompute rolling open rate and drop vs baseline
- LogicFilter to cohorts below decay threshold
- ActionUpsert flagged cohorts to Airtable watchlistAirtable
- OutputLive re-engagement queue in AirtableAirtable
What it does
This workflow turns raw email-engagement data into a ranked at-risk list. It queries BigQuery for per-cohort open rates across the last several sends, compares each cohort's recent rolling average against its own baseline, and surfaces the cohorts whose engagement is sliding before they fully disengage. The result lands in an Airtable watchlist so the lifecycle team has a single, current view of who to win back.
When to use it
Use it when your newsletter list is large enough that aggregate open rate hides cohort-level rot — a recent signup batch going cold while older readers stay steady. Run it on a weekly cadence aligned to your send schedule so flags arrive before a cohort is unrecoverable.
How it works
- 1A weekly schedule fires the run after the week's sends are logged.
- 2BigQuery returns open counts and send counts grouped by signup cohort and send date.
- 3A logic step computes each cohort's rolling open rate and the percentage drop from its baseline.
- 4A filter keeps only cohorts below the decay threshold you set.
- 5Flagged cohorts are upserted into an Airtable watchlist with their current rate and drop magnitude.
- 6The Airtable table becomes the team's live re-engagement queue.
Set it up
What you configure once, before turning it on.
- 1Connect BigQueryDatasets, queries, schemas.
- 2Connect AirtableBases, tables, views, automations.
- 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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This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
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