OTHER

Build a quarterly churn-risk board report from health data

Each quarter this aggregates NPS trends, health-score movement, and saved-vs-churned outcomes from Snowflake, has an agent write a narrative analysis.

CategoryOther
EngineSim + Paperclip
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerFirst business day of the quarter schedule
  • ActionAggregate NPS trend, band transitions, save/churn outcomes (Snowflake)SnowflakeSnowflake
  • LogicCompute headline metrics and top churn drivers
  • ActionWrite board-ready narrative analysis (Paperclip agent)
  • ActionPublish formatted report to NotionNotionNotion
  • OutputPost report link to leadership SlackSlack

What it does

Replaces the manual end-of-quarter churn deck with a generated report. It rolls up the quarter's NPS trajectory, how many accounts moved between health bands, and which at-risk accounts were saved versus lost, then writes the narrative a board actually reads.

When to use it

Use it at quarter close when leadership needs a defensible churn-risk story backed by data, not vibes. Best for a CS or RevOps lead who currently hand-assembles this in slides each quarter.

How it works

  1. 1A scheduled trigger fires on the first business day of each quarter.
  2. 2An action step pulls the quarter's NPS trend, health-band transitions, and save/churn outcomes from Snowflake.
  3. 3A logic step computes the headline metrics — net health movement, save rate, top churn drivers.
  4. 4A Paperclip agent writes the narrative: what changed, why, and what to fix, citing the figures.
  5. 5An action step publishes the formatted report as a Notion page in the leadership space.
  6. 6The output posts a Slack note linking the new report so the board knows it is ready.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SnowflakeWarehouses, queries, shares.
  2. 2
    Connect NotionPages, databases, comments.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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