FINANCE

Quarter-Close Deferred Revenue Cohort Variance Notion Brief

At quarter close, queries BigQuery for deferred revenue roll-forward by booking cohort, has OpenAI explain timing shifts in burn-down vs. plan.

CategoryFinance
Enginesim
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerQuarter-end close schedule fires
  • ActionQuery deferred revenue roll-forward by cohortGoogle BigQueryBigQuery
  • LogicCompare burn-down to plan, tag shifts
  • ActionDraft cohort narrativeOpenAI
  • OutputPublish brief to Notion close pageNotionNotion

What it does

Builds a quarter-close deferred revenue brief organized by booking cohort. It shows the deferred balance roll-forward (opening, additions, recognized, closing) per cohort and explains where recognition is burning down faster or slower than the original schedule implied.

When to use it

Run it at quarter-end when the controller and FP&A need a cohort view to defend the deferred balance and explain timing-driven swings to auditors or the board.

How it works

  1. 1A quarter-end schedule starts the workflow.
  2. 2BigQuery returns the deferred revenue roll-forward grouped by booking cohort and product line.
  3. 3A logic step compares each cohort's actual burn-down against its planned schedule and tags accelerations and deferrals.
  4. 4OpenAI drafts a narrative: which cohorts drove the closing balance and why timing diverged.
  5. 5The structured brief, with the roll-forward table, is published to the controller's Notion close page.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect BigQueryDatasets, queries, schemas.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect NotionPages, databases, comments.
  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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