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FloKit reporting answers three questions every growth team needs to answer weekly: Which cohorts are paying back? Which actions improved or harmed retained value? What should we approve next? Every report view is available in the dashboard, via the API, and exportable to CSV. For warehouse-backed analytics tools, FloKit supports direct export to BigQuery and CSV-compatible formats for Looker Studio, Tableau, and Metabase.

Core report views

1. Payback report

CAC, ROAS, payback curves, and projected LTV by cohort. The primary report for evaluating acquisition quality across campaigns, channels, and markets. See Payback reports for full documentation.

2. Action outcomes

Tracks the performance impact of approved actions — which moved metrics in the right direction, which regressed, and which were rolled back. Each completed or rolled-back action shows:
  • Pre-action baseline (CAC, ROAS, trial conversion).
  • Post-action delta.
  • Whether the outcome was within the predicted range.
  • Rollback reason, if applicable.
Use action outcomes to calibrate trust in FloKit’s recommendations over time. If budget_shift actions are consistently outperforming predictions, that’s a signal to relax the confidence threshold or increase the spend cap. If a category of action is underperforming, restrict it in guardrails until you investigate.

3. Creative performance

Trial conversion rate and 90-day LTV by creative ID. This report is intentionally separate from your ad platform’s creative report — it shows subscription quality metrics that platform dashboards don’t surface. Creatives are ranked by conversion-weighted LTV, not by CTR or install volume.

4. Offer analysis

Trial conversion rate, plan mix (monthly vs annual), and renewal rate by offer and paywall variant. Use this report to understand which combinations of offer and paywall produce the best subscription economics — before running a formal A/B test.

5. Integration health

Data freshness, event volume, identity join rate, and any sync errors across your connected integrations. Check this report if a payback report looks stale or if action recommendations have slowed. Key indicators:
  • Event lag — time since last event received from each source.
  • Identity join rate — percentage of subscription events successfully matched to an attributed install.
  • Event volume — daily event counts vs 7-day average (spike or drop may indicate an integration issue).

Weekly growth review cadence

A consistent weekly review cycle is the most effective way to use FloKit. Each review session should cover four areas, in order:
1

Review the payback report

Flag cohorts with improving or declining payback compared to the prior week. Note any channel, country, or creative that has moved more than 10% in either direction. These become the inputs for action queue review.
2

Review the action queue

Go through actions in ready_for_approval state. Approve, reject, or defer each one. For deferred actions, add a note explaining why — this context is useful when the action re-surfaces.
3

Check action outcomes

Review actions that moved to running or completed in the past week. Compare actual impact to predicted impact. Note any actions approaching rollback trigger thresholds.
4

Review guardrail triggers

Check whether any guardrails fired in the past week. If the same guardrail is repeatedly blocking actions that your team would approve manually, the threshold may need adjustment. If guardrails are rarely triggering, that may indicate the confidence threshold is too permissive.

Exporting reports

CSV export is available from any report view. Click Export in the top-right corner of the report. The export includes all rows and columns at the current filter and grouping settings. API access:
See API reference → Reports for query parameters, pagination, and response schema.

Custom dashboards

FloKit’s export API supports integration with:
  • Looker Studio — via CSV connector or BigQuery export.
  • Tableau — via CSV or direct BigQuery connection.
  • Metabase — via CSV or BigQuery data source.
For warehouse export configuration — pushing FloKit-computed payback metrics back to your BigQuery or Snowflake instance — contact the FloKit team. This is available for workspaces with a warehouse integration already connected.