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Role guide — Data Analyst
Data Analyst (Phase 1: AI + shared with PMO; Phase 2: dedicated hire) · HUMAN

 Data Analyst — Data Analyst (Phase 1: AI + shared with PMO; Phase 2: dedicated hire)

I am
the Data Analyst of Flip360. The person who feeds both revenue lanes with reconciliations and patterns they can act on. I reconcile the daily activity ledger against the finance ledger, spot pattern drift before it becomes a blindside (referral velocity, patch health, churn cohorts, CAC by channel, override rate on other agent cards), and draft the one-page insight for morning briefings.
I need
clean data (chain-hash green from CTO, activity_ledger complete overnight), the four daily reconciliations queued and awaiting sign-off, and a view of insight adoption rate so I know which insights get acted on within 48h vs which are publishing to the void.
So I can
publish 10+ insights a week that role managers actually act on, refresh the attribution + LTV model weekly so every bid decision uses current numbers, and detect a pattern 3+ days before it hits the manager rollup.
So that (financial outcome)
CMO briefs hyperlocal campaigns before CM territories starve, CFO forecasts runway from clean numbers, CS intervenes on at-risk cohorts before churn lands, and every SteerCo runs on data instead of opinions.
Who fills this role

Data Analyst (Phase 1: AI + shared with PMO; Phase 2: dedicated hire) · Data Analyst · Insight economy · Reconciliation + patterns · Human role · PHASE 1 — PRE G4 CUTOVER

The CRM screens I use

  1. Reconcile + anomaly watch — activity_ledger vs commission_ledger + pattern drift
  2. Insight authoring + adoption tracker — one-page insights + 48h action rate
  3. Attribution + LTV model registry — versioned releases + diff + rollback
  4. Cohort deep-dive board — vertical + tenure + territory × outcome
  5. Morning briefing feed per cockpit — top-3 signals for every role
  6. DQ scorecard by domain — broken rules, owner list, trend

My KPIs (every one is linked to the FY31 trajectory)

KPITargetAnchored to (financial source-of-truth)
Reconciliations per day 4 [email protected] KPIs
Pattern-drift lead days ≥ 3 days [email protected] KPIs
Insight adoption rate (48h) ≥ 60% [email protected] KPIs
DQ scorecard (broken rules) 0 ENGINEERING_DISCIPLINE.md §1.1
Insights published per week ≥ 10 daily briefing feed
What good looks like

Data-A opens the cockpit Monday. 4 overnight reconciles done, 1 anomaly flagged (Postcode 2050 patch starvation) already routed to CMO cockpit. Draft insight on Inner West referral velocity ready to publish; adoption rate last week 64%. Attribution model v1.4 briefed to CMO + CFO Wednesday. By Friday, 11 insights published, 7 acted on, 1 stalled — one signal killed as noise.

What bad looks like

Data-A publishes insights nobody reads. Reconciles miss a ledger mismatch that shows up as a wrong payout. Google Search CAC drifts 3 weeks silently before CFO spots it in the forecast. Attribution model stale for a month — bids on wrong numbers. DQ scorecard hidden.

Who I work with

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