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Analytics & Dashboards — One Truth, Faster Decisions

Governance Outcome:
  • One truth for HCP & DTC.
 I design the KPI layer and build Looker/Tableau/Power BI dashboards that stitch paid + owned (and approved 3rd-party) data—so leaders decide faster, regions roll up cleanly, and agencies optimize to the same metrics.

Who this helps

  • (at a glance)
  • C-Suite (CEO/CFO/CMO) — real-time executive tiles and mobile snapshots; at-a-glance ROMI, pacing, and risk alerts.
  • Marketing Directors / Leads — budget clarity, faster scale/pause calls, consistent ROI readouts.
  • Web Portal Product Owners — stable schema, defensible consent, fewer data exceptions.
  • Agencies / Vendors / Finance — shared KPIs, pacing alerts, clean reconciliation.

Proof / Mini-KPIs

≥90%

on-time decision cycles

−35%

data discrepancies

Weekly

exec one-pagers shipped

What you get

  • (ready to use)
  • Governed KPI Layer & Metric Dictionary — clear definitions, owners, calc logic (the one truth)
  • Real-Time Executive Reports (C-Suite Command Center) — live tiles for ROMI, revenue/pipeline, regional pacing; exception alerts; mobile snapshot
  • Executive Dashboard — weekly Decision One-Pager (what changed → so what → now what)
  • Brand & Channel Ops Dashboards — HCP/DTC journeys, creative/claim performance, pacing & ROI
  • Compliance & Privacy View — consent coverage, event quality, audit log summaries
  • Paid/Owned Stitching — governed UTMs, GA4 events/params, ad platform joins, server-side where appropriate
  • Model-Ready Exports (MMM/MTA) — daily grain, stable campaign/region keys, governed fields
  • Adoption Program — training, office hours, dashboard guardrails, usage tracking

Problems solved

  • Three decks, three numbers
  • UTM drift/GA4 gaps → “(other)” and missing conversions
  • Pretty dashboards that don’t change decisions (no KPI layer, slow refresh)
  • Static, out-of-date agency metrics that mask reality
  • No reliable way to measure vendor /agency /partner ROI—we centralize trustworthy analytics so you can see and compare performance and reallocate spend in real time

My approach

  • (people • process • data • tech)
  • People: metric owners, escalation paths, adoption goals, breaking departmental silos of shared data
  • Process: weekly Decision Readout · monthly Allocation Review · QBR scorecards
  • Data: governed UTMs/events, consent logic, stitching keys, QA monitors
  • Tech: GA4/Tag Manager · Looker/Tableau/Power BI · BigQuery/Snowflake · CM360/SA360, Meta/LinkedIn/TikTok, DV360/TTD · ESP/CRM (SFMC, Braze)

Reporting platforms

  • (at a glance)
Looker Studio
  • (Google)

Best for

Rapid prototypes, stakeholder-friendly scorecards, SEO/paid media rollups.

Strengths

Fast to stand up, great for shareable links and embed; native BigQuery fit.

Notes

Use for exec snapshots and cross-channel scorecards; graduate heavy models to BI.

Power BI
  • (Microsoft)

Best for

Enterprise governance on Microsoft stacks; Finance ops and ROI reconciliations.

Strengths

Row-level security, semantic models, Power Automate; strong M365 adoption.

Notes

Ideal when source data sits in Fabric /Dataverse/Synapse; great for C-suite tiles + ops views.

Tableau

Best for

Visual exploration by Brand/Analytics teams; complex HCP/DTC journey storytelling.

Strengths

Rich viz library, parameter controls, strong Snowflake/Redshift/SAP connectors.

Notes

Use for deep-dive brand and regional analysis; keep certified data sources in the catalog.

Teaming & data flow

  • (lakehouse → clean room → dashboards)

Source & land

Paid (ad platforms, POC, programmatic) + owned (web/CRM/ESP) + approved third-parties land in the lakehouse (BigQuery / Snowflake /Fabric).

Govern & model

Apply UTM/event standards, identity keys, consent logic. Build the KPI layer and semantic models shared by all BI tools.

Privacy-safe joins

Use clean rooms (e.g., Snowflake Native, AWS Clean Rooms, BigQuery DCR) to match with outcomes/partner data without sharing PII.

Certify & serve

Publish certified views for each audience (C-suite, Brand, Ops, Compliance). Enforce row-level security, refresh SLAs, and QA monitors.

Visualize & adopt

Expose the same governed layer in Looker Studio, Power BI, and Tableau, so every team sees one truth—with role-based tiles, alerts, and a weekly Decision One-Pager.

How we work together

  • Marketing co-owns the KPI dictionary and decision cadence (readouts, allocation reviews).
  • Data/Engineering owns pipelines, models, SLAs, and clean-room policies.
  • Analytics/BI maintains certified datasets and dashboard guardrails.
  • My role: orchestrate standards, align teams, and keep the loop tight between insight → decision → reallocation.
  • Result: Real-time executive tiles for C-suite, consistent KPIs for every region/agency, and measurable vendor/partner ROI off a single governed source.

Data quality SLOs

  • (set & monitored)
  • Freshness: <24h to exec tiles (near-real-time when feasible)

  • Completeness: >95% governed UTM fill • >98% event-param coverage
  • Accuracy: ±2% vs. platforms for governed metrics (exceptions flagged)
  • Consent: ≥90% of tracked events carry a valid consent state

Engagement plan

  • Diagnose — metric audit, UTM/event gap scan, quick fixes
  • Design — KPI layer, data model, dashboard wireframes, export spec
  • Build — stitching + dashboards + monitors; pilot brand/region
  • Prove — weekly one-pager live; decisions logged; tune
  • Scale — rollout, training, usage tracking; QBR templates

Case flashes

  • (representative)

Global dashboard fabric

→ −60% reporting lag, −35% data errors, weekly reallocation adopted by brand leads

Paid/owned stitching cleanup

→ platform vs. BI variance within ±2%, ROAS lift by creative-claim cluster


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FAQs

No—measurement design first (KPI layer, data model), then dashboards, then adoption.

HIPAA/GDPR-aware patterns; consent parameters at event level; de-identified/aggregated analytics only.

Yes—stable keys/fields plus a metric dictionary aligned to modeling needs.