Role-based dashboard suite: Built Daily/Weekly/Monthly views for GMV, Revenue, Payments, AOV, Transactions, Statuses, and conversion.

SPICE acceleration: Modeled and loaded data into the in-memory SPICE engine for fast, interactive exploration.

ML-powered analytics: Enabled built-in anomaly detection, forecasting, and auto-generated narratives.

Self-service NLQ: Activated natural-language queries so business teams could ask questions directly.

Data validation & metric parity: Structured verification to ensure complex calculated fields matched legacy definitions.

Adoption & enablement: Phased pilot with power users, organization-specific documentation, and recorded trainings.

Performance governance: Established baselines, monitoring, and SPICE-capacity management to keep dashboards responsive.

Faster delivery: Report development time dropped from 2–3 weeks (Looker) to 3–5 days (QuickSight) (~70% faster).

Snappier dashboards: Load times improved from 5–7s to 2–3s, boosting usability and adoption.

Lower support effort: Ongoing effort reduced from 20 hrs/month to 8 hrs/month (60% reduction).

Higher adoption: Active business users increased from ~40% to ~75% thanks to NLQ and simpler workflows.

Built-in ML value: Anomaly detection, forecasting, and narratives delivered out-of-the-box—no external tools required.

TCO savings: Three-year total fell from $336,000 (Looker) to $167,600 (QuickSight)—$168,400 saved (~50%), with ~40% lower licensing and 60% lower ops costs.

ROI & payback: >300% ROI in Year 1, payback in <3 months, and ~$56,000/year in ongoing licensing and labor savings.