AI Dashboards Analytics
Build a single source of truth for executives and teams—KPI suites,ROAS dashboards, forecasting & anomaly detection, plus experimentation frameworks that prove incrementality. Many organizations now rely on AI Dashboards Analytics to unify reporting and accelerate decision-making.
- Connect GA4, ads, CRM, and warehouse data using AI Dashboards Analytics
- North‑star metrics with owners and definitions
MMM and A/B/geo holdout to prove lift powered by AI Dashboards Analytics
Buyer Personas
- C‑level (CEO/COO/CMO): growth, profitability
- Marketing & Growth: ROAS/CPA, funnel, cohorts
- RevOps & Ops: SLAs, throughput, retention
North‑Star KPIs
- ARR, MRR, CAC, LTV, Payback
- ROAS, CPA, CTR, CVR
- Activation, Retention, Expansion, Churn
Measurement Framework
- Metric definitions, owners, and taxonomies informed by AI Dashboards Analytics
- Experiment design (A/B, MVT, geo holdout)
- Dashboards + alerts + weekly reviews
Common Problems
- Fragmented reporting and conflicting numbers
- No clear owners or definitions for KPIs
- Slow manual spreadsheets and stale data
- No way to prove incrementality
Our AI Solutions
- Warehouse‑native models (ELT/ETL) + dbt style transforms
- Canonical KPIs with versioned definitions
- Executive dashboards (Looker Studio/embedded)
MMM + experiments for causal impact enhanced by AI Dashboards & Analytics
Use Cases
Executive KPI Suite
Company‑wide KPIs with drill‑downs and ownership.
ROAS & Creative Breakdown
Channel and creative performance with MMM/experiments.
Sales & Funnel
Leads→MQL→SQL, pipeline velocity, and revenue impact.
Product & Retention
Cohorts, activation, churn risk, and expansion alerts.
Finance & Ops
ARR/MRR, cashflow, SLAs, throughput, and AHT.
Anomaly Detection
Proactive alerts on significant metric shifts.
Data Sources & Integrations
GA4 / Search Console
Meta / Google / TikTok / LinkedIn Ads
Shopify / WooCommerce
HubSpot / Salesforce
Zendesk / Intercom / Freshdesk
BigQuery / Postgres / MySQL
dbt / Looker Studio
OpenAI / Vertex (forecasts)
We integrate via APIs, connectors, and ELT tools; dashboards ship with ownership and alerting.
Experiments
- A/B and multivariate tests with clear hypotheses
- Geo holdout and pre/post designs
- Lift calculations and decision criteria
MMM & Attribution
- Budget allocation and saturation effects
- Channel synergy and diminishing returns
- Scenario planning for “what‑ifs”
Security & Access
- RBAC and least‑privilege data access
- PII handling and audit logs
- Version control for metrics and models
Delivery
- Looker Studio reports + embedded dashboards
- Weekly reviews and enablement sessions
- Runbooks, SLAs, and warranty window
Implementation Timeline
| Phase | Duration | Deliverables | Owner |
|---|---|---|---|
|
Discover |
3–5 days |
KPIs, taxonomy, sources |
DGS + client |
|
Design |
1 week |
Models, dashboards, alerts |
DGS |
|
Build |
1–3 weeks |
ELT/ETL + visualizations |
DGS |
|
Launch |
2–5 days |
Pilot, QA, enablement |
DGS + client |
Packages & Timelines
Growth
4–6 weeks
- 3–5 dashboards
- 2–3 integrations
- Alerts & governance
- 2 revisions
Scale
Custom
- Attribution/MMM
- Embedded analytics
- Custom models
- Custom revisions
Case Studies
What leaders say
“We finally trust our numbers—weekly reviews are crisp and aligned.”
— COO, B2B SaaS
“MMM plus creative breakdowns changed budget conversations.”
— CMO, DTC Brand
FAQ
Yes—GA4, ads, CRM, shops, helpdesk, and warehouses via APIs.
Role‑based access, masked fields, retention rules, and logs.
Enablement sessions, runbooks, and QBR templates.
Yes—secure embeds with RBAC and tokenized access.
SLOs for refresh, monitoring, and alerts on failures.
You own models, transformations, and dashboards.