Key Activities
- Online user behavior tracking and analysis
- KPI dashboards across all 9 pillars
- ROAS measurement and media mix modeling
- Personalization via cohort segmentation
- Recommendation engine performance management
- Channel attribution modeling
- Real-time and predictive modeling
- A/B test and experimentation program governance
Build a process where your data scientists are providing insights, not just generating reports. A good data scientist will pay for their salary in a month by implementing their insights.
KPIs
- All pillar KPIs (roll-up): Site Traffic, AOV, Conversion Rate
- Cohort performance and retention trends
- Acquisition and conversion funnel drop-off by stage
- Revenue per visitor (RPV)
- Customer Lifetime Value (LTV) by cohort
- Predictive LTV accuracy (model vs. actuals)
- Attribution model variance (first-click vs. last-click vs. data-driven)
- Dashboard adoption rate (% of team actively using BI tools)
- Data freshness / pipeline latency SLA
- New vs. returning visitor conversion rate split
Current Best-in-Class Tools
Web Analytics
GA4
Event-based analytics with BigQuery export, predictive audiences, and purchase journey funnel reporting built in.
Web Analytics (Enterprise)
Adobe Analytics
Deep segmentation and pathing analysis. Best when paired with AEM and Target in the Adobe Experience Cloud.
Business Intelligence
Looker / Tableau
Self-service BI with live data warehouse connections. Best for pillar-level leadership dashboards.
Business Intelligence
Power BI
Microsoft-native BI — strongest when your org is already in the Microsoft 365 / Azure ecosystem.
CDP / Segmentation
Segment (Twilio)
Collect, unify, and activate behavioral data across all tools from a single customer data platform.
Personalization / CDP
Bloomreach
CDP plus personalization plus search in one platform. Strong mid-market and enterprise eCommerce fit.
Attribution
Triple Whale / Northbeam
Post-iOS 14 multi-touch attribution built for DTC. Gives true channel-level ROAS without pixel dependency.
Attribution (Enterprise)
Rockerbox
Cross-channel attribution with media mix modeling for larger ad budgets and multi-brand organizations.
Data Warehouse
BigQuery / Snowflake
Cloud data warehouses that serve as the single source of truth for all pillar-level reporting and ML models.
Data Pipeline
Fivetran / dbt
Automated data ingestion and transformation from every eCommerce platform and marketing system.
Media Mix Modeling: Real-Time Predictive Spend
Traditional MMM was a quarterly report from an agency. These platforms have killed that model — making spend optimization continuous, real-time, and self-serve. The question shifts from 'where did our money go?' to 'where should our money go next week?'
What Real-Time MMM Does
Media Mix Modeling ingests your spend data across every channel — paid search, social, email, display, affiliate, TV — and uses statistical modeling to isolate the true incremental contribution of each. Unlike last-click attribution, it accounts for lag effects, saturation curves, and diminishing returns. Real-time platforms update these models continuously (daily or weekly) and surface actionable spend recommendations: increase budget here, pull back there, this channel is saturated at current spend levels.
The most valuable output is not what worked last month — it's the spend scenario planner that tells you what your ROAS will look like if you shift $50K from Meta to Google next week before you do it.
MMM (Real-Time / DTC)
Prescient AI
AI-native MMM built specifically for DTC eCommerce. Continuous model updates with real-time spend recommendations and scenario planning. No data scientist required to operate.
MMM (Bayesian / Self-Serve)
Recast
Bayesian MMM with 'what if' budget allocation scenarios updated weekly. Surfaces diminishing returns by channel and recommends optimal spend distribution.
MMM + Attribution
Northbeam
Multi-touch attribution layer plus scenario modeling for spend reallocation. Bridges the gap between pixel-based attribution and full MMM.
Incrementality + MMM
Measured
Incrementality testing platform that validates true channel lift. Pairs with MMM outputs to confirm recommendations before budget shifts.
MMM (Open Source)
Meridian by Google
Google's Bayesian MMM framework released in 2024. Open source, fast adoption among data-mature teams. Requires in-house data science to operationalize.
MMM (Enterprise)
Analytic Partners
Enterprise-grade MMM with real-time dashboards and scenario planning. Used by large retail and CPG brands. Full-service with analyst support.
MMM (Open Source)
Robyn by Meta
Meta's open-source MMM with automated hyperparameter optimization. Strong community adoption. Requires data science resources to run and interpret.
MMM + Attribution
Rockerbox
Cross-channel attribution with media mix modeling for multi-brand and larger budget environments. Bridges MTA and MMM in a single platform.