Marketing and revenue teams that need reliable campaign, funnel, and customer reporting
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Marketing Analytics & BI
Campaign measurement, executive dashboards, customer analytics, metrics layers, and Custom BI views grounded in operating records.
Engagement shape
A focused analytics build that turns marketing and customer data into trusted metrics, dashboards, and operating views.
Typical timeline
Typically 3-6 weeks depending on source access, attribution complexity, and dashboard scope.
Who it is for
Designed for teams with a concrete operating problem.
Executives who need clear operating dashboards tied to business records
Teams whose BI stack exists but does not yet produce decision-grade measurement
Deliverables
Concrete artifacts, not vague advisory output.
Measurement model for campaigns, funnels, channels, and customer cohorts
Dashboard, Custom BI, or analytics-site implementation with documented metric definitions
Recommendations for data capture, source cleanup, and ongoing reporting ownership
Outcomes
What this work should leave behind.
Measurement models for campaign, funnel, and customer performance
We keep the deliverable tied to operating use: records people can own, workflows people can inspect, and technical contracts agents can use safely.
Dashboards, Custom BI views, and metrics layers for decision-grade reporting
We keep the deliverable tied to operating use: records people can own, workflows people can inspect, and technical contracts agents can use safely.
Analytics foundations that connect marketing signals to business records
We keep the deliverable tied to operating use: records people can own, workflows people can inspect, and technical contracts agents can use safely.
Related Lab Notes
Relevant thinking from the platform work.
AI-ready data foundations
Connect warehouses, metrics, and operational records so AI agents and operators can use trustworthy business context.
Marketing analytics that operators can use
How useful marketing analytics connects campaign signals to customer records, follow-up work, segmentation, and business decisions.
BI needs a clear metrics contract
Why BI dashboards need metric definitions, ownership, source assumptions, and governance before teams can trust reporting.
Custom analytics should create operating leverage
Custom analytics is most valuable when it changes a decision, workflow, segment, or follow-up path.
Slab5 beta
Give your business workflows a governed operating layer.
Start with one real operating flow: records, REST APIs, MCP access where enabled, AgentGrid approvals, audit logs, and the context business operators need to trust the work.