Pillar
The head page for each topic Claravine covers — marketing data standards, taxonomy, measurement and AI readiness — in depth.
The Latest
Reduce Marketing Waste: What's Actually Recoverable
Most marketing-waste advice targets media decisions. A large share of what gets counted as waste is untracked spend — a measurement problem, not a media one.
CRM Data Integrity: How to Audit It, and What the CRM Cannot Fix
CRM data integrity means records that are complete, consistent and trustworthy. Here's how to audit it — and which problems arrive already made.
Data Clean Rooms: What They Solve, and What They Assume
A data clean room lets two parties analyze combined data without exposing records. It also assumes both sides describe the same things the same way.
AI-Ready Marketing Data: What It Actually Requires
AI-ready data is usually defined for enterprise data teams. Marketing's readiness problem is different — and it is not solved by a better pipeline.
Ad Trafficking: What It Is, and Why It Decides Your Reporting
Ad trafficking is the process of getting creative live in an ad server. It is also where the tracking data every report depends on gets created.
SaaS Sprawl: The Data Cost Nobody Counts
SaaS sprawl is usually measured in wasted licenses and security risk. There's a third cost — every new tool is another place your data gets named differently.
The Marketing Process: Where It Breaks, and How to Optimize It
The marketing process moves work from plan to execution to review. Here's the sequence, the handoffs where it breaks, and what optimization actually changes.
Digital Operations in Marketing: What the Function Owns
Digital operations keeps marketing's systems, data and workflows running. Here's what the function owns and how it differs from IT ops.
Data Management: What It Covers, and Where Marketing Data Sits
Data management covers how data is created, stored, integrated, governed and used. Here's the discipline — and the part marketing actually controls.
Campaign Operations: What the Function Owns
Campaign operations runs the execution layer of marketing — build, tag, launch, QA. Here's what it owns, and why its data outlives the campaign.
First-Party Data Strategy: Collecting It Is the Easy Part
A first-party data strategy covers what you collect, with what consent, and to what end. Here's the step most guides skip — making it usable once you have it.
Disparate Data Sources: Why Connecting Them Is Not Combining Them
Disparate data sources hold related data in incompatible forms. Integration gives you access — here's what still has to be agreed before you can combine them.
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