composable cdp - Martech Therapy (Page 2)

Is it all a magical illusion?

Rethinking the Quadrant / Part 1: Why the Magic Quadrant no longer reflects CDP reality

Gartner’s Magic Quadrant is treated like gospel in boardrooms from Dubai to Düsseldorf. A single position in that familiar matrix can nudge millions in Martech budgets from one vendor to another. The thing to keep in mind is that the Quadrant doesn’t measure what many buyers think it does. It rewards size, vision, and analyst choreography, and not necessarily real-world usability, implementation speed, or practitioner satisfaction. It reflects power structures, and rarely performance.

This first part in the Rethinking the Quadrant series takes aim at the mechanics behind those polished charts and asks a blunt question:

What kind

The evolution of Omni-Man

From debugging eVars to preaching composable gospel -> Adam Greco's 25-year journey through martech's identity crisis

I finally sat down with Adam Greco for what turned into one of those conversations that explains how we got to this beautiful disaster we call modern martech.

Adam earned the nickname "Omni-Man" back when he was basically Adobe Analytics incarnate, the guy who could fix your broken implementations and somehow make eVars seem less like a cruel joke played on marketers by bored engineers. For years, he was the poster child for mastering one platform completely.

Which makes his current crusade for composable CDPs either beautifully ironic or perfectly logical, depending on whether you've had your coffee yet.

His

Contextual CDPs: Composable, not chaotic

Part 5 of 6: Contextual CDPs need lightweight structure, not heavyweight rebuilds

By now, we’ve explored what context can unlock in a CDP, from dynamic profiling to real-time orchestration and trust. We’ve talked about layering memory and inference without blowing up your current stack. So in this fifth part, let’s look at what happens when you want to make these contextual layers stick… without making everything feel like a pile of duct-taped services.

Because that’s the risk. Composability gives us incredible flexibility, but without some architectural discipline, it becomes hard to explain, harder to maintain, and impossible to govern.

Let’s explore how to structure context-aware systems in

If the warehouse can think, what’s left for the CDP?

A critical reflection on Databricks, data gravity, and what comes next.

Nope, this isn’t an analysis of a press release. We’ve seen all Databricks partners do that generously all over LinkedIn. It’s a reflection, a personal one (I had some spare time over the weekend), on something that’s been building quietly in the background and what it means now that someone has taken a concrete step forward. That someone is Databricks.

Last week, Databricks launched something called Data Intelligence for Marketing. And sure, you could skim the headline and file it under “AI feature drop.” But that’s not what caught my attention.

What stood out was

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