Thoughts and rants from a veteran Martech contractor and interviews with my peers.

A little lift never hurt anyone

Hightouch, Zeotap and mParticle now sell a toggle that lifts your match rate with identifiers you never collected. The gain is real. The work is the consent check nobody does before flipping it. What it does, and what to look at first.

You spend a week defining an audience in your CDP. Lapsed high-value customers, the ones actually worth winning back. You push the segment to Meta feeling good about it. Then the matched figure comes back at around sixty percent of what you sent, and the rest just isn't there. The platform couldn't recognise four in ten of your own customers.

Anyone who has run paid media knows that feeling. It's the match rate gap, and it has a few causes. People sign up with one email and log into Meta with another. Phones get replaced every

composable cdp

The CDP you weren't supposed to buy

Hightouch said the packaged CDP was dead weight. Four years on, Gartner lists it in the CDP Magic Quadrant. The architecture was right. The pitch skipped a step.

In 2022, Hightouch published a piece with a headline built to draw attention: Friends Don't Let Friends Buy a CDP. I remember where I first saw it, neck deep in my client's packaged CDP project. Sure, it was vendor content. Everyone knew it was vendor content. Nevertheless, it got passed around, because the frustration underneath it was real, and most of us had heard it, or even felt it.

The argument was simple enough to fit on a t-shirt. Your data already lives in the warehouse. Why pay a second vendor to copy it into a separate

The Context Audit

A follow-up to the follow-up. My last piece explaining "what the context layers has to do" argued that customer state has to be Queryable, Addressable, Current, and Accountable if agents are going to act on it in real time. It ended pointing at a one-page audit and stopped there.

This is that audit.

The context layer's job is to make the customer state usable when an agent needs to act on it. Whether it's doing that job is not a question anyone can answer from an architecture diagram. Architecture diagrams describe

Contextual CDPs

What does the context layer actually have to do?

Queryable, addressable, current, accountable. Four things the layer of customer state has to deliver if AI agents are going to act on it in real time. A follow-up to the six-part Contextual CDPs series, written a year on, now that the industry has caught up to the language.

A follow-up to the six-part Contextual CDPs series.

A year ago, I published a six-part series on contextual CDPs. It started with MCPs reframing the CDP as a dynamic context engine, then memory as the orchestration layer, then trust as the interface when systems start to infer and decide, then the practical bridge between today's stack and an agent-driven future, then composability that needs sequence and scaffolding rather than more connectors, and finally contextual fluency as a human skill rather than a technical one.

I thought I was making an argument that needed defending at

Martech Events

Plotting my course to AntiCon

At AntiCon 2026 in London, three questions I want answered: trust-ladder criteria, real organizational redesign vs. relabelled roles, and the possible next-era framing.

AntiCon lands in London on May 21 and I'm registered for the full main-stage track on day one. Looking at what I've signed up for, the route through the day is revealing... in hindsight. Behavioral science as the human advantage, and as a former data analyst, I am looking forward to this one. The three levers of marketing transformation. Redesigning the marketing organization for an AI era. Architecting the agentic operating model. Co-pilot or autopilot. Are you prepared for the next Martech eras. Conviction at scale.

A bunch of different titles, with vastly different speakers, but

Vibe Coding Martech

The iceberg under the demo

An investor's AI contest landed in my inbox the same week the UK government published an open letter to business leaders about AI cyber threats. Read together, they describe the same reality from opposite ends. And they leave a gap most boards aren't going to notice in time.

Last week two things crossed my ~~desk~~ screen that, on the face of it, had nothing to do with each other.

The first was an email from an investor running an internal AI contest across six of their portfolio companies, one of which I used to work with. The framing was good, and I was happy to see this development. They were asking employees (and somehow former contractors like me) to record a two-minute screen capture of an AI workflow they'd started using. A 15-minute task done faster. A draft response written in half the time. You

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