Martech Therapy: CDP strategy and agentic AI

The Forrester Wave halo measures your reference program

Forrester's customer-feedback halo rewards the reference program as much as the customers. What the 2024 notation change added, and what it removed.

Last week the Forrester Wave for B2C customer data platforms came out, and I spent more time on the legend than on the chart. That's not where I expected to end up.

Ten companies on the graphic.

One of them, Amperity, carries a halo around its marker. Forrester's own footnote spells it out:

A halo means above-average customer feedback, and a double halo means the vendor is a Customer Favorite.

Nobody else on the chart carries a halo at all. And nobody at all carries the double, so the Customer Favorite designation went unawarded in this market.

Martech entropy

The Martech Stack you bought twice

Unused features cost nothing. A second contract for a capability you already own costs what the invoice says, and no utilization survey will find it.

Just like my previous article, and most because of the fast moving pace of Martech, I revisited some early work.

Back in July I went at whether AI closes the gap in Martec's Law, and part of that piece dealt with the Gartner utilization number. 58% of stack capability in use in 2020, 42% in 2022, 33% in 2023, with the 2025 reading climbing back toward 49% under a slightly different question. Directional rather than gospel, as I put it at the time.

I still think that's right.

What I didn't do is ask why the dead

Contextual CDPs

Which context wins when two systems disagree about your customer?

Two systems calculate lifetime value differently and nobody has said which counts. I tried to score that in my context audit and broke my own rubric.

Back in June, while writing about composable CDPs, I asked a question and then, like a distracted person, walked straight past it.

When two systems disagree about something like a customer's email opt-in status, which value wins, and is that rule written down anywhere?

I gave it one line of answer. In packaged systems the vendor sorts it out for you, in composable systems the work goes to your data team. Both true, but neither one tells you which number is right. That has bothered me on and off ever since.

Composable CDP, translated for marketers

Composable CDP

Martech contracting

Is Martech work slowing down?

Five conversations, one pattern. What actually slowed martech contract work, what AI changed, and the review problem nobody has priced.

I recently returned from my holiday without some magical Martech insight. What I did pick up was a plethora of LinkedIn posts and private messages from people who have been let go from their positions, or who are sharing their experiences of a perceived drop in Martech-related contract work.

And an announcement from my friend Daniel Heer. More about that later.

In total, a handful of conversations over the last few months, from three different parts of this industry, all describing the same thing.

I will try to tell the story, using some light-hearted references to one of

Identity Resolution

Identity Resolution: a practitioner's guide to who owns the match

Identity resolution is a set of business decisions about who counts as the same person. Five approaches, and what each one costs you in ownership.

In part 4 of the Agentic CDP series I made a claim and then moved on rather quickly.

Identity resolution stops being a data-team hygiene project and becomes a precondition for anything agentic being trusted with a budget.

That deserved more than the paragraph it got, so here is the longer version.

Your agentic CDP will optimize whatever you measure

Every agentic CDP will be sold on goals-based marketing. That assumes a goal an agent can chase and a signal fast enough to learn from. Most teams have neither.

Martech Therapy: CDP strategy and agentic AIMatthew Niederberger

Agentic CDP

Your agentic CDP will optimize whatever you measure

Every agentic CDP will be sold on goals-based marketing. That assumes a goal an agent can chase and a signal fast enough to learn from. Most teams have neither.

The last dimension on the scorecard in part 3 was goal and measurement fit.

Can the tool take the goals and the clean signal you can actually give it?

I saved it for its own part because it is the dimension the entire category rests on, and the one where the distance between the pitch and the average marketing team is widest. And it bears the roots of my entire post-military career.

Every vendor is selling you goals-based marketing

Before we jump into the deep end, let's briefly look past the architecture arguments, and you will see

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Every vendor is selling you goals-based marketing