Martech, explained · CDP architectures · 2:00
Agentic CDP, explained
The same CDP with a new operator: the goal, the gate, and what the agent steers on
The short answer
An agentic CDP is the same CDP with a new operator. It still collects, unifies, segments and activates, but agents assemble and keep up campaigns toward a goal you write: an outcome, a measure, a deadline and a limit. Actions that matter wait at a sign-off gate, and since it steers on what you measure, you check the work.
Questions this answers
Is an agentic CDP a new kind of CDP?
No. It runs on a packaged, composable or dual zone foundation. What changes is who operates it.
What goal can an agent act on?
One with four parts: an outcome, a measure, a deadline, and a limit on what the agent may do. Most teams write the first three and leave off the limit.
What is the autonomy line?
What the agent may do alone, and what it brings back for sign-off. A tool that can only suggest is an autocomplete; a tool with no gate is a liability.
Why does identity matter more with agents?
The agent takes each customer record at face value. If one customer is three records, it moves budget on the wrong picture, with complete confidence.
Why can an agentic CDP drift from the goal?
The measure you care about, such as retention and margin, arrives every few months, so the loop steers on a fast stand-in like opens and clicks. Watch how far the two drift apart.
Transcript
Every chapter as text. Click a time to play the film from there.
0:00 Intro
An agentic CDP isn't a new kind of CDP. It's the same one, with a new operator.
0:10 Same CDP, new operator
It still collects, unifies, segments and activates. What changes is who operates it. Agents do the assembly and upkeep of a campaign, the work that used to fill your week. Underneath, it still needs a foundation: packaged, composable or dual zone.
0:28 A goal an agent can act on
You become the director. You write the goal, and a goal has four parts: an outcome, a measure, a deadline, and a limit on what the agent may do. Most teams write the first three. The limit is the one they leave off.
0:43 The autonomy line
Then you set the autonomy line: what the agent may do alone, and what it brings back for sign-off. A tool that can only suggest is an autocomplete. A tool with no gate is a liability.
0:57 It reads context
Before it acts, the agent reads who each customer is, and it takes all of it at face value. If one customer is three records, it moves budget away from the wrong channel, with complete confidence.
1:10 Steering on a stand-in
Then it acts, reads the measure, and adjusts, over and over. The measure you wrote is retention and margin, and that number arrives every few months. The loop cannot wait that long, so a stand-in steps into its place: opens and clicks, back in minutes. The loop runs. The goal is still fed, never read. Watch how far the two drift apart.
1:35 You check the work
You're still accountable for the outcome, even when you're no longer the one clicking. Bad data used to look like a broken dashboard. Now it looks like a competent answer.
1:46 See it step by step
See it step by step at Martech Stack Builder, or learn more about each piece there.
Your agentic CDP will optimize whatever you measure.
Read more
The articles this film is drawn from.