Marketing and Experience
AI agents in marketing stopped being the exception: most martech teams already pilot or use one. What holds companies back is the team and data's real readiness to make use of it, not a lack of tooling.
- Personalization built on real customer data, not generic segments
- AI tools judged by results, not by the vendor's promise
- Data and team readiness before committing to scale
Martech right now
81%
of martech leaders already pilot or use AI agents in their operations.
45%
of martech leaders with AI agents in pilot or production say the vendor-offered capability doesn't meet promised business performance.
40%
of martech leaders report having the full readiness (team, technical, and data foundations) needed to run AI agents at scale.
Source: Gartner, survey of 413 martech leaders, October 2025.
From a martech tool to an experience that actually converts.
Customer data organized before the personalization promise
We assess whether your current data foundation supports the personalization promised, before recommending any martech platform.
Let's talkAI agents judged by results, not by the vendor's demo
We test the tool against a defined business goal, not against the vendor's sales pitch.
Let's talkScale only once the team and data are ready for it
We avoid committing budget to scale before confirming the data foundation and team can sustain the promised volume.
Let's talkWhat we're writing about marketing and experience.
Brand experience starts before the purchase
Chatbots that solve nothing: how to avoid them
Customer service as a retention channel, not just support
Customer service as part of the brand experience
Customer service metrics leadership should actually review
Customer service personalization without surveillance
Next step
Want to know if your data foundation supports the personalization you promise customers?
We diagnose this before recommending any martech tool. If the foundation isn't ready yet, we'll tell you that too.
Talk to a specialist