Expert Advice for Marketing Leaders on MarTech, AI, & CX
Expert mode marketing technology, AI, and customer experience articles for marketers and other professionals from The Agile Brand Guide®.
When a 30-second spot carries a price tag of eight million dollars before a single celebrity is hired or camera rolls, the only metric that truly matters isn’t buzz, but business impact. Did the ad connect with the right audience? Did it reinforce the brand? And most critically, did it create a clear path to purchase uplift and long-term brand equity?
Customers might browse a website, read support articles, ask a chatbot or contact a service team directly. Sometimes they’d watch YouTube videos, check Reddit threads, ask in Facebook groups. Across those channels, the organisation still largely understood and could interject into how its products, services and policies were explained.
New Analyst Agent Hub and agent catalog introduce a collaborative Agentic workforce to help security teams investigate threats, generate detections and coordinate response
This article was written for CustomerThink by Greg Kihlström. The Medallia 2026 State of Customer Experience Report reveals a disconnect between how
brands perceive the quality of experiences they provide and the consumer
reality. While 66% of customer experience practitioners believe experience quality is on the rise, only 17% of consumers agree. This perception gap suggests that many enterprise teams operate in an echo chamber.
Agentic AI promises autonomous lead research, scoring, and outreach, but experts caution that human oversight and measurable KPIs are critical to avoid compliance risks and brand damage.
The AI conversation in marketing has officially moved past “should we use it?” to “who owns it, and is our data good enough to make it work?” Two HBR pieces this week hit on something CMOs need to take seriously: the C-suite battle over AI governance is happening right now, and marketing is at risk of losing decision rights over the very tools that will define customer experience for the next decade. If you don’t have a seat at the AI governance table, someone else is making those calls for you.
The practical decisions CMOs need to make are not about which AI tools to buy. They are about whether their organizations have the process discipline, data quality, and governance structures to make any AI investment pay off. The announcements below illustrate both the opportunity and the operational gap in concrete terms.
Only 32% of U.S. employees are actively engaged at work right now. That number has been falling for five years straight. Companies are spending more than ever on engagement surveys, pulse checks, eNPS scores, and culture consultants. And the needle isn’t moving.
While the pursuit of natural language understanding was a necessary step, it often overshadowed a more critical goal: utility. The real measure of success isn’t whether an AI can eloquently apologize for its inability to help, but whether it can actually solve the customer’s problem.
After decades of “spend-to-learn” advertising, are you still paying for
consumer insights that AI can generate for free, before a single dollar of
media spend?
