The Relevance Gap - Why Most Martech is Already Obsolete

Relevance is the most critical currency in the customer lifecycle, yet most brands are unable to deliver it.

In a world where FAANG-engineered algorithms curate much of our reality—tailoring social feeds and entertainment to our specific, one-in-a-million preferences—consumer expectations have skyrocketed. We have been trained to expect magic. Consequently, when a consumer interacts with a standard brand, the drop-off in quality is jarring. For companies lacking the tech to match these "Netflix-level" interactions, the result is generic outbound noise that doesn't just annoy customers; it actively pushes them away.

The stakes are higher than you think. McKinsey data confirms that 76% of customers are frustrated when personalization is missing. But the uncomfortable truth is that even the brands that think they are personalizing are often getting it wrong, and "conventional wisdom" is to blame.

Most major Martech platforms were built on paradigms that are now several decades old. Basic segmentation, linear automation, and "insert name here" tokenization. All these approaches are no longer fit for purpose. You might be calling them by their first name, but you are still just broadcasting at them. It lacks relevance.

Some companies have even moved to LLM-generated personalization techniques but even these show up as a long-form version of tokenization - "insert unmoderated AI-generated copy here". More personal, just as irrelevant. 

Personalization = Treating people differently.
Relevance = Respecting those differences.

True relevance is nuanced. It isn't about who the customer is; it is about why they are here. Why would they want to hear from you? Why do they care? 

Relevance means reaching out with the exact solution they need, at the moment they need it. Even more importantly, it’s about leaving them alone when they don’t need it.

On a technical level, the gap between personalization and relevance is huge. Personalization has been possible for decades. Relevance at scale is a breaking wave, only now made possible by cutting-edge AI built on advanced data infrastructure.

We believe brands can, and must, do better. We envision a world where customers actually thank brands for the messages they receive because the communication is timely, channel-appropriate, and genuinely helpful. Where scattergun marketing dies off in favor of the next evolution of AI models for customer marketing.

Over the next few posts, we are going to tear down this topic in detail—exploring what is possible today and predicting what’s next. Make no mistake: huge changes are on the horizon. In many ways, we are looking at an "extinction-level event" for the legacy platforms that refuse to adapt. The industry must evolve, or it too will become irrelevant.