Marketing leaders today are under immense pressure: deliver smarter, faster, and more personalized customer experiences while operating with smaller teams and tighter budgets. The problem? Most martech stacks are bloated with redundant tools, unused licenses, and expensive long-term contracts. In lean times, that model breaks.
Over the past year, I’ve spoken with CMOs across industries — from retail and travel to financial services and gaming — and they’re all wrestling with the same challenge: how to do more with less. The answer isn’t chasing the next shiny platform. It’s about getting ruthless with your existing stack, grounding every initiative in high-quality, real-time data, and being disciplined about emerging tech like AI.
Here are three practical steps to build a leaner, more effective stack.
1. Audit and optimize before you buy anything new
Most enterprise stacks contain significant duplication. I’ve seen organizations with three separate solutions for customer data management, each producing slightly different results, none delivering the outcomes the business expected. One major financial services company had invested in nearly every tool on the market, yet still couldn’t act on half the insights those platforms promised.
The first step is simple: audit ruthlessly.
- What platforms are in use?
- Which are duplicative or underutilized?
- Did each tool actually deliver on its original use case?
Too often, marketing teams “settle” when a tool falls short, lowering expectations instead of holding technology accountable. Stop auto-renewing underperforming platforms. A one-year retrospective is critical: did the platform achieve what you set out to achieve? If not, why renew? Define what success looks like, measure against it, and create exit strategies in advance.
In lean times, ROI clarity isn’t optional. It’s the difference between building a lean, effective stack and maintaining a patchwork of underperforming tools.
2. Make real-time, high-quality data your foundation
Even the most advanced martech platforms are useless without reliable data flowing through them. A recurring theme in my recent conversations is how even simple use cases fall apart when the right data isn’t available.
One global retailer admitted they couldn’t send a personalized cart abandonment email – because the technologies they bought that promised the data and activation never delivered on that promise. A leading gaming company told me they could only personalize offers when a customer was physically on the property, missing massive opportunities to build loyalty via tailored offers before and after visits.
The lesson is clear: your stack is only as strong as its data foundation. Before layering on new capabilities, ensure you have real-time, accurate, and complete data to power them. And “real-time” has been watered down — with some platforms, it means hours or days. But customers act in milliseconds, and so must your data.
Without accurate, immediate data, personalization becomes generic, triggers misfire, and automation collapses. Invest in making your customer data accessible and actionable in the moment. That’s what enables you to connect historical insights with live behavior to deliver experiences that actually matter.
3. Be thoughtful about AI adoption
If you haven’t solved for stack optimization and reliable data, you’re not ready for AI. I recently met with a company with no reporting capabilities trying to jump straight into predictive analytics. It simply doesn’t work. Your models are only going to be as good as the data you use to feed, or as they say – garbage in, garbage out.
AI should be introduced when clear problems and trusted data align. Otherwise, it’s just box-checking. Focus on nailing the fundamentals first: clean data, clear use cases, and technology that proves value. As I often say, not every problem requires AI, sometimes the best solution is simply executing the basics really well.
Rethinking martech from the ground up
Forward-thinking brands are shifting perspective: martech isn’t just a set of tools, it’s an ecosystem designed to power analytics, real-time intelligence, and instant customer triggers. When stacks are built with this philosophy, businesses not only get more value from their existing investments, but they also set themselves up to evaluate new technologies with greater discipline.
By auditing ruthlessly, prioritizing high-quality data, and resisting premature AI hype, CMOs can turn today’s constraints into tomorrow’s competitive advantage. The result isn’t just a leaner stack — it’s a smarter, more effective engine for growth.