Natalie Cunningham, Senior Vice President of Marketing at Data Axle shares a few proven B2B marketing must-dos in this MarTech Interview with MarTechSeries:

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Hi Natalie, tell us what you most love about today’s state of B2B marketing?

B2B is officially shedding its “Boring2Boring” reputation. We’ve stopped marketing to job titles and started marketing to humans. The tools are smarter, the insights are faster, and the creative bar is so much higher.

What I love is the shift from broadcasting to orchestrating, and using data to design intelligent, adaptive experiences that actually earn attention. Marketers who lean into the convergence of data, AI, and creativity are redefining what’s possible.

At a time when data is integral to every marketing plan, what tips would you share with modern marketers?

At a time when data is (or should be) woven into every marketing strategy, my biggest piece of advice is to focus on what actually makes it work: quality, connection, and context. Too many teams still chase volume over validity. When your data is accurate, unified, and well-governed, you earn the confidence to move faster, take smarter risks, and create personalization that feels genuinely human instead of automated. It’s not about having more data; it’s about having the right data, working together.

Take us through some of the ways in which you’ve been using AI-powered martech to drive goals and processes.

We’re using AI to turn possibility into velocity. At Data Axle, we are actively embedding AI into everything from segmentation and enrichment to creative production and predictive modeling. But the key isn’t just the technology, it’s the orchestration. AI can only deliver real value when it’s paired with quality data and human intuition.

I’m less interested in using AI to automate the past and more focused on using it to anticipate the future, uncovering patterns, testing ideas, and freeing up time for marketers to do what machines can’t: think, imagine, and empathize.

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With marketing’s evolution, thanks to the rapid change in how martech and AI are influencing the ecosystem, how are you seeing typical marketing teams and roles shift?

Marketing has evolved from a function-based department into a dynamic, data-driven ecosystem. Traditional silos of brand, analytics, and operations are giving way to cross-functional “jobs to be done” (JTBD) structures – teams organized around outcomes like brand awareness or customer expansion rather than rigid disciplines.

In practice, this means we’re seeing pods of generalists supported by virtual AI teammates, integrated workflows, and specialized tools – all aligned toward a shared business objective. While deep expertise still matters, the real shift is in how these teams collaborate: analysts think like storytellers, creatives understand data, and CMOs think like technologists.

It’s a model long embraced by product and engineering organizations, but with the rise of GenAI, marketing and broader revenue teams are now following suit, challenging the traditional boundaries between sales, marketing, and customer success. The result is a more adaptive, outcome-driven culture where experimentation and iteration are core to how teams operate.

What about today’s modern martech range is still undervalued by marketers?

For years, marketers have been sold the idea that software could solve all our problems. We’ve invested heavily in platforms, but often without a clear strategy for how they should work together or what they’re meant to enable. The truth is, technology should support strategy, not drive it.

We’ve had it backwards for too long, asking “What can this platform do?” instead of “What do we need our martech to do to make our strategy real?” The most undervalued aspect of martech today isn’t a feature or a tool – it’s strategic alignment.

The marketers who step back, reconnect their systems around a unified purpose, and use AI to accelerate that alignment will be the ones who finally realize the promise of all this technology.

Five ways in which you feel marketers should optimize their martech use and processes to drive goals.

1. Start with strategy, not software: Your stack should follow your vision, not dictate it.
2. Clean and unify your data: AI and automation are only as good as the inputs they learn from.
3. Design for agility: Processes should evolve as fast as the martech market is.
4. Interoperability is key: Your stack shouldn’t require manual intervention between tools. Build the connection layer.
5. Keep the human layer: Tools enable outcomes, but ultimately, you are in charge.

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