Milena Traikovich has built her career at the intersection of data analytics and demand generation, helping businesses navigate the complexities of modern marketing to nurture high-quality leads. With extensive experience in performance optimization, she offers a sharp perspective on how artificial intelligence is fundamentally reshaping the B2B landscape. In this discussion, we explore the collapse of the traditional marketing funnel in an AI-driven world, the critical shift from channel-specific metrics to unified customer data, and the strategic consolidation of technology stacks. Milena breaks down why first-party data has become the ultimate competitive advantage and how brands can balance data-driven optimization with creative excellence to thrive in this new era.
With organic click-through rates dropping as AI resolves queries directly, the traditional consideration funnel is collapsing. How can brands ensure they appear in these AI-driven shortlists, and what steps should they take to adapt their demand generation strategies for this new reality?
This shift caught everyone by surprise, not because it was happening, but because of the sheer velocity of the change. We’re seeing organic click-through rates plummet by as much as 34% to 64%. This isn’t from a lack of interest; it’s because AI is now the one answering the question, completely bypassing the need for a user to click through to a website. The entire consideration phase is being short-circuited. If your brand isn’t part of that initial AI-generated response, you effectively don’t exist for that buyer. To adapt, you have to shift your focus from chasing traffic to earning a presence within these AI-mediated discoveries. This means optimizing your content not just for search engines, but for the large language models that power these tools, ensuring your brand’s value proposition is clear, concise, and easily synthesized.
You describe programmatic AI moving from simple optimization to full-funnel orchestration. Can you walk us through a practical example of how AI might manage a customer journey across channels, and explain why clean first-party data is the most critical asset in this new environment?
Absolutely. Think of it as moving from a specialist to a conductor. Today, programmatic AI is great at optimizing a single instrument, like bidding on the right ad placement. Tomorrow, it will be orchestrating the entire symphony. Imagine a potential customer watches a CTV ad for a software product. The AI registers that exposure and, based on real-time intent signals, decides the next best step isn’t another ad, but a piece of high-value content delivered through a social channel. If the user engages, the AI might then dynamically shift the budget to serve a case study via a premium publisher, followed by an invitation to a webinar. This entire journey is fluid, managed by AI systems talking to other AI systems. But this orchestration is completely powerless without clean, actionable first-party data. That data is the lifeblood; it’s what tells the AI who the customer is, what they care about, and what they’ve done before. Without it, the AI is just guessing, and the orchestration falls apart.
Many marketing teams still rely on outdated metrics like CPMs and last-touch attribution. What are the biggest hurdles to shifting an organization’s mindset toward unified customer data, and what business outcomes, like lifetime value, can best convince leadership to invest in this change?
The biggest hurdle is simply inertia. It’s comfortable to stick with what you know, and metrics like CPMs and clicks are easy to measure, even if they don’t tell the whole story. The real challenge is that embracing a unified data approach requires fundamental changes—rethinking measurement frameworks, restructuring teams away from channel-specific silos, and investing in new technology. To get leadership on board, you have to speak their language, which is the language of business outcomes. Instead of talking about impressions, talk about increasing customer lifetime value. Show them how a unified view of the customer leads to higher cohort-level conversion rates. Frame the investment not as a marketing expense, but as a strategic imperative for understanding and proving the incremental contribution of every channel to the bottom line.
When consolidating tech stacks, a common pitfall is focusing on efficiency before strategy. Could you share an anecdote about a consolidation gone wrong and outline the first three steps a company should take to align its data strategy and integration capabilities before selecting tools?
I’ve seen it happen too many times. A company invests a fortune in a shiny new all-in-one platform, promising to cut costs by eliminating a dozen other tools. Six months later, nothing has improved because the underlying problem was never the tools themselves; it was fragmented data and a lack of a clear measurement strategy. The new, efficient platform was just amplifying the existing chaos. The first three steps should always be strategy-led. First, establish a single, consistent view of the customer—this means prioritizing your CRM and CDP to create a solid foundation of identity before you even think about orchestration tools. Second, get all stakeholders to agree on shared success metrics that are tied to business outcomes, not channel activity. Third, establish clear governance with cross-functional teams that have shared budgets and accountability. Without that structural change, the old silos will inevitably creep back in, no matter how great your tech is.
You highlighted CTV and retail media as powerful full-funnel channels. For a brand new to these platforms, how should they approach campaign planning, and what key performance indicators would you track from initial impression to final sale to prove their impact beyond simple awareness?
For a brand new to these channels, the approach must be integrated from day one. CTV is phenomenal because it offers the reach of traditional television but with digital precision, allowing you to connect ad exposure to real-world outcomes. Retail media is a game-changer because of its proximity to the point of purchase, with spend in the space already approaching $69 billion. To prove its full-funnel impact, you must move beyond awareness metrics. Start by tracking initial reach and frequency on CTV, but immediately connect that to mid-funnel actions like website visitation or product page views. Then, for retail media, you can close the loop entirely. Track everything from the first impression right through to the final sale using the platform’s first-party purchase data. This creates a clear, undeniable line connecting your ad spend to revenue, which is the holy grail for any marketer.
The relationship between creative quality and data-driven optimization is converging. How can data guide creative strategy without stifling originality? Please share a step-by-step process for how a brand can use AI testing to enhance, not just automate, its creative development.
It’s a misconception that data and creativity are at odds; they’re becoming partners. Data should never replace creative judgment, but it can provide an incredible compass. A practical process would look like this: First, use AI to analyze top-performing creative—yours and your competitors’—to identify patterns in messaging, visuals, and tone that resonate with your target audience. This isn’t about copying; it’s about understanding the landscape. Second, use these insights to develop several distinct creative hypotheses. Give your creative team the freedom to build original, compelling work based on these strategic pillars. Third, deploy these variations at a small scale and use AI-powered testing to rapidly measure engagement, sentiment, and conversion signals. Finally, feed the performance data back to the creative team not as a rigid set of rules, but as actionable insights to refine and perfect their art. This way, data provides the ‘what,’ and creatives master the ‘why’ and ‘how.’
What is your forecast for B2B marketing in the next five years?
Looking ahead, I see the most successful B2B marketers being the ones who master three core pillars: data, visibility, and trust. First, first-party data infrastructure will no longer be a nice-to-have; a unified CRM and CDP will be absolute table stakes for survival. Second, the game will shift dramatically from buying traffic to earning a presence. Marketers will need to become experts at getting their brands featured in AI-mediated discovery, as that’s where decisions will increasingly be made. Finally, privacy and transparency won’t just be compliance issues—they’ll be performance levers. Brands that are transparent about data use and can verify their claims will build the durable customer relationships that outlast any tactical trend or algorithm change. The future belongs to those who build on a foundation of clean, actionable data and genuine trust.
