With extensive experience in analytics and lead generation, Milena Traikovich helps businesses cut through the noise of modern marketing. We sat down with her to discuss the pervasive challenge of data overload, a problem highlighted in a recent report from Funnel and Ravn Research. Our conversation explored why so many teams feel they are drowning in data yet starving for insight, touching on the pitfalls of vanity metrics, the struggle to break down data silos, and the critical need to build a culture that moves beyond simple reporting to genuine, actionable analysis.
A recent report found 72% of in-house marketers feel overwhelmed by data. What is the first practical step a team can take to move from data collection to insight generation? Please walk me through a simple, step-by-step process for getting started.
That feeling of drowning in spreadsheets and dashboards is incredibly common, and the key is to stop trying to boil the ocean. The first, most crucial step is to radically simplify your focus. Start by asking your team to agree on the single most important business question you need to answer this quarter. Is it “Which channel is generating the most qualified leads?” or “What is our customer acquisition cost for our new product line?” Once you have that one question, the next step is to identify the two or three—and no more than three—metrics that directly answer it. Everything else is noise for now. Finally, build one simple, clean report or dashboard that displays only those few key metrics. This process forces you to move from a collector’s mindset to an analyst’s mindset, instantly making the data feel less overwhelming and more purposeful.
The article mentions dashboards often serve up “vanity metrics” instead of answering, “what do we do next?” How can teams redesign their reporting to focus on business outcomes? Could you share an example of transforming a vanity metric into a truly actionable one?
This is a classic problem because vanity metrics feel good but tell you very little. Clicks are my favorite example. Seeing “10,000 clicks” on a report looks impressive, but it’s pure vanity. It doesn’t tell you if you’ve made a single dollar or moved a single lead down the funnel. To make it actionable, you have to connect it to a business outcome. So, instead of tracking clicks, you track “Click-to-Lead Conversion Rate.” I remember a campaign where a team was celebrating a huge spike in clicks, but sales were flat. When we switched our focus to the conversion rate, we saw it was less than 0.1%. The clicks were coming from a completely irrelevant audience. That one change in reporting shifted the entire conversation from “Look how many people clicked!” to “Why are the people who click not converting, and how do we fix our targeting or landing page?” That’s the pivot from vanity to value.
With 68% of marketers reporting a lack of up-to-date, cross-channel visibility, what is a crucial first step to break down these data silos? Please describe a process or tool that has helped a team you know gain a more unified view of performance.
Breaking down silos feels like a monumental task, but the first step is actually organizational, not technical. You need to create a “shared source of truth.” This begins with a workshop where you get stakeholders from every channel—paid search, social, email, content—in the same room. The goal is to map out the entire customer journey and identify every single data source. From there, you can prioritize. Instead of trying to connect everything at once, focus on integrating the two or three most critical platforms that represent the core of your funnel. A marketing intelligence platform is often the best tool for this, as it can automate the process of pulling data from different APIs into one unified view. I saw one team realize, only after unifying their social and search data, that their top-of-funnel social campaigns were driving a massive increase in high-converting branded search queries a week later. They had been ready to cut the social budget, but that unified view proved it was one of their most valuable assets.
Given that 41% of teams don’t analyze what caused their outcomes, how can a leader foster a culture of deeper analysis? Can you share an anecdote or a specific meeting structure that encourages teams to move beyond simply reporting numbers and start recommending next steps?
This is entirely a cultural challenge that leadership has to solve. You have to change the expectations around reporting. I’ve had great success implementing a meeting structure I call the “What, So What, Now What” framework. In our weekly performance meetings, no one is allowed to just present the “What”—the raw number. They must immediately follow it with the “So What,” which is their analysis or hypothesis for why that number changed. And most importantly, they must end with the “Now What,” a concrete recommendation for action. For example, instead of saying, “Our email open rate dropped 5%,” a marketer has to say, “Our open rate dropped 5% [What]. I believe this is due to subject line fatigue, as we’ve used a similar format for four weeks [So What]. I recommend we A/B test three new, curiosity-driven subject lines for next week’s campaign [Now What].” It’s uncomfortable at first, but it quickly trains the team to think like analysts and strategists, not just reporters. It fundamentally shifts the team’s value from telling you what happened to advising you on what to do next.
What is your forecast for the future of marketing intelligence?
I believe we are on the cusp of a major shift from descriptive analytics to prescriptive analytics. For years, we’ve been stuck just trying to answer, “What happened?” The report highlights that we’re not even doing that very well, with 86% of teams struggling to identify what’s driving performance. The future, powered by more sophisticated AI, won’t just show you the data in a clean dashboard; it will actively recommend your next steps. Instead of a marketer having to dig for the “why,” the platform itself will surface insights like, “Your cost per lead on this channel is rising; we predict it will be unprofitable in two weeks. We recommend reallocating 20% of the budget to this other, emerging channel.” This will free up marketers from the drudgery of data wrangling and allow them to focus on the creative and strategic elements that a machine can’t replicate. The challenge of being overwhelmed by data will be replaced by the challenge of choosing the best recommendation among several good options.
