Moving Beyond Visibility: Turning Marketing Data into Real Business Outcomes

3/27/2026 Matthew Tilley

The sheer volume of data available to marketers today is staggering. We can track clicks, views, impressions, and engagement across countless channels, leading to dashboards that are constantly glowing with activity. Yet, as Kevin Bell points out in a recent episode of Iridio^℠ by RRD's The Orchestration Podcast, this visibility often masks a deeper issue: mistaking access to data for true understanding.

Many organizations are swimming in metrics but starving for actionable insight. The goal isn't just to see what happened, but to understand why it happened and, more importantly, what to do next. Bridging this gap requires a fundamental shift in mindset and an evolution of our measurement philosophy.

What’s working vs. what’s noise in modern measurement

Kevin Bell highlights that measurement is, thankfully, evolving positively. The industry is paying more attention to the data foundation and fostering a greater test-and-learn mentality, which enables more advanced analytics and closed-loop measurement.

However, this increased focus also brings significant noise:

• The deterministic myth: There’s a pervasive, though incorrect, belief that with the rise of first-party data, every outcome is perfectly traceable, real-time, and deterministic. As Kevin notes, this isn't the reality, especially in digital media, where probabilistic results are inevitable. Over-relying on this notion creates fragility.
• Data overload: The trap of "more data is always better" can lead to chasing too many signals, distracting from the core business objective of any given test. It’s like having extra, unnecessary information in a math problem — it clouds the simple solution.
• Failure aversion: Perhaps the most harmful noise is the culture that treats a failed test as an absolute failure. If the stakes are high, there's pressure to avoid negative results, which stifles the learning necessary for true progress. As Kevin jokes about skiing, if you aren't falling, you aren't pushing your limits.

From dashboards to decisions

The dashboard is essential, but it often defaults to focusing on campaign and channel analytics, such as “How well did email perform versus social?” To drive real impact, the focus must pivot to client measurement, which is more likely to ask "How do all these efforts combine to impact the end business objective?”

The way to close this gap is by starting with a “North Star” objective and working backward to establish measurable points along the customer journey. 

That means defining the ultimate business objective first. This goal then dictates the necessary leading indicators (signals that show progress) and lagging indicators (results requiring longer attribution windows). 

And, of course, context is king. Metrics are only meaningful when put into context. Is this data point a leading indicator toward the goal, or is it merely a comfortable vanity metric (like easy-to-measure clicks or likes) that doesn't actually connect to the bottom line?

This intentional approach allows teams to build reports that clearly illustrate how various tactical inputs ladder up to the overall story of business performance.

First-party data as a dynamic partnership

First-party data is often treated as a static asset, but Kevin encourages viewing it as an ongoing journey and a partnership. It represents the customer's unique touchpoints over time—their path to purchase.

Like any relationship, this data set is dynamic. Customer habits, life events (e.g., pre- vs. post-COVID), and daily routines change, meaning the data from last year won't perfectly predict today. 

Therefore, data must be viewed as a conversation that builds a relationship over time. This perspective recognizes that data needs to be continuously refreshed and understood through context. While compliance and privacy must lead, utilizing this richer context offers a significant advantage in understanding customer loyalty journeys.

From what happened to what should happen

The ultimate goal for advanced measurement is to shift from descriptive ("What happened?") and diagnostic ("Why did it happen?") to predictive ("What will happen?") and prescriptive ("What should we be doing to create the future?").

While this move up the value chain is challenging, requiring robust data infrastructure and advanced models, the technology to enable it is advancing rapidly. However, this forward-looking work must still be housed within a culture that expects and embraces failed tests and imperfect predictions. The constant loop of stimulus, action, observation, measurement, and learning remains the only timeless framework, regardless of the sophistication of the tools (MTA, MMM, AI) being used.

Starting your journey to smarter measurement

If you're feeling overwhelmed by concepts like Multi-Touch Attribution (MTA) or Media Mix Modeling (MMM), the best way to start is by focusing on a playbook mindset anchored to your core business objective.

Start by understanding what specifically P & L goal you are trying to move. Then, ask, “What reliable data do you currently have to measure against that goal?” Then, build your initial playbook around the feedback loop: Stimulus → Action → Observe → Measure → Learn. 

This foundational structure is more valuable than any single tool or metric. And, by prioritizing this simple, resilient loop, marketers can filter out the noise and develop a strategy that is custom-built to deliver meaningful, measurable outcomes for their specific business.

Want to hear the rest of the conversation? Check out the full episode of The Orchestration Podcast for a deeper dive into modern marketing.

Matthew Tilley is the host of The Orchestration Podcast by Iridio and Vice President of Growth Marketing at RRD.