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As digital experiences become more complex, marketers and analysts alike must rethink how they build analytics systems that scale. In this conversation, Frederik Werner shares his insights into Adobe Analytics, journey analytics, and what it takes to create a human-centered, data-driven organization.

With more than a decade of experience in web analytics and data science, Frederik Werner has worn many hats—from developer to strategist, analyst to enabler. As the Head of Analytics at Accutics and author of the Full Stack Analyst blog, he brings a rare combination of technical expertise and business empathy. In this conversation, he reflects on evolving as an analyst, architecting scalable analytics systems, and unlocking the full potential of Adobe Customer Journey Analytics.
Early in his career, Frederik took pride in building technically advanced implementations—particularly as tools like tag managers reshaped how analysts worked. But as he matured in the field, his focus shifted from individual output to organizational enablement. Today, his greatest sense of accomplishment comes not from delivering reports himself, but from seeing stakeholders confidently navigate data systems he has built.
“Instead of being proud of what I can achieve on my own, I feel most accomplished when I can enable others. A scalable analytics system is the real achievement.”
This mindset has influenced how he approaches customer journey analytics—from the foundation of the tech stack to how data empowers decision-making at scale.
Every analytics journey starts with understanding business strategy and stakeholder maturity. For Frederik, the first step is always a deep exploration phase. He connects with senior leadership to align on strategic goals and assess how far along the organization is in its analytics journey.
“You have to align ambition with budget and capability. A gap there will break your foundation before you even start.”
From there, the architecture falls into place. If the goal is lightweight reporting, tools like Google Analytics or Matomo may suffice. But if analytics is core to the business strategy, enterprise-level tools like Adobe Analytics become critical. For teams that want to expand self-service, adding layers like Power BI or Adobe Customer Journey Analytics becomes part of the equation.
Even in forward-thinking organizations, analytics maturity often lags behind technical ambition. Stakeholders may demand insights without fully understanding the time and training required to deliver them. This creates a strain on analytics teams that are both building systems and managing expectations.
“The biggest constraint is team size. We have the systems, but education and stakeholder enablement take time.”
It’s a balancing act—showing value quickly while not overpromising in the early phases of maturity. Clear communication, managed expectations, and repeatable processes are key.
Frederik has worked with Adobe Analytics for many years and is a vocal advocate for getting the most out of the tool’s capabilities. His first rule: good analytics starts with good data. That means regular implementation audits, standardized tracking, and leveraging newer features like Global- and Virtual Report Suites.
Another non-negotiable is user identification. Log-ins and unified IDs unlock cross-device and cross-platform journeys—precisely what Adobe Customer Journey Analytics was designed to handle.
“Once your data is healthy, the possibilities with Customer Journey Analytics are nearly limitless.”
From comparing product interactions across apps and web to evaluating cross-channel marketing campaigns, journey analytics transforms how organizations think about performance.
When it comes to must-have metrics, Frederik focuses on three that blend strategic thinking with statistical rigor:
“Adobe lets me build these metrics end-to-end within the frontend. That’s powerful for speed and trust.”
With a background in psychology, Frederik brings empathy into how he builds and communicates analytics systems. This starts with framing questions in a human way, like translating “do users like this feature?” into measurable behavioral patterns such as “used the feature more than once.”
Empathy also means recognizing that most stakeholders aren’t technical. To make analytics work, analysts must present information simply, in business language, and always with a clear connection to user behavior.
“We’re not just collecting data. We’re helping teams extend their behavioral repertoire. That’s a human job.”
Frederik is candid about the challenges analytics teams face—especially the unrealistic expectations that a single analyst can drive transformative change without support.
“Analytics is like music. A one-man-band can play a tune, but a full orchestra creates impact.”
To truly embed data into the fabric of the business, analysts must shift from report producers to educators and system builders. This redefines how they’re hired, measured, and valued.
Having worked in both telecommunications and media, Frederik shares tactical advice tailored to each:
Frederik sees two major shifts ahead: the rise of privacy-conscious, login-based experiences and the democratization of advanced analytics. Tools like Adobe Experience Platform are breaking down walls between technical and business users.
“We’re moving from ‘track everything’ to ‘track what matters.’ That’s where trust and value intersect.”
He believes analysts must lead the charge—advocating for ethical tracking, empowering citizen analysts, and designing systems that are both powerful and usable.
Adobe Customer Journey Analytics enables organizations to combine data from web, app, and offline sources to analyze customer journeys across channels in real time.
A consistent tracking structure ensures reliable reporting across teams and platforms, making it easier to analyze behavior and optimize performance over time.
Identifying logged-in users enables accurate cross-device tracking and journey analysis, helping teams understand lifetime value, retention, and engagement patterns.
Modern analysts need technical skills in tools like Adobe Analytics, statistical knowledge for A/B testing and forecasting, and communication skills to translate insights into action.
It means designing metrics and systems that reflect user behavior and intent—going beyond clicks to understand how people interact with products and why it matters to the business.