This article was based on the interview with George Chang, Senior Director, Digital Experience & Technology Corporate Marketing at Hexagon AB by Greg Kihlström, AI Adoption and Marketing Measurement keynote speaker for The Agile Brand with Greg Kihlström podcast. Listen to the original episode here:
In enterprise marketing, there are few forces as powerful, or as potentially misguided, as the “great idea” that emerges from a senior leadership meeting. It often arrives with conviction, a sense of urgency, and a complete lack of supporting user data. We’ve all been there.
We are tasked with executing a vision based on intuition, only to watch it underperform, quietly rolling it back weeks later. This cycle of assumption-driven marketing is not only inefficient; it’s a quiet killer of innovation. It prioritizes being right over learning what’s right for the customer, creating a culture where testing is seen as a validation step rather than a discovery process.
The alternative is not to dismiss experience or intuition, but to channel it into a disciplined system of inquiry. This is the essence of a mature digital experience program: moving from project-based campaigns to a state of continuous optimization. It’s about building an engine for learning, where usability insights fuel A/B tests, and the results of those tests inform personalization strategies. This isn’t just about tweaking button colors. It’s a strategic shift that requires a cultural commitment to being data-informed, the right technology to enable agility, and a willingness to see a “failed” test as a valuable lesson learned. George Chang of Hexagon AB has been on the front lines of this transformation, turning a complex, multi-industry brand story into a coherent and constantly improving digital experience.
Making Optimization a Strategic Imperative, Not a Tactic
For many organizations, Conversion Rate Optimization (CRO) lives in a tactical silo. It’s a project, a line item, or a task assigned to a junior team member to “go run some tests.” This approach inherently limits its impact. To truly drive business results, optimization must be woven into the fabric of your strategy, influencing not just how you execute campaigns, but how you iterate on the entire digital experience. At Hexagon, a global leader in measurement technologies, this philosophy is central to their approach. They understand that a few isolated data points are just noise; real insight comes from a continuous stream of information.
“I think to make CRO something strategic, you have to treat it like something strategic. I guess what I mean by that is you have to be intentional in including testing as part of not only how you execute, but also how you iterate. And I think that’s really the key… If you take a few measurements here and there, you’re not really going to get a whole lot of useful information. But it’s the large number of measurements in context with one another that gives you that level of fidelity. And think testing and optimization is a similar story, right? You have to test and you have to test often.”
Chang’s analogy to Hexagon’s own technology is particularly sharp. A 3D scan isn’t created from a handful of measurements; it requires a massive volume of data points to create a high-fidelity image. Similarly, a high-fidelity understanding of your customer doesn’t come from one or two A/B tests a quarter. It comes from building a programmatic approach where testing is a constant, integrated part of the content lifecycle. For marketing leaders, this means reframing the conversation. Optimization isn’t what you do after a page is launched; it’s part of the launch process itself. It’s a commitment to treating every digital touchpoint as a living experiment, providing the continuous feedback loop needed to make smarter, broader strategic decisions.
Slaying the HiPPO with Objective Data
Every organization has a HiPPO in the room—the Highest Paid Person’s Opinion. It’s the voice that can override data, user feedback, and team consensus with a single subjective statement. Building a true culture of experimentation requires a framework for respectfully challenging that dynamic. The goal isn’t to create conflict, but to establish a system where all ideas, regardless of their origin, are treated as valid hypotheses to be tested. Data becomes the great equalizer, a neutral arbiter that shifts the focus from who is right to what is right for the user.
“The nice thing about data is that it’s objective and then people in general, by definition, they’re subjective… There’s that acronym, HiPPO, the highest paid person’s opinion, when you’re talking about decisions being made… Our stance on this whole thing is very much, everyone’s opinion is valid, regardless of your job title or your pay. It’s all valid and we all want to look at what options there are, but we want to run them through a test. And that’s really our proof point.”
This is a powerful cultural lever for any marketing leader. By institutionalizing testing, you create a process that can absorb and evaluate stakeholder requests without derailing the roadmap. Instead of a “yes” or “no,” the answer becomes, “That’s an interesting idea. Let’s design a test to see how users respond.” This approach has a dual benefit. First, it ensures that decisions are based on evidence, not authority. Second, it often reveals surprising truths about user behavior, reminding even the most experienced among us that our own biases and assumptions are often poor proxies for the customer’s reality. As Chang notes, people consistently do the unexpected, and the only way to know for sure is to test.
Scaling Optimization Through Democratization and Technology
One of the biggest hurdles to running a high-volume testing program is the operational bottleneck. If every test requires a centralized team of specialists—analysts, developers, QA—the program will inevitably move too slowly to generate meaningful momentum. The key to scaling, as Hexagon has found, is not to build a bigger central team, but to democratize the process. This involves empowering the marketers who are closest to the content and the customer to run their own experiments. Of course, this is only possible with a platform that makes it accessible.
“As we scale this program internally, we’re looking to democratize that testing and personalization process as widely as we can. We want to distribute that scale of people by enabling all these marketers to be able to do this themselves… We’re able to do this because of Sitecore XM Cloud, right? That platform has the testing and personalization interfaces built directly into the same interface that they go in and do their content editing and the content authoring and page creation process. So because it’s already a familiar interface to them, this makes it really easy to enable them.”
This is where the technology stack becomes a critical enabler of strategy. By integrating testing and personalization capabilities directly into the content management system (CMS), platforms like Sitecore AI (formerly XM Cloud) remove the technical and cognitive friction that often prevents marketers from experimenting. When creating a test is as easy as editing a page, it stops being a specialized task and becomes a natural extension of the content creation workflow. For leaders, the takeaway is clear: to scale your optimization efforts, you must equip your teams with tools that lower the barrier to entry and foster self-sufficiency. This creates a distributed model of ownership, where learning and improvement happen across the organization, not just within a single team.
Redefining Success: A Failed Test Is a Successful Lesson
Perhaps the most significant cultural shift required for continuous optimization is redefining the concept of success. In a traditional, project-based world, a test that doesn’t produce a lift is often seen as a failure. This creates a risk-averse environment where teams are afraid to try bold ideas, opting instead for safe, incremental changes. A truly agile, insight-driven organization understands that the goal of testing isn’t just to win; it’s to learn.
“A failed test gives you just as much insight as a successful test, right? The success in driving this culture of testing isn’t dictated by how many tests you get right, like how many times your hypothesis was proven right, but really how many good quality tests that you’re actually able to run, because with every test you learn something… The biggest thing is just to get started, to run that first test and then to run the second test and then to run the third test.”
This is a critical message for every marketing leader to champion. The value of an experiment lies in the information it generates, regardless of the outcome. A hypothesis that is proven wrong tells you something valuable about what your customers don’t want, saving you from investing in a flawed strategy. Success, therefore, should be measured not by the win rate, but by the testing velocity and the quality of the insights generated. The biggest barrier to this is often inertia. Chang’s advice to simply get started is fundamental. Begin with a small, simple test—changing the wording on a call-to-action, for example. The act of running that first experiment, analyzing the results, and sharing the learnings begins to build the muscle memory and cultural momentum needed for a sustainable program.
Summary
The journey from an intuition-led to a data-informed marketing organization is not merely a technical one. It is a fundamental shift in culture, process, and mindset. It requires elevating optimization from a tactical afterthought to a strategic pillar that informs every aspect of the digital experience. As George Chang’s work at Hexagon demonstrates, this involves establishing a system where objective data is the ultimate authority, empowering decentralized teams with the tools to experiment, and fostering a culture where learning is valued more than being right. It is a commitment to relentless iteration, grounded in a deep curiosity about human behavior.
For those of us leading marketing teams, our role is to be the chief enablers of this culture. We must provide the strategic framework, invest in the integrated technology, and, most importantly, create the psychological safety for our teams to place bets, to be wrong, and to learn from the outcome. The goal is not simply to achieve a higher conversion rate; it is to build a more agile, resilient, and customer-centric organization. By embracing a disciplined system of continuous testing and learning, we move beyond our own assumptions and begin building digital experiences that truly adapt to the ever-changing needs of our customers.
