Why understanding your business model matters more than any metric
Jomar’s Panel Session at Superweek Feb 2026
February, 2026
This was my fourth year hosting Superweek TV, the live studio sessions running alongside the main conference. Due to last minute schedule changes, the panel had to be assembled quickly, on the day I arrived.
Rather than relying on formal planning, I brought together three people I had come to know through different chapters of my career, each of whom consistently champions business understanding over data for data’s sake. What followed was not one standout moment, but a sustained sense of insightful energy, anchored in a shared belief that brands grow when they understand their business, serve customers well, and measure outcomes that actually matter.
I first met Juliana Jackson during the COVID years, when she joined Web Analytics Wednesday Copenhagen (Online) as a guest speaker. We immediately clicked. She has a rare ability to cut through complexity and speak honestly about how organisations actually work.
Gunnar Griese and I go further back, having worked in the same environment at IIH Nordic. What always stood out was his depth of thinking and his structured way of communicating complex ideas. He grounds measurement firmly in commercial reality.
I met Ezequiel Boehler through Superweek and MeasureCamp, initially through conversations around experimentation and decision making. Beyond the product discussion, what stood out was his consistent focus on intent. Why are you doing this at all?
Metrics without business context do not drive decisions
One of the first assumptions challenged by the panel was the idea that metrics such as profit or customer lifetime value can function as practical steering mechanisms on their own.
Juliana made the point clearly. “Every company will say their north star is profit or CLV. But that does not really mean anything if you have multiple leadership metrics and siloed team KPIs that do not actually connect.”
The issue is not a lack of data, but the distance between leadership metrics and everyday decision making. When teams optimise in silos, metrics lose their ability to guide the business as a whole.
CLV is an outcome, not a lever
Rather than treating customer lifetime value as something to optimise directly, the panel consistently reframed it as a consequence of stronger fundamentals.
Gunnar was explicit on this point. “CLV is essentially an outcome of something else. Of a good product, of a good experience, of whatever actually drives the business.”
When CLV becomes a target in itself, organisations risk chasing short term improvements that undermine long term value. When it is treated as an outcome, it becomes a useful signal of whether the business is working as intended.
Personalisation cannot fix a weak core
Personalisation featured heavily in the discussion, but not as a silver bullet.
The panel agreed that personalisation is one lever among many, and rarely the first one that should be pulled. Without a solid product, a clear proposition, and coherent pricing, personalisation simply amplifies existing weaknesses.
As Gunnar put it bluntly, “You can have the best personalisation in the world. If you have a really bad product at the core, personalisation is not going to save you.”
Maturity is knowing why you are doing something
From both agency and vendor perspectives, maturity was framed as intent rather than sophistication.
Ezequiel emphasised this clearly. “There is maturity in knowing why you are acquiring a product. Whether you then use all of its potential is secondary to understanding the purpose.”
Buying tools without clarity creates the illusion of progress while avoiding the harder work of alignment. Knowing what success looks like matters more than knowing how every feature works.
Measurement must reconnect with business reality
Another recurring theme was the gap between analytical excellence and business impact.
The panel challenged the idea that organisations need deeper data. Instead, they need stronger connections between what they measure and how the business actually operates.
As Gunnar summarised, “We do not need deeper data. We need better connections between data and the business.”
Too often, success is judged on surface metrics that ignore returns, refunds, long term value, or operational cost. Measurement maturity is about understanding what outcomes truly represent.
Complexity should be hidden, not celebrated
From the agency side, Juliana argued strongly for abstraction over exposure.
“Clients do not care about the technical complexity,” she noted. “Our job is to understand their commercial reality and help them get there.”
Complexity should live behind the scenes. When it becomes the focus, it distracts from the decisions leaders are actually trying to make.
A simple truth beneath the complexity
As the conversation closed, the takeaway was strikingly simple.
Businesses grow by increasing top line revenue and protecting the bottom line. That clarity often gets lost beneath layers of metrics, tools, and optimisation frameworks.
This panel was a reminder that data is most powerful when it serves the business, not when the business is reshaped to serve the data. Understanding your business model will always matter more than any single metric. Everything else follows from there.
Five takeaways for brand leaders
- Start every initiative with a business question, not a metric
If you cannot clearly explain how something supports revenue growth or cost control, it is unlikely to create real value. - Treat CLV as a health indicator, not a control lever
Use it to understand the consequences of your decisions, not as a target to optimise in isolation. - Fix the foundations before optimising experiences
Personalisation and experimentation amplify what already exists. Make sure the core of your business is sound first. - Align people and incentives before buying new tools
Shared understanding of outcomes matters more than technical sophistication. - Measure outcomes that reflect real business impact
Go beyond surface metrics and focus on what helps leaders make meaningful trade offs.
