Customer Experience
We Say We are Customer-Centric. But, Are We?
By Frankline Kibuacha
“ We are customer-centric.” Think about the number of times you have heard this statement. I would bet it has come up so often that you no longer pause to reflect on what it actually means.
It is said in boardrooms, in strategy meetings, in brand presentations, and in marketing plans. It has become one of those phrases that everyone agrees with, no one challenges, and very few people take the time to define.
The reality is, at some point, customer-centricity stopped being something brands strive for and became something they assume they already are. And that is where the problem begins.
Because once something becomes assumed, it stops being interrogated. We stop asking what it looks like in practice, how it is measured, and more importantly, we stop asking whether the customer would agree.
Customer-centricity, in many organisations today, has quietly shifted from a discipline to a declaration.
But through this article, I want to challenge us to take a step back and think deep about what being customer centric means. The simple meaning and spirit of the term: Being customer-centric means putting the customer at the center of every business decision, strategy, and interaction. It is a long-term business strategy and a company-wide philosophy that prioritizes understanding and fulfilling customer needs over short-term sales or internal processes.
32 MAL71 / 26 ISSUE
The Data Comfort Zone
Part of the reason this illusion persists is that we are living in a time when data is more accessible than ever.
Today’ s marketer has visibility that would have been unthinkable a decade ago. We can track customer journeys across platforms, measure engagement in real time, analyse conversion funnels, and segment audiences with increasing precision. We can see what people click on, how long they stay, what they buy, and when they leave.
There is no question that this has made marketing more informed and, in many ways, a lot more effective. But it has also created a certain level of comfort.
When you have this much visibility, it is easy to believe that you understand your customer. You have good AI-powered Customer Relationship Management( CRM) software, so the dashboards are detailed. The numbers are precise. The trends are clear. Automated and super-personalized emails and WhatsApp messages are going to clients at just the right time and touchpoint. It gives a sense of control. And that is where we need to be careful, because visibility is not the same as understanding.
For example, a customer clicks on your ad. We interpret that as interest. Another one makes a repeat purchase. We label them as loyal customers. Another opens your app frequently, we put them in the“ engaged customers” pot.
But each of these is an interpretation layered on top of behaviour. And behaviour, on its own, does not always tell the full story. What we are often looking at is what customers did, not why they did it. And that distinction matters more than we sometimes acknowledge. In my work, I have seen how easy it is to build confident narratives from incomplete signals.
The data, in all these cases, is accurate. But the meaning we assign to it is not always. This is not a limitation of data itself, but a reminder of its role. Data shows us patterns and shifts, and points us in a direction. But it does not always explain the underlying cause.
And when we rely on it as a complete picture, rather than a starting point, we risk making decisions that are technically informed, but strategically misaligned.
When Interpretation Becomes Truth
We have established thus far that the challenge is not the availability of data, but how quickly we move from observation to conclusion.
Over time, the patterns we see in our reports start to feel like explanations. Teams begin to build narratives around them. The issue is that once these narratives take hold internally, they become difficult to challenge. They shape strategy, influence decision-making, and guide investment. And because they are backed by data, they carry a level of authority that makes them feel unquestionable. These interpretations