The lesson the industry half-learned
- Customer experience strategy was the dominant business conversation of the early 2010s for the same reason AI dominates now, and most organisations made the same mistake: they went skin deep.
- The companies that built a genuine customer-insight capability in that period are structurally better positioned now. Not because they solved it once. Because they built the muscle to keep solving it as the problem evolved.
- AI does not change the underlying dynamic. It amplifies it. Understanding your customers more clearly than your competitors remains the durable advantage. The tools change. The principle does not.
If you were working in strategy, product, or marketing around 2013, you will remember the moment experience became the word that unlocked every boardroom door. Customer experience strategy. Human-centred experience design. Experience innovation. Every consultancy had a practice. Every conference had a track. Every major brand had a transformation programme with the word "experience" somewhere in the title.
It was, in many ways, the AI of its time. The dominant conversation, the thing that felt both genuinely important and slightly overwhelming in equal measure. Every company wanted to say they put the customer at the heart of their business. Some of them even meant it.
I was working in experience strategy, innovation and design through that period, and I have a particular memory of those years that I cannot quite shake. The Post-it note. If I had bought shares in 3M around 2012, I would be retired by now. The volume of sticky notes consumed by experience workshops was, by any reasonable measure, genuinely alarming, and I was an enthusiastic and perhaps unhealthy contributor to that particular epidemic.
But the substance underneath the Post-it notes was real. And it still is.
What We Learned Then Still Applies Now
The insight that emerged from a decade of serious customer experience work was not complicated, but it was consistently underestimated. Customers are human. They have needs, preferences, frustrations, and expectations that exist regardless of what technology you have deployed or what strategy you have declared. And those needs do not stay static.
As you solve one problem, another surfaces. Human beings are not a static set of requirements to be satisfied and checked off. They are people living evolving lives, in changing contexts, with shifting expectations shaped by every experience they have, not just their experience with your product. The bar moves constantly because everything around it is moving.
This is not a reason for despair. It is the engine of everything. The fact that human needs continuously evolve is what keeps businesses relevant, what creates new markets, what drives the next wave of innovation. It is the cycle that keeps the wheel turning. Once you understand that, you stop trying to reach a final state of "good enough" and start building the capability to keep pace.
The Durable Advantage
49%
faster profit growth for organisations that are genuinely customer-obsessed, alongside 41% faster revenue growth and 51% better retention
Forrester Research, 2024
Forrester's research quantifies what practitioners in this space have known for years. Organisations that genuinely understand their customers, and that build their operating model around that understanding, outperform peers by meaningful margins across revenue, profit, and retention.
The word "genuinely" carries weight here. There is a version of customer focus that is performative: mission statements, customer councils, NPS dashboards, and annual journey mapping exercises that produce beautifully formatted documents and change very little. And there is a version that is structural: where the voice of the customer informs product decisions, operational priorities, and investment choices in something close to real time.
The gap between those two versions is where most organisations live. The first is comfortable. The second is hard. The second is also what actually moves outcomes.
Why AI Does Not Make This Irrelevant
This is the argument I find myself making more frequently now. As AI becomes the dominant conversation, there is a version of the future being described where technology solves the customer understanding problem at scale: AI analyses behaviour, predicts needs, personalises experiences, and optimises the entire interaction without significant human judgment required.
Some of that is real and worth taking seriously. AI absolutely has the capability to process customer signals at a volume and speed that was not previously possible, and that has genuine value.
But the underlying challenge was never primarily a data or processing problem. It was a judgment problem. Which signals matter? What does this behaviour actually tell us about what this person needs? What tradeoff is worth making when those needs conflict with each other or with business constraints? How do you build trust with a customer base over time in a way that survives individual negative experiences?
These are human questions. They require human judgment, informed by data. AI is a powerful tool in service of that judgment. It is not a replacement for it.
The organisations that will win the next decade are not the ones who automate the most. They are the ones who understand their customers most clearly and who build the operating capability to act on that understanding at pace. Technology helps. Human judgment leads.
The Cycle Continues
What I have come to appreciate, after more than a decade in this space, is that the cycle is self-sustaining and, in its own way, reassuring. Human needs evolve. Organisations that understand those needs build better products and better experiences. Better experiences raise expectations. Raised expectations create new needs. And the people paying close attention to that movement, who are genuinely curious about what customers actually want rather than what they said they wanted last quarter, will always have somewhere valuable to go next.
The experience conversation of 2013 did not expire. It matured. The companies that took it seriously then are better positioned now, not because they solved the customer problem once, but because they built the muscle to keep solving it. That muscle does not go out of date.
Key Takeaways
- Experience strategy was not a trend. It was a fundamental insight about how durable competitive advantage is built. That insight has not been superseded by AI.
- Customer needs are not a static target. They evolve continuously. The organisations built to track and respond to that evolution have a structural advantage over those that treat it as a one-time problem to solve.
- AI amplifies the capability to understand customers. It does not replace the judgment required to act wisely on that understanding. The two need to work together.
- The gap between performative customer focus and structural customer obsession is where most competitive battles are actually being decided.
- The companies that took experience seriously in the 2010s built a muscle that compounded over time. The companies taking AI seriously now, and doing it properly, are building the same kind of durable capability.