Hi I’m Jake, a Product Designer, professional skeptic and well-practiced daydreamer. I spend a lot of time thinking about things that, by my own admission, probably don’t warrant the level of scrutiny I give them. I also ask a lot of questions, often about things of dubious importance. However, every so often, something genuinely interesting (admittedly by my assessment alone) starts to take shape.
Like a vague cloud of raw thought, it’s that sense that there’s something more to an idea or experience. It floats around my head, bumping into walls until, eventually, my brain connects the dots and packages it into something worth exploring. It’s a bit like trying to herd smoke, or like getting a hundred angry bees to march, single file down a straw. This particular thought has held my attention long enough that I’ve decided to write my very first blog post, not just about this thought, but my first blog post ever. Whether I manage to wrangle my thoughts into something coherent remains to be seen, but I’ll have a punt.
So… after a few important people in my life called out my tendency toward self-criticism. Basically, I couldn’t take a compliment. This, in true Jake fashion, provoked a pretty solid period of self-reflection. Which eventually led me to the thought:
“You believe your self-criticism is objective, while dismissing others’ praise as distorted by psychological biases and social pressure.”
That realisation was valuable on its own. It shifted how I interpret positive feedback. However, it quickly expanded beyond personal reflection. It made me start thinking about how the same dynamic might show up elsewhere, especially in design.
Subjective truths & performative behaviours
Which brings us to the question: how much can we really trust our users? Not because they intend to deceive, but because, like all of us, they’re human, shaped by bias, emotion, and context. With the sheer number of cognitive biases at play e.g. confirmation bias, selective perception and illusory correlation to name a few, as well as social pressures and the general unpredictability of human behaviour, can we really trust the data that users provide us? Percolating on all of this led to, as is so often the case for me, a whole load more questions…
How reliable are our research findings, really? And if they are reliable, how often? Ninety percent of the time? Fifty? Twenty? Not at all? What makes them reliable? Do we have a clue what users think and feel, or are we just interpreting their experiences through a fog of assumptions and hopeful guesswork?
There’s a bunch to unpack here, spanning multiple disciplines: design research, behavioural science, psychology, UX theory, and more. Each field offers its own perspectives and insights, which, for me at least, would be impossible to cover comprehensively in a single blog. On top of that, I don’t claim expertise in all these areas; rather, this is just the beginning of my exploration into the complexity of human perception in design. My aim is to lay out some initial thoughts, highlight key ideas, and open up the conversation about how perception can influence, and be influenced by, design decisions.
We’ll touch on some of the limitations of relying primarily on user-reported data to guide design decisions, and we’ll question the framing of resulting design solutions as being aligned with an “objective reality”. A concept that is arguably inaccessible due to the inherently subjective nature of human perception.
Over-reliance on attitudes and behaviours
User attitudes, found through methods such as semi-structured interviews, are the staple of user research for almost every design project (with budget for research, of course) and are often the only type of research used to guide entire design projects. The attitudinal findings are typically used as pillars of absolute certainty when it comes to guiding design solutions.
However, it’s well documented that user attitudes, particularly in isolation, are unreliable and easily influenced. Things like acquiescence bias, social desirability bias, limitations of human memory and even the presence of the interviewer, all contribute to the potential unreliability (although not without value) of stand alone attitudinal data, and this doesn’t even begin to consider the influence and bias imposed on the data from the researchers side.
The obvious solution to combat the potential shortcomings of attitudinal data: behavioural methods. Now, behavioural data doesn’t suffer the same challenges as attitudinal data, such as self-reporting bias, and can bolster the value of your attitudinal data when used in tandem. Still, this pairing isn’t flawless. People often adjust their attitudes after observing their own actions or change them when they feel discomfort because beliefs and behaviours clash, a tension known as cognitive dissonance.
So what does that leave us with?
Beyond the observable: Latent knowledge and perceived value
Latent knowledge, a far less commonly pursued and often dismissed data source, that is easily just as valuable as attitudinal and behavioural data, albeit not without its challenges. Latent knowledge refers to the implicit, often unspoken understanding people bring to their interactions with products, services, and environments.
Shaped by past experiences and cultural context, it influences how individuals interpret cues, navigate systems, and make decisions instinctively. This kind of knowledge is powerful but difficult to surface because people rarely articulate what they intuitively know, making it challenging for designers to uncover through direct questioning or standard research methods. A quote often attributed to Henry Ford captures this dilemma:
“If I had asked people what they wanted, they would have said a faster horse.”
It illustrates how latent knowledge often hides behind literal requests, requiring designers to interpret deeper needs. Perceptions are a clear example of latent knowledge. Perceptions are defined as how people “interpret sensory information to form a mental representation of the world. It’s influenced by experience, expectations, attention, and varies across individuals.” (IxDF, 2020). Because perceptions are often felt but not verbalised, they fall under tacit knowledge and since tacit knowledge itself is a subset of latent knowledge, we can understand perception as both tacit and latent: present in experience, yet difficult to surface. It’s not just about what users see or do, but how they make sense of it.
The phrase “all value is perceived value,” popularised by Rory Sutherland, means that the worth of a product, service, or experience is not determined solely by its objective features, but by how people feel about it. In other words, value exists in the mind of the user. It is a perception, shaped by context, expectations, emotions, and presentation.
A great example of how perception can shape an experience, often diverging from objective reality is the ever-popular trip to the coffee shop. Starbucks designed its coffee-making process to feel more artisanal by emphasising visible, manual steps, like steaming milk by hand and preparing drinks in full view of customers. By making the process slightly slower and more theatrical, the brand enhanced the perception of quality and care. Importantly, the product itself didn’t change, the coffee remained the same. What changed was how it was perceived.
This shift in perception helped position Starbucks coffee as a premium, handcrafted product, rather than a fast, commodified beverage. Apparently, that’s how you justify charging £50 for a latte with someone’s name spelled wrong on the cup. This validates Beau Lotto’s work in neuroscience, demonstrating how our brains apply meaning to raw sensory data, often leading to illusions or misinterpretations, which is exemplified in this case: the coffee itself never became more premium.
Rory Sutherland said it best: “All value is perceived value”
TEDGlobal 2009
It’s arguable that designing for perception often matters more than improving objective reality, an idea strongly championed by Rory Sutherland. The Starbucks example illustrates this perfectly, the perception of a premium, handcrafted product was achieved not by changing the coffee itself, but by changing how the experience was framed and delivered.
It’s unlikely that a similar shift in customer sentiment could have been achieved through product quality improvements alone. Ignoring the psychological and perception-based experiences of your audience risks missing what truly drives user satisfaction and loyalty. Without understanding how people feel about an experience, not just what they do or say, designers may invest in the wrong improvements, solve the wrong problems, or worse, create friction where they intended to add value.
The cost of neglecting perception in design
While the value of designing for perception is clear, the risks of neglecting it can be significant, leading to misaligned solutions, wasted resources, and experiences that fail to resonate. To make the risks of ignoring perception more tangible, let’s look at a challenge in the eco-friendly product space, specifically, dish soap.
Attitude: “I try my best to live as sustainably as possible.”
Behaviour: Buys conventional (non-eco) dish soap.
Stated Reason: “Because it cleans better than the eco-friendly alternatives.”
At first glance, this seems like a straightforward case of misalignment between values and actions. We’ve identified the attitude, the behaviour, and the rationalisation behind the choice. So, what are the possible solutions? Since there’s no actual difference in cleaning quality between the two products, the variation users have reported reflects their experience, not the underlying performance or objective reality. So how might you address that? Here are a few possible approaches:
- Marketing Campaign: Reassure users that the eco-friendly soap cleans just as well.
- Product Reformulation: Invest in making it outperform conventional soaps.
- Third-Party Endorsements: Leverage chefs, cleaning experts, or sustainability influencers.
Each of these solutions has merit; however, they also come with significant cost, time, and effort. Even then, they may not sufficiently address the root issue. This is where asking what Rory Sutherland calls the psychological why (as discussed in his book Alchemy: The Magic of Original Thinking in a World of Mind-Numbing Conformity) proves valuable. The answer to this “why” lies in the emotional, experiential, and often irrational reasons why people behave the way they do. Reasons that make perfect sense to the individual, even if they don’t align with logic, data, or so-called objective reasoning.
As mentioned earlier, this kind of insight is notoriously difficult for users to articulate. Yet it’s key to uncovering the perceptions you’re ultimately looking to design for. To be absolutely clear: this is a question for the project team, not for the users. It’s up to the team to formulate hypotheses around the psychological why and to develop the means to test and validate them.
So, returning to the washing-up liquid example, let’s assume the team has successfully uncovered the factors contributing to users’ underlying perception that eco-friendly products don’t clean as effectively. In this case, the insight likely looks something like this:
Underlying user perception: “More lather = better cleaning.”
If the eco-friendly soap doesn’t foam as much, it may be perceived as less effective, regardless of its actual performance. I will preface this by stating I’m no expert in dishwashing soaps; however, enhancing lather through the use of safe, biodegradable foaming agents might help overcome barriers to the adoption of eco-friendly dish soaps. Rather than turning immediately to costly solutions, a more targeted approach to uncovering genuine user perceptions could lead to outcomes that are more appropriate, effective, and potentially less resource-intensive.
Designing for perception, not deception
How GE HealthCare turned fear into adventure through empathetic, perception-driven design.
One of the potential hesitations around designing for perception is that it may feel manipulative, even unethical. There’s a discomfort in the idea of shaping how people feel rather than just improving what they get. The truth is, every design intervention influences perception, whether intentionally or not. The real responsibility lies in how thoughtfully and ethically that influence is applied. When done with care, designing for perception isn’t about deception, it’s about empathy. And few examples demonstrate this more powerfully than GE HealthCare and the MRI scan.
This is one of the clearest demonstrations of the magic of perception-based solutions. When faced with lots of children scared about their MRI scans, an experience that’s vital for delivering essential care GE HealthCare tackled the perception, not the process. Rather than redesigning the machines themselves, which would have been costly and time-consuming, GE took a different approach.
They transformed the environment around the machines, turning MRI rooms into immersive adventures, pirate ships, space missions, jungle safaris. The machines didn’t change, but the children’s perception did. They were no longer patients, they were explorers. This simple shift in framing dramatically reduced sedation rates and improved patient satisfaction, all without altering a single piece of hardware.
It’s a powerful reminder that when perception is approached with empathy and intention, it can become a force for good, especially in contexts as sensitive and high stakes as children’s healthcare. That’s how you masterfully turn a scary scan into a swashbuckling quest for buried treasure.
Not all that matters can be measured
If there’s a pattern emerging from these perception-based solutions, it’s that they tend to be subtle, resource-light, and rooted in psychology, yet they often outperform more complex, heavily resourced solutions. Not always, of course but often enough to make designing for perception genuinely exciting. There’s a unique satisfaction in solving big challenges with minimal, well-placed interventions.
These are the kinds of solutions that become design school legends but in practice, they remain surprisingly rare. However, they could appear more often if effort went into actively seeking them out. That’s not to say perception-based solutions will ever become default. They’re challenging to surface. They often lie outside the design process, and many psychological in nature.
Biases like Maslow’s Hammer, Solutionism, and James C. Scott’s Legibility Bias steer us toward solutions that are big, measurable, and concrete, precisely the kind of thinking that causes perception-based solutions to be overlooked (another topic for another post).
Much of today’s design research still leans heavily on what’s measurable and objective, which is understandable, but in my experience, limited. I’ve lost count of how many times I’ve heard, “The user didn’t say that enough times,” or “The participant doesn’t say that exactly,” leading teams to focus only on what’s explicitly stated, while the deeper, underlying issues go unexplored. Even when the psychological angle is raised, it’s often quickly dismissed, due to its intangible nature and lack of objective measurements.
However, limiting ourselves to only what’s directly observable, we risk overlooking the hidden drivers of behaviour, the ones that often hold the key to truly innovative, human-centred design. I’m not saying designing for perception is the only way to design. In fact, I think it’s a critical addition to our existing approaches. It’s an untapped area of opportunity we can’t afford to ignore.