Why the Kano Model is a Game-Changer for Product People
As product people, we talk a lot about “Wow! Moments”, “Aha! Moments”, and “Delighters”. But how often do we stop to question exactly how we determine what that should be and for whom? The same applies to the prioritization and categorization of the rest of your features. Are we using generic frameworks to help guide the process? Or worse yet, are we simply choosing features based on unstructured qualitative data (e.g., general user feedback)? Yeah, no, we can do better. So let’s do better together.
Also, I can’t think of a better time than the present to improve our product expertise because, let’s be real, we are living through a very cutthroat and highly competitive environment in tech, and everyone is under pressure to create value for your end-users all the way to your board members. Any bit of strategic advantage can make a big difference.
With that in mind, I decided to dive into the Kano Analysis Model. I’m a big fan and I believe everyone can benefit by adding it to their product toolbox.
Why do I like the Kano Model so much?
Three main reasons:
Deeper User Insights
Whether you’re on the product team, design team, a product manager, a product designer, or even a founder, this model forces you to dig deeper into your user base. For it to be effective, you have to go beyond the surface, diving into the nuances that make your users unique. Here, we move beyond the typical "getting to know your users" approach and focus on truly understanding them at a deeper level. It’s about recognizing their individual likes, dislikes, and even the little quirks that set them apart. With this insight, you can segment your users more precisely and, even better, align those segments with your key business goals. This allows you to focus on the users who matter most—the ones driving real impact. After all, not every user influences your metrics in the same way.Designers Be Like: “Delight and Surprise!”
It’s an easy-to-use mechanism that brings us designers back to our roots of the “delight and surprise” mantra. Who doesn’t want to evoke this type of human emotion? In a time when data-driven decisions can sometimes overshadow creativity, the Kano Model is a reminder that design is about making people feel something!Versatility Across Company Stages
This qualitative model isn’t just for startups or early-stage products. It’s versatile enough to be used in all stages of a company’s lifecycle. Whether you’re launching a new product for a handful of early adopters or refining an established product for millions of users, the Kano Model has a place in your toolkit.
Alright, let’s get into it. First, a little background of its origin followed by the fundamentals.
Dr. Noriaki KANO
Origin of this theory
In 1984, Dr. Noriaki Kano, a professor of quality management at the Tokyo University of Science, revolutionized the approach to customer loyalty. Before his groundbreaking work, companies primarily focused on resolving complaints and enhancing popular features to improve loyalty. Dr. Kano challenged this notion, arguing that customer emotions played a crucial role in loyalty. He identified five distinct emotional responses to features and developed the Kano Analysis Model. By leveraging this model, companies could allocate resources strategically, prioritizing features that genuinely resonate at an emotional level with users and drive loyalty.
What it is
The Kano Model is a powerful tool for understanding what really drives user satisfaction. It breaks down how different product features impact users—whether they see them as must-haves, performance enhancers, delightful surprises, or even “sus” (as Gen Z might call them). By using the Kano Model, you can prioritize the right features at the right time, ensuring your product isn’t just meeting expectations, but also creating moments of surprise and delight where it matters most.
Five Emotional Response Types
These five categories are mapped on the Kano quadrant, with each category type plotted against customer satisfaction on the Y-axis and the level of feature implementation or functionality on the X-axis, showing how each feature influences user experience from dissatisfaction to full-on delight.
Must-Be features follow a low curve. Users expect them, so even when well-implemented, they don’t increase satisfaction much. But if they’re missing or poorly done, dissatisfaction hits fast.
Performance features have a linear relationship—better implementation means higher satisfaction. If these are done poorly, users are dissatisfied; if done well, they’re happy.
Delighters start at neutral or indifferent but have an exponential impact. When fully implemented, they surprise and delight users, creating a much higher level of satisfaction than expected.
Side note- A really fascinating thing about Delighters is that they often have a limited window of impact before they transition into Performance or Must-Be features, or they become irrelevant if not maintained. Notice how I listed Dark Mode as a Must-Be feature. Did you know this was once-upon-a-time a Delighter? Yep, and then it became more widespread. That initial curve started to drop as the feature shifted from one category onto another. This shift highlights not only that user expectations evolve but that the competitive landscape plays a significant role here. It’s why it’s so important to stay tapped into your user base as their evolve so you can continually aim to delight them and gain a competitive advantage.
Indifferent features sit almost flat on the chart. Whether present or absent, they don’t move the satisfaction needle much.
Reverse features actually cause dissatisfaction for some users as implementation increases, making them polarizing or "love it or hate it" features.
This diagram is a guide, a visualization to help you visualize the impact of your categorized features. It’s not meant to be used as a plotting mechanism. Just making sure that’s clear.
So, what comes next?
User segmentation
User segmentation is key to making the Kano Model truly impactful for your product. By understanding the unique needs and expectations of different user segments, you can better tailor features that resonate, and leave out the stuff that won’t.
In the next post, I’ll walk you through how to effectively segment your users and put these insights into action, using real-world research data as examples. Stay tuned!
