Is Kano Modeling Interchangeable with Maximum Differentiation?
Kano modeling and Maximum Differentiation (MaxDiff) analysis are excellent market research tools leveraged across industries, year in and year out. But when a client asks us if they are interchangeable, the short answer is usually, “No, not really”.
Of course, there are situations where you might get similar results. But consider using a flathead screwdriver on a Phillips-head screw; yes, it may get the job done, but there are better tools for the job.
So let's take a closer look at why these two great methodologies shouldn't substitute for each other.
Maximum Differentiation Scaling provides a simple, rigorous, and engaging means of ranking a set of items such as product features, claims, messaging, or experiential requirements. It is a variation of DCM (Discrete Choice Modeling) which arose as a direct result of increased computer power.
Items are experimentally rotated in sets. Respondents evaluate these sets, each with different items to choose from. The analysis returns both 'ranking' and 'relative importance.' You simply ask respondents which features are most important and least important (or valuable, compelling, motivating, etc.) to understand individual level relative preference across a large number of features, claims, or elements.
Dr. Noriaki Kano developed the Kano Model in 1984 to understand the concept of customer quality. It results in distinguishing between essential and differentiating features. The final analysis determines which customer requirements are more critical than others and the impact of these requirements on customer satisfaction.
According to the Kano Model, a product or service can have five types of attributes or properties that can satisfy or dis-satisfy customers:
Basic Features - Must-have requirements that, if not fulfilled, cause high dissatisfaction but have a limited impact on satisfaction. Think perhaps of a back-up camera on a new car which has moved rapidly from a performance/excitement feature to perhaps a basic feature now. Or of on-time home pizza delivery.
Performance Features - One-dimensional requirements that generate satisfaction proportional to performance. Increased delivery on these features increases satisfaction proportionally. Think perhaps of extra space for luggage on an airplane.
Excitement Features - Attractive requirements that generate positive satisfaction. Even if customers don't know they want these features, when they get them, they are delighted. Think of self-parking or lane change alerts on cars. Or additional exfoliation properties for cosmetics.
Irrelevant Features - Unnecessary requirements that do not satisfy or dissatisfy customers. We don’t want to be judgmental here, but example of this abound – a famous one might be square vs. rounded edges of a pizza.
Reverse Features - Unwanted requirements that cause high dissatisfaction. Think perhaps of the size of an airline seat in economy section or wait times on the phone.
Kano's most classic use is in experiential customer satisfaction. At its core, Kano says an element can be a dissatisfier or a satisfier. Let's use the airline industry as an example. Airlines can tank satisfaction with delays, packed flights, and minimal legroom. Alternatively, they can boost satisfaction by upgrading seats, providing real food worth eating, and keeping flights on time.
So, if both methods can prioritize elements or features… why aren't they interchangeable?
At first blush, it's an easy leap to assume that both methodologies are measuring the same thing: prioritizing elements and understanding consumer preference. They both might work pretty well, but they aren't the same tool and shouldn't be used for the same job.
The thing is, MaxDiff looks at product features, claims, or sets of elements that are generally positive. It is often used in product development to figure out what to add to a product or service.
When we conduct a MaxDiff analysis, we typically look at dozens of good things and want to know the top two or three that will resonate with audiences. Some aspects might have less utility or less resonance but they usually won't deter a consumer from making a purchase. It’s possible, but fairly rare for MaxDiff to be used when we're asking people to evaluate bad things that will have a negative impact (e.g. “Which of these make you the most Unhappy?”)
When our goal is to identify the best delighters, since MaxDiff will have people react to multiple measures of a delighter not just once but numerous times over, MaxDiff will better differentiate the cream of the crop, while Kano will identify those top features but not necessarily create space within them. So, given the simplicity of the exercise, when the business objective simply seeks to identify the top priorities or rank features, MaxDiff is the clear option.
However, Kano drills down on features or sets of elements that are positive and negative. It not only asks if this feature is irrelevant or less important but also asks if it dissatisfies consumers and pushes them away from a purchase.
When our business purpose is to identify and sort ALL the aspects of customer satisfaction AND dissatisfaction, Kano is a very good option. This isn't to say Kano is better than MaxDiff. It is simply a different tool with a different output.
Many years back in the auto industry, Kano received a lot of attention measuring dispositions toward different features, primarily to identify features or performance levels that would provide "surprise and delight" instead of merely meeting expectations. Some people thought they could identify features that would stand out better than required features (i.e., replace required items with 'bright shiny objects'). While it was interesting to understand these delighters, they shouldn't replace those items that are higher in priority. Besides, their effectiveness would be muted by missing requirements. In this hypothetical, focused on identifying the TOP Five elements for Ford to prioritize in an updated dashboard, MaxDiff will deliver clear results without the detractors they never really asked for.
When should we use Kano instead of MaxDiff?
This isn't set in stone, but typically Kano is better suited for experiential business objectives, whereas MaxDiff is better suited for feature optimization.
If we look at the service and hospitality industry, we can pull several helpful insights from a Kano Analysis. The more direct interaction there is with people, the more opportunity for something to go wrong. Kano can identify the experiences to promote, say heavier towels, and the things to always avoid, such as poor mattress quality. If mattress quality appeared at the bottom of a MaxDiff analysis, it doesn't mean it's a detractor; it just doesn't enhance the guest experience as much as the features at the top.
There are still many examples where a hotel, to use the analogy above, should run a MaxDiff analysis. Let's say the business objective is to identify service elements to prioritize and elevate. For example, leadership may seek to improve the corporate loyalty program or mobile-app engagement. We want a measure of the top priorities due to any number of constraints (time, budget, attention span) and don't need to focus on detractors. MaxDiff will clearly show what will increase appeal and engagement.
Operational data might show that something's off; lower occupancy rates, increased complaint volume, lagging in the market. When considering Kano and MaxDiff, the critical question is whether the Kano metrics provide additional context over MaxDiff prioritization for the goal being pursued.
Kano will be most helpful if your objective is to optimize the good and minimize the bad to reduce complaint volume. If you have a product or service deficiency that you need to get better at and have a limited budget to do only one or two things, MaxDiff will identify which items to focus on.
Should you run a Kano or MaxDiff study? Let's chat and find out.