The Kano model is a great tool for adapting your product/service to the actual demand of your customer base, but it should be used with a degree of caution. It works very well when you already have some experience with the relevant market, but you need some data to drive your decisions, otherwise you won’t get much of a benefit from Kano as opposed to just making random choices.
Understanding Different Needs
The whole basis of the Kano model is splitting the needs of your customers into three categories, and organizing your work so that you can satisfy the needs that really matter in the grand scheme of things. However, this assumes that you can accurately categorize your customers’ needs, as using the wrong category can severely degrade the performance of your organization.
After all, if you believe a feature is of low importance, but it’s actually a must-be, you will obviously miss a huge opportunity to improve the initial impressions of your clients. And in the opposite case, if you spend too much effort on a feature that ends up changing nothing in terms of performance and reception, that’s a huge waste that will eventually drag down your organization.
Leveraging Old Data Sets
This drives us to an important point – if you don’t have preexisting data sets related to the specific product you’re developing, you may not be able to get a good overview of the different types of needs of its consumers. With that in mind, the initial development of the product’s very first version should be driven by a more experimental approach, although if you can draw on data from external sources, this can definitely be helpful as well.
And as you’re probably guessing, the data generated during this first run will be of critical importance later on if you want to continue working in that market and you want to make sure that your next product will be a noticeable improvement over the first iteration. How you’re going to record and store all that data is entirely dependent on the type of product you’re working on, and while some industries have established standards for data collection, retention and analysis, in some cases you’ll have to come up with your own custom implementation.
The Changing Nature of Needs
Another problem you may face in this context is that customers’ needs can change along with the design of the product itself. For example, you may unknowingly introduce a “must-be” feature, which then changes each customer’s perception of other aspects of your product. That way, in the long run, some features will move down in the table and will turn into indifferent needs, while something else might get promoted to a must-be feature.
That’s why it’s important to run regular market analysis on your customer and always be aware of their exact requirements and opinions. This is also necessary due to the volatile nature of most markets themselves, especially today in a time when the internet is making everything so dynamic and unpredictable.
The good news is that this system can also be very beneficial for collecting opinions and impressions from a large number of customers (both current and potential ones), and as long as you leverage your presence on the market correctly, you shouldn’t have any problems building a good model of your customers’ needs, and figuring out the exact direction to take your next product in.
The Kano model is a good framework for addressing many types of issues that arise in the development of a product, but it relies on preexisting data to make accurate decisions. If you’re developing an entirely new type of product or you don’t have much experience in its relevant market in the first place, you will need to do some groundwork before you can apply Kano effectively. Once you’ve gone over that barrier, you’ll find the model to work very well on a small scale as well as a large one, and it will give you a valuable insight into the way your company should work.