受行为地翻译家赫兹Berg的双要素理论的启发，东京(Tokyo卡塔尔(قطر理文大学传授狩野纪昭(Noriaki Kano卡塔尔和她的同事Fumio Takahashi于一九七八年三月刊登了《质量的爱护因素和刺激因素》(Motivator and Hygiene Factor in Quality卡塔尔国一文。
Indifferent Features 无异功效
Curve 1: Desired Features
Remember when I said more isn’t always better? Well,sometimesit is it is. More storage space or battery life is better. Faster download speeds? Better. These are all examples of where the user will usually express greater satisfaction in direct proportion to how much of the feature they get.
With desired features, satisfaction is directly proportional to feature implementation
In the case of Crunchrr, desired features could be:
- Speed and responsiveness
- Number of users to connect with
- Suggestions based on stated preferences and past browsing behavior
- Options for quickly zeroing in on a kind of cereal (sorting, filtering, etc.)
- Size of cereal selection
Curve 4: Indifferent Features
These are features the user simply doesn’t care about either way. Whether they’re implemented fully or not at all, they won’t change users’ opinions about the app, or change how they use it.
Neutral features don’t affect satisfaction one way or another
The Kano Analysis
A Kano Analysis is cheap and easy to perform and provides clear vision into what users actually want and expect from your product. It also provides hard data, which breaks everyone out of the trap of biased or shortsighted thinking. There’s no need to argue and debate with internal stakeholders about which features are in or out. The numbers don’t lie!
Brian O’Neill @brianeoneill is a designer in the San Francisco Bay Area, currently at NVIDIA.
These curves go by many different names, depending on the source. I picked these names arbitrarily. In the end, it doesn’t matter what they’re called.
A Better Way Discover What Users Really Want From Your Product
by Brian O'Neill
You’re on the design team for Crunchrr, a new app that helps users discover cereals they’ll love. Users can:
- Create a profile and connect with others
- Discover cereals based on their preferences
- Rate and review cereals
Crunchrr is in the hands of some early adopters who are loving its core features. Things are going great. That is, until the requests start rolling in.
Annelise from marketing says: “Crunchrr needs a map view so users can see where each cereal is made. People are really interested in where their food comes from nowadays, so this is really a must! Besides, every app has a map view.” Kevin from sales was at a meeting with a potential advertiser who asks: “Where’s the chatbot? You can’tnothave a chatbot. Conversational UI is the future!”
One of your early adopters pings you to suggest: “There should be a button so I can email the cereal maker to request a gluten-free version.” Another one says: “Maybe there could be something like Shazam for cereal. That way, if I’m in a restaurant I can take a picture of what the person at the next table is eating and it’ll show me what that cereal is.”
The next thing you know, your backlog is a gaggle of suggestions, requests, and demands. It seems that everyone has brilliant idea that justhasto go into the next release.
This can’t be avoided. Everyone has an opinion and given the opportunity, they’ll express it. And people easily fall into a “more is better” mentality. More features equals a better product, and the more of each feature, the better.
The obvious problem is that you can’t deliver on every request. Not only that, but all ideas aren’t created equal, and users are often at a loss as to how to articulate what they really want and need. On the other hand, internal stakeholders tend to view features in the narrow context of their own interests. How do you stop the madness?
“The most important thing that a team can do to help their design is to say no to almost any idea for a feature”
— Jared Spool
You need a way to predict user satisfaction that lets you prioritize feature releases and even re-evaluate existing features. And you need hard data to support your decisions about what goes into Crunchrr and when. That’s where theKano Modelcomes in.
今日在Medium看见风流洒脱篇用研方法的介绍—— 卡诺模型（The Kano Analysis）。用于深入分析多少个产物成效是不是能使客户知足，这种艺术的亮点是能搜查缉获多个活生生的数量结论，匡助决策。总括办法也挺轻巧的，问卷操作也正如便于轻易，费用非常的低。笔者本身特别向往这种能便捷验证的低本钱措施，能在有限的日子与人力财富条件下，也能高效得出可信的数据参谋与清丽的结论。正如自个儿上大器晚成篇小说介绍的方式肖似，能大大进步调换功能，降低无谓的口角。本办法对效果与利益的四种划分也蛮风趣，让自己回想锤子科学技术，锤子的无绳电话机正是特别讲究软件上的Delightful Features而忽略任何硬件上的Required Features。那就刚刚表达了怎么锤子销量与认识度不成正比。
Anti-feature Features 反向效能
艺术运用问卷提问的不二秘诀募集数据，最终通过数量整合得出三个功能的五个全面：知足周详Satisfaction Coefficient 与 不向往周密 Dissatisfaction Coefficient。假设知足全面超过不顺心周密，该成效值得做。
以下是原著内容 Let's Go：
Curve 2: Required Features
Required features are the ones users expect and take for granted.
With required features satisfaction levels off once the basic need has been met
Users are dissatisfied when a required feature is not present and satisfied when it is. But that satisfaction levels off after a certain point. This makes sense when you think about it. If a wheel doesn’t roll, it will cause dissatisfaction. If it does roll, it will cause satisfaction. But it’s hard to get anyone excited about a wheel that rollsreally, reallywell. In the case of Crunchrr, as with most other apps, this could mean things like:
- Reliable uptime
- Ability to create a profile
- Easy log in/out
Curve 5: Anti-features
Anti-features are the features that users actively dislike. (Remember Clippy?) And the more these features are implemented, the greater the dissatisfaction. Anti-features are like the mirror opposite of desired features.
Anti-features are the ones that frustrate or annoy users. Dissatisfaction is directly proportional to implementation
Curve 3: Delightful Features
Delightful features are the ones that make an app fun to use and give it a personality. They’re the features you love, but don’t expect. It could be as simple as when the login form appears to shake its head when you enter the wrong credentials. Or it could be the tone of the writing or a fun mascot character or some unique interaction.
Users are satisfied with delightful features, but are not dissatisfied when they are absent
As you can see from the graph, users express increased satisfaction with delightful features. But there’s no dissatisfaction when they’re not present. Also, as with required features, there’s a limit to just how delighted a user can be. After a certain point, there are diminishing returns.
Annelise’s map view is probably an example of a delighter because it’s little more than eye candy, and it certainly isn’t solving any of the currently defined business needs for Crunchrr.
Delightful features are an important part of the user experience, and shouldn’t be ignored. Butthey come with a shelf life, in part because they’re so easily imitated. For a while, the swiping interaction was a big part of Tinder’s unique identity. Now, Tinder is justone of many appswhere users can swipe left or right. In other words, over time, delightful features go on to become desired or even required features.
Required Features 必备成效
Putting it All Together
Looking at all of these features together not only provides a clear pictorial representation of how features will be perceived, but also helps you figure out strategic direction.
The complete Kano Model diagram
Desired Features:Resources should be invested heavily in these features, because they are key to user adoption and retention, as well as competitive advantage
Required Features:Resources should be invested heavily in these features, but only until basic needs have been met.
Delightful Features:It’s fine to invest resources here, but not at the expense of desired and required features. However, delightful features are often key differentiators that can build loyalty and buzz.
Indifferent Features and Anti-features:Resources should be invested only in identifying these so as not to waste cycles on building and implementing them.
By now I hope you’re sold on the Kano Model. Then the next question is: How do you find out which features belong to each category? That’s where the Kano Analysis comes in.
Delightful Features 魔力功效
After you’ve aggregated all of the responses, you’ll calculate the satisfaction and dissatisfaction coefficients. The satisfaction coefficient is a number between 0 and 1: the closer to 1, the stronger the influence on satisfaction. The dissatisfaction coefficient is a number between 0 and -1: the closer the closer to -1, the stronger the influence on dissatisfaction. We calculate the coefficients with these formulas:
Let’s say that the aggregated responses for the map view breaks down like this:
That would give you these results:
Satisfaction: (4 5) / (4 5 12 23) =0.2045
Dissatisfaction: (5 12) / (4 5 12 23) * (-1) = -0.3864
As you can see, the map view feature is having a significantly stronger influence on dissatisfaction than on satisfaction. This clearly indicates that we should leave it out of Crunchrr. Sorry, Annelise! (Actually, if you saw these results in the real world, you wouldn’t even need to calculate the coefficients. Seeing 31% anti-feature and 25% questionable is enough to tell you not to include this feature. I used these exaggerated figures to highlight the differences produced in the coefficients.)
Other times, the coefficients will show little difference in influence. Cases like those will require a judgement call or re-testing.
The Kano Analysis
To find out which features belong where, we need to ask our users. But remember, users are not usually great at identifying or expressing what they really want and need. The Kano Analysis accounts for this by asking questions in pairs: afunctional questionfollowed by adysfunctional question. Let’s go back to Annelise’s suggestion of a map view for Crunchrr. We could ask a question pair about this feature like this:
If Crunchrr let you see on a map where a brand of cereal is made, how would you feel?
If Crunchrr did not let you see on a map where a brand of cereal is made, how would you feel?
For both functional and dysfunctional questions, users must choose one of the following answers:
- I like it that way
- I expect it that way
- I am neutral about it
- I can live with it that way
- I dislike it that way
You would prepare an entire questionnaire in this style for each of the features in your backlog. Each user’s answers can then be analyzed by plotting its outcome in the following table.
The analysis table tells you where a user would place a feature in the Kano Model based on how the functional and dysfunctional responses compare
It should be clear that if a user likes it when the feature is present and dislikes it when it’s not, then that is a desired feature. The designation ofquestionablehappens when the answers apparently contradict each other. (This is often the result of the user not understanding the question.)
Great. We’re almost done. The final piece is to aggregate all of the survey responses to find the overall results for each feature. (Alternatively, you could break this down even further and aggregate responses based on personas.)
Desired Features 期待功用
The Kano Model
In 1984 professor Noriaki Kano presented a model that predicts how satisfied people will be with a product based on its features. Since then, the Kano Model has become a standard design tool because of how effectively it can make typically invisible ideas about quality visible. The core principle of the model is that satisfaction can be plotted along five distinct curves.