Uncover Voice of the Customer with Kano Framework. Practical guide

Businesses want to capture and continuously grow the demand for their products, want them to live long and prosper lives and be valued by the customers. Users, in turn, expect the software products to solve their problems, address their needs and wants in the effective, efficient and elegant manner.
That said, businesses can acquire a sustainable demand for their products only by solving real problems of real people.

Though, to thrive, businesses also need to care about keeping customer satisfaction and loyalty high. And there’s only one way of doing it right — listening to the Voice of the Customer.

Kano Framework is one of the techniques that call on the users to speak and help businesses to uncover the Voice of their Customer.
Applying the framework allows to identify and distinguish between essential and differentiating product features, rank and prioritize requirements, and make better decisions in trade-off situations.
The practical employment of the Kano Model includes the following steps:

1. Selecting users to participate in the study.
2. Selecting features.
3. Preparing questions.
4. Conducting a survey.
5. Analyzing the results.

#1. Selecting users to participate in the study

As a part of the study, you want to survey several people representing your target audience and then look for the trends in their answers. But your target audience is not homogenous, and what they think about your product won’t be either. So surveying your users “as-is” would result in getting a diversity of answers to the same question about the same feature, which would be of no help in the understanding of what’s trending.
That’s why you need to segment your user base first: reveal similarities (demographic, behavioral, social, etc.) and arrange your users into groups.

Definitely, you can apply multiple segmentations to your target audience. And the idea is to choose one that makes the most sense in the context of your product because reasoned and well-thought-out segmentation very positively impacts the accuracy of the study.

Bottom line, within this step in preparing for the study, you need to segment your target audience (or carefully revise the existing segmentation) and then select several representatives from each of the derived segments.

Ideally, you should have done the segmentation long before validating your product features with the users. The right time for this would be when working your business model through. Personas, empathy maps, customer journey maps, etc. — build whatever you need to better understand your target audience.

#2. Selecting features

You need to identify which features to test for each user segment:

• Select only features that deliver value and meaningful benefits to the users of each segment.
• Leave your internal backlog aside: tech tasks, design refreshment, internal logging and reporting, back-office functionality, etc. aren’t externally tangible and are therefore out of the scope of Kano Analysis.
• Limit the number of features. Don’t attempt to test “everything at once” — it’s time-consuming and will exhaust your users. Exhaustion, in turn, lowers concentration and attention, which may lead to vague and inaccurate answers.
• Accompany each of the selected features with whatever details you have: sketches, mockups, interactive prototypes, charts, etc. The more informative your input is, the more accurate the feedback you will receive from the users.

#3. Preparing questions

There are two questions you need to ask your users about each of the selected features: how they feel if they have the feature (functional question), and how they feel about not having it (dysfunctional question).

The combination of these two questions helps to avoid bias responses and inconsistencies and allows to identify the type of requirement.

• It’s important that each pair of questions stands for a single product requirement.
  So if a feature is complex and incorporates multiple requirements, it would be better to break your questions down.
• Phrase the questions from the perspective of value and benefits for the users, avoid technical descriptions.
  For example, “How do you feel if once created, your invoices will get automatically converted to the .pdf format and saved to your personal folder?” is better than “How do you feel about having a PDF converter for invoices?”. The accent is on what is in this requirement for the users: automatic conversion and storing would spare them some time.
• Express the functional question in a positive way, and dysfunctional — in a negative way.
  Note that the dysfunctional question isn’t always the opposite of the functional one, it just declares the absence of functionality.
  For example, “How do you feel if once created, your invoices will get automatically converted to the .pdf format and saved to your personal folder?” (functional) and “How do you feel if there’s no automatic conversion to the .pdf format for your invoices?” (dysfunctional)
• Make your questions clear and unambiguous so users can understand them without assistance (or at least with minimal assistance).
• If possible, test the questions in advance (e.g. with your colleagues) to ensure they are clear and easy to understand.

#4. Conducting survey

Next, you need to survey your users about each of the selected product requirements.

Kano questionnaire (a pair of functional and dysfunctional questions) isn’t open-ended and prescribes a very specific set of options as possible answers:

• I like it
• It must be that way
• I don’t care
• I can live with it
• I dislike it

The possible answers need to be presented in this exact order, falling along the scale from pleasure to avoidance of displeasure.

You can put the questionnaire in the grid as suggested below:

#5. Analyzing the results

Now it’s time to infiltrate all collected feedback through the evaluation table which correlates answers to the functional and dysfunctional questions into a final category for each product feature:

• D — Delighter
• M — Must have
• P — Performance
• I — Indifferent
• R — Reverse (users absolutely don’t want this feature and strongly expect the reverse)
• Q — Questionable (contradictory results which cannot be categorized)

The generally accepted approach would be to interpret results based on the answer frequency in the context of each user segment:
1. Categorize answers using the evaluation table.
2. Count the total responses in each Kano category for each feature: the category with the most responses will be the final feature category.
For instance:

Though, it’s recommended that if (P+D+M)>(I+R+Q), the max value of (P, D, M) should be adopted. Otherwise, the max value of (I, R, Q) should be used.

If results fall into multiple categories without clear prevalence, and you can’t assign a final category to a feature, most likely there is a hidden user profile that you didn’t consider in your segmentation. In this case, you need to revise the collected responses and search for the patterns in order to derive the missing segment. Then, you’ll be able to make the “go” or “no go” decision for that segment depending on its size and strategic importance for your product.
If you conclude this segment is a few (compared to the others) and/or isn’t strategically beneficial for your product, you may want to exclude the results of the respective users from the study and work with what’s left.

From the evaluation table, you can grade features based on their importance and overall score they’ve got from the users (answer frequency). If several features have the same score, it’s recommended to choose the category that has the greater impact on the product, with the priority order being M > P > D.

In closing

Although Kano Analysis is terrifically useful for identifying the product features that might influence ultimate customer satisfaction, you need to remember that it’s never a replacement for the usability studies, customer interviews, focus groups, and iterative design process.

Apply it carefully, as it matters not only what you deliver to the market but also when you deliver. The amount of effort it takes to prepare to and conduct the study, and then analyze the results is quite significant, so you need to decide to what extent you actually want it.

Therefore, before jumping into the study:

• Think of how much time you are ready to dedicate to it.
• Consider optimizing the number of participants: the more people you involve, the more time you’ll need for surveying them and analyzing the results.
• Consider optimizing the set of features you’d like to present in the study.
• Think of how far you want to go with the analysis of the data gathered — would you like to wrap it up with uncovering the main trends or would you like to go further and investigate all the inconclusive and puzzling items in depth?

Or hire the external experts, so they’ll do it all for you ;)