Kano Model Template

If you're planning to running a Kano model survey, you may be thinking - "how do I actually analyse the results?"

Maybe you're thinking of using a spreadsheet like Excel, so you're looking for a template you can use.

The good news is that it's definitely possible.

The bad news is that it's not that easy.

The trouble is that everyone's result data is in a different shape so it's hard to fit it into a standard template. If you need to make any changes to the template (which you probably will need to) then you need a good understanding of spreadsheet functions like INDEX, MATCH, VLOOKUP and so on.

Then you have to copy and paste your data into the sheet in exactly the right format (and hope that you don't make any mistakes while you do it!), and as new results come in you have to do more copy/pasting to update the analysis.

And in the end the analysis tends to be very basic because of the limitations of spreadsheets for this sort of task.

In short...

With that said, below I will show you how to set up a simple Kano model template to do the categorisation for you. This should help you better understand how the Kano technique actually works, and should be enough for simple projects or demonstrations.

The screenshots show Google Sheets but you could use Excel or any other spreadsheet tool you prefer.

Step 1

Create a new sheet, and add three tabs - "Categories", "Data", and "Analysis".

Step 2 - the categorisation table

In the "Categories" tab, create a table like this that matches pairs of positive and negative answers together to give a category. There are several different versions of this table, with different people taking slightly different interpretations. You're free to make adjustments to suit your own interpretations of course!

Have a play with our interactive Kano categories tool to get a good understanding of the mappings.

Step 3 - copy/paste the results

Next in the "Data" tab enter your results. These are the pairs of positive and negative answers that you received from your survey respondents, grouped by feature. Add more groups of columns going across for each feature you tested. Leave one column blank per group - we'll add a formula to that next.

Step 4 - categorise the responses

We need to fill in the empty "Category" columns now. We're going to use the INDEX and MATCH functions to find the right entry in the table. Mine looks like this:

=index(Categories!$C$3:$G$7, match(B3, Categories!$C$2:$G$2, 0), match(A3, Categories!$B$3:$B$7, 0))

Copy and paste this into every cell in category column. Change the A3 and B3 to match the columns for that feature group. Now each feature in each response will have a Kano category against it!

Step 5 - count the categories

We evetually want to find the primary category for each feature. We do this by counting the categories that were assigned in step 4.

In the "Analysis" tab, create a table as in the screenshot above with features across the top and categories down the side. The bottom row will hold the primary category - the one that comes up the most in the responses.

Now we need another formula. Enter this formula into all the boxes in the upper table:

=countif(Data!$C:$C, A2)

Change $C:$C to match the column with the categories for that feature, from the "Data" tab. So column C is feature 1, column F is feature 2, column I is feature 3 and so on.

A2 refers to the name of the category, so that should match the row that you're counting - A2, A3, A4 etc.

You should get a table like this:

Step 6 - find the primary category!

Finally we can find the primary category for each feature. Enter the formula below into the bottom row of each feature, adjusting the G to match the column you're entering it into. This will find the highest value in that column and then find the name of that category.

=index($A$2:$A$7, match(max(G12:G17),G12:G17,0), 1)

And there it is, the final answer - the primary Kano category for each feature.

Summary

You now have your own simple Kano model template (Google sheets or Excel or whatever you used). Here's my version so you can see a working version or make a copy to tweak for yourself.

But it took a lot of fiddling to set up, some coding knowledge and the analysis is pretty basic:

Having just a single primary category isn't quite the full picture. Sometimes you'll get a split decision between two primary categories, sometimes you'll get a winner but only by a tiny margin, or sometimes you'll get results where there's no clear winner at all!

Our tool solves all these problems and gives you much more insight into your results. We use statistical significance calculations to find the real winners, and show levels of confidence against each result so you can be sure.