Uncovering customer segments

Segments are about understanding what is valuable to who

The Kano method was created to assess how customers perceive the value of a product's features. It's therefore only natural that a Kano study surfaces the differences between customers in value perception. In other words, a Kano study can help you find segments in your customer base.

Tension between a feature's categories signals segments in the customers who responded to your survey can be segmented.

I once researched the roadmap for an administrative software tool. One particular feature had a 50/50 split between Indifferent and Must-Be. The other features were less split, but there was tension between the categories.

I re-ran the analysis for the people who were in the Indifferent camp and for the people in the Must-Be camp for that one 50/50-split feature. It turned out that the answers per camp for each feature were very similar, meaning I had found two segments that perceived the product's features differently.

Because I had done a live survey, I had notes about each surveyee and found that digital proficiency separated the two segments. The answers of digitally proficient people were very similar to those of other digitally proficient people and vice-versa.

This was an important insight for the company I worked for. They had been thinking of creating different product versions, catering to different audiences, but could not decide what features to offer in the different tiers. Knowing on what parameters their customer base was segmented helped them make a decision about the different product tiers.

The Kano method can help you find the segmentation criteria that matter to your product. Typical segmentation criteria, like demographics, often don't correspond with segmentation based on perception of value. It's dangerous to base product decisions on unfounded segmentation criteria.

Experienced and novice users

As discussed in the chapter on selecting survey participants, studies show that results will often differ between customers who are long-time users and novice users.

To understand why segments bubble up in your analyses, it's best you know who is completing your survey. Live surveys, or adding extra questions to your survey, can help you there.

But if all you have are the results, and there is tension between the feature categories, it can be helpful to try and segment the results into experienced versus novice users. Chances are you'll see more coherent results within each segment. You'll better understand the reasoning behind each segment's feature categories too.

Consumption goals

If you can, find out from your surveyees why they are using your product. Studies show that the amount of "skin in the game" has a strong influence on product attribute value. For example, consumers of an appetite depressant attach a different value to its features based on how motivated they are to lose weight. Their consumption goal (no pun intended) is different: some people have to lose weight for health reasons, some people just want to lose a few pounds before the summer season. Consequently, they'll attach different levels of importance to the features of the product.

Read Ponam 2011 again.

• Understanding what is valuable to who

• Cf Word: only 20% of features are used, but not every customer uses the same 20%!

Eg - people who thought Instagram filters were annoying vs users: https://www.pcworld.com/article/253254/why_is_instagram_so_popular_.html

Also, see Materla

Mittal ski's

B2B customer platform example (large and small)

Certainly use Ponam 2011! "Surprisingly, however, prior studies have not addressed the issue of market segmentation."

Mittal 2001: