Using the Kano Model to get product feedback

Priorities are essential for successful product development, and product feedback is one of the most important ways to orient those priorities.

The temptation to endlessly refine products can overwhelm developers, fixating them on efforts that don't actually translate to positive customer experiences. By gaining customer feedback before expending resources, you'll reveal clear signposts telling you which product features to focus on, which not to, and which might even catapult your brand to the limelight.

The Kano Model is one such way of collecting product feedback from customers and analyzing it for insight into which priorities will most likely translate to greater customer loyalty.

The Kano Model is a method of prioritizing product features based on the customers' needs and preferences. It works by scoring the likelihood that a feature will satisfy or dissatisfy customers and then comparing that score to the feature's development costs. With a Kano Analysis, DevOps teams can make wiser decisions about how to direct their efforts towards higher customer satisfaction.

Doing so involves breaking down various product features into feature type and determining how satisfying or dissatisfying they'll be for the users. Customer feedback sheds light on what aspects of a product are or aren't important to them, allowing researchers to quantify the value of the suggested features and more confidently choose which features to work on.

Skillfully applied customer feedback takes away much of the guesswork involved in prioritizing development tasks, where ideas easily become backlogged without objective measures of their value—and that's exactly the dilemma that sparked the creation of the Kano Model.

The origins of Kano Analysis: Dr. Noriaki Kano

In 1984, Dr. Noriaki Kano developed the Kano Model to learn what exactly influenced customer loyalty and satisfaction. An engineer by training, he noticed there was a wide disparity between how much effort goes into developing a product feature and whether that feature actually affected customer loyalty.

Dr. Kano began by investigating how customers assigned value to different product features. By analyzing exactly which product features increase customer satisfaction and why, Dr. Kano created a method for directing product-development efforts where they'll do the most good. His findings served as a convincing argument against the trend in the '80s of tactlessly trying to improve every aspect of manufactured products.

Today, the same principles are more relevant than ever. Digital products have even more potential for bottlenecked efforts—and good project prioritization is often the deciding factor between success or failure for businesses at any scale.

The Kano Model is a straightforward way to clarify which features your customers need, want, and don't want. Simple though it is, knowing how much value customers place on different features is essential for deepening a product's impact on its market.

It can also improve company-wide operations, giving each team member tangible proof of which efforts are and aren't useful to the one group that matters most—your end users. 

For almost 40 years, product designers, manufacturers, and development teams have been using the Kano Model to direct their efforts more wisely. It's extremely versatile, and for any product-driven industry, a Kano Analysis can provide company-wide benefits:

• Helps product teams rank their priorities

• Greater simplicity than most other prioritization models

• Quantifies user experience research (UXR)

• Less risk of Analysis paralysis

• Gives companies a more responsive and competitive edge

• Higher confidence in project decisions

• Provides customers with more of what they want

• Improved decisions and use of resources

Because the Kano Model attaches a value to each product feature, it's useful whenever there's uncertainty over which features deserve the development team's time. Kano Analyses quickly dispel confusion over which product features are most important to customer satisfaction, brand loyalty, and the company's bottom line.

They also simplify research prioritization, such as when backlogged design and prototyping work becomes overwhelming, leaving you unsure which efforts have the most value.

You might also consider a Kano Analysis when:

• You're considering investing labor into new, unproven features

• Development teams have limited time and resources

• The project pipeline becomes clogged

• Developer efforts seem diffuse and poorly directed

• Customer satisfaction levels keep fluctuating

• Complaints broadly increase, and you don't know where to begin

Compared to other product management frameworks, the Kano Model is quite simple. It begins by grouping product features into categories based on how important those features are to the product's:

1. Basic use

2. Performance

3. Excitement

If desired, the study can also account for features your customers feel (4) indifferent to or (5) dissatisfied about.

With market research, each of the features are assigned satisfaction levels. These generally fall under:

• Satisfaction

• Delight

• Indifference

• Dissatisfaction

More exact levels of satisfaction can be measured (such as with a multi-choice answer form). But the end goal is simply to identify the features that will create the highest level of customer satisfaction and delight with the lowest investment.

Altogether, these simple but powerful insights speak volumes about which development efforts will likely pay off and which won't. When almost countless labor hours go into creating, testing, and deploying a given feature, it can be edifying or crushing to learn just how well those efforts translate to customer success! Yet these are crucial insights into how to hone your product, and your entire company, into something customers will love.

What are the Kano Model feature categories?

Dr. Kano broke features down into five categories, with three relating to customer satisfaction and two relating to dissatisfaction. First, the categories for satisfaction:

1. Basic (threshold) features. Those which customers expect, seeing them as minimum standards for a working product. Customer delight is not a realistic expectation here, where the goal is more about sating your customers' minimum threshold for satisfaction.

2. Performance features. What customers normally look for to differentiate brands, such as greater speeds or some other spec. Generally, performance features satisfy customers in proportion to how much developers invest in them. Because of this linear relationship between cost and satisfaction, Dr. Kano calls these "one-dimensional" features.

3. Excitement features. While customers may not expect them, excitement features are seen as a bonus, dramatically raising the product's value to them. These are highly attractive features, and they're more likely to delight customers disproportionately higher than the amount invested. And the last two categories, which relate to unsatisfied or dissatisfied customers:

4. Indifferent features. Those features which, whether they're included or removed, don't impact overall customer satisfaction. Knowing this can free up developer time for more fruitful efforts.

5. Reverse Features. The features that outright dissatisfy customers—or those that satisfy customers when they're specifically not included.

These categories are plotted onto a basic four-quadrant graph, with "dissatisfaction" at the bottom of the Y-axis and "delight" at the top. Along the X-axis is the "execution" level, ranging from "poor/nonexistent" on the left to "excellent" on the right. You can measure execution according to how many resources were or will be used, such as time and labor costs, or some other measure of company investment.

The natural decay of delight

Satisfaction levels naturally fluctuate, and product management consultant Daniel Zacharias coined the term "natural decay of delight" to refer to how exciting features often eventually become expected. On the graph, this would look like customer feedback falling from the upper right (excited about excellent execution) to somewhere more in the middle (basic satisfaction) instead.

Applying the Model

Applying the Kano Model effectively is easy if you take it one step at a time:

• Step 1: Choose your target features and users, then place each feature into one of the five categories above.

• Step 2: Through surveys or other customer-feedback methods, gather the best possible data from your customers to determine which features will satisfy them and by how much.

• Step 3: Analyze the results by compiling the feedback and comparing features with each other and to their investment costs.

To stay ahead of the "delight" curve and improve customer experience, companies must take proactive actions in response to their Kano Analysis. This could include:

• Improving products and services

• Refining buyer persona traits based on research

• Conducting a benefit vs. cost modeling study of the most important features

• Using Kano data to positively influence your Net Promoter Score (NPS) and customer reviews/feedback

A Kano Analysis can inform your product roadmap in endlessly nuanced ways. To begin with, focus on the following fundamentals:

• Free up resources by stopping work on all "indifferent" and "dissatisfied" features

• Maintain satisfaction levels by prioritizing all "basic/threshold" features

• Boost satisfaction by prioritizing as many "performance" and "excitement" features as possible (but not at the cost of the basics)

When using the Kano Model, be aware customers may not always be as interested in a feature when it's finally presented to them as they said they would in the survey. They can't know with 100% certainty how they'll feel in the future.

The Kano Model also walks a very narrow line between true quantified vs. qualified data. For instance, some common response selections in the surveys may not be mutually exclusive (meaning a customer could want to give multiple answers to the same question but only enter one). Customers might state that they are "excited" about a performance spec (like higher storage space), blurring the lines between categories.

Developers may also add to the confusion without clear definitions of "excitement" and "performance" categories—does everyone agree on what makes a feature "high-performance" vs. "exciting"?

As one of many product research models, the Kano Model is unique for its focus on how customers will likely react to features. For more nuanced priorities, other product-research frameworks may be in order. But if the sample size is large and trustworthy enough, the Kano Model may be perfect for its simple and broad overview.

When customer satisfaction is the highest priority and subjective feedback is acceptable, a Kano Analysis can help your development team take better aim and find greater traction in their marketplace without scrutinizing details.

The Kano Model's feature categories are:

1. Basic (threshold) features—needed for the product to work

2. Performance features—those that make your product work well

3. Excitement features—what makes your product more attractive than the competition

4. Indifferent features—unnecessary, but not likely to turn customers off, either

5. Reverse features—things that leave customers dissatisfied

These are the first three of five main categories, which represent customer satisfaction or delight:

1. Basic, obligatory features

2. Good performance

3. High excitement

By extension, you might consider the other two categories "need nots."

After assigning features to categories and obtaining customer feedback, you complete a Kano Analysis by compiling and interpreting the results. The features can be assigned values, which developers use to prioritize their efforts.

Kano Analyses are made for comparing multiple features. Here are some examples for each category:

1. Programs and apps that don't crash devices are considered basic features—excessive glitches are not tolerated.

2. Higher storage capacities, encryption, and 2FA for cloud-based storage services are common performance features. They make a product more competitive, and the feature's value is directly proportional to how much developers invest into it.

3. Tier-based service bonuses and popular, novel features are exciting features. Note that these features can gradually become expected, as the bar for excitement rises over time.

4. Free service for a promotional product customers aren't interested in is inconsequential to the users' experience; thus it's an indifferent feature. It won't attract customers, but it also won't turn them away.

5. Slow load times, disruptive ads, and spyware are common types of reverse features. They dissatisfy users and actively deter them from using what otherwise may be a good product.