Kano Model Analysis: Step-by-Step Guide & Survey Template

Kano Model Analysis: Step-by-Step Guide & Survey Template

What is Kano Analysis?

Imagine launching a product packed with features you believe are essential. But will they truly resonate with your customers? This is where Kano Analysis, a powerful tool developed by Professor Noriaki Kano in the 1980s, comes into play. It goes beyond simply ticking off features on a list because it taps into the emotional connection you have with customers.

Kano Analysis goes beyond the surface-level question of “what do customers want?” It digs deeper, exploring how features make customers feel. Through well-designed questionnaires, it categorizes features based on two key factors: customer satisfaction and feature implementation. Think of it as a strategic roadmap, guiding you towards functionalities that maximize customer delight while optimizing resource allocation.

Use cases of Kano Model

The Kano Model is versatile and can be applied in various contexts to enhance product development and customer satisfaction strategies. Common use cases include:

  • New Product Design: Understanding user preferences to create new technological products with features that align with customer expectations.
  • Feature Enhancements: Prioritizing software updates based on what users find delightful, necessary, or unneeded.
  • Service Improvement: Enhancing service offerings by identifying key drivers of customer satisfaction and areas of potential improvement.

By understanding which features are essential, desired, or unnecessary, businesses can tailor their offerings to better meet customer expectations and drive loyalty.

How Does the Kano Model Work?

The Kano Model is often depicted through a visual chart with two axes:

  • Feature Implementation Axis (X-Axis): Represents the level of execution for a particular feature, ranging from “Didn’t Do It At All” to “Did It Very Well.” (This reflects how well the feature is implemented, not simply whether it exists.)
  • Satisfaction Axis (Y-Axis): Represents the level of customer satisfaction, ranging from “Very Low” to “Very High.”
Kano model chart from Survalyzer showing the relationship between feature implementation levels and customer satisfaction, including Must-be, Performance, and Excitement categories.

The chart is divided into distinct zones by a diagonal line, separating positive correlations (above the line) and negative correlations (below the line). Each feature category (Attractive, Performance, and Must-be) occupies a specific area of the chart based on customer responses to the survey questions.

Aligning Features with Customer Needs

Understanding how features address distinct customer needs is crucial for product development. The Kano Model categorizes features into six groups, each impacting customer satisfaction and loyalty differently. Let’s explore these categories and how to leverage them for a winning product strategy.

Infographic displaying the Kano Model quadrants of customer needs, categorized into Attractive, Performance, Must-be, and Reverse, with explanations for each.

Attractive Features: The Wow Factor

Attractive features exceed customer expectations and provide a surprise element, significantly enhancing customer delight. They don’t cause dissatisfaction when not present, but can create the most value if done right. Market researchers can identify innovations that not only differentiate products but also unveil emerging consumer trends. By focusing on what creates a ‘wow factor,’ they can guide companies toward novel product differentiators.

  • Example: Luxury features in cars, such as a heated steering wheel or panoramic sunroof, offer unexpected pleasure.

Must-be Features: The Essentials

Must-be features are basic functionalities that customers expect as standard. Their absence causes dissatisfaction. Market researchers can employ benchmarking studies to ensure these must-haves meet the industry baseline. Through continuous tracking and evaluation, it is important to adapt these essentials to changing market norms.

  • Example: In automotive research, essentials like engine performance and safety features.

Performance Features: The Satisfaction Drivers

Performance features are those that customers explicitly demand, and their performance directly correlates with the level of customer satisfaction. These features are critical for informing feature development prioritization, since the better they are executed, the bigger customer satisfaction.

  • Example: Cars are expected to have comfort and essential features like air conditioning, and their absence or poor performance leads to dissatisfaction.

Reverse Features: The Acquired Tastes

Reverse features are the features that customers do not want at the moment. Their presence can actually lead to customer dissatisfaction. Example: touchscreens in cars for particular segments of clients are unwanted and they may actually prefer cars without them.

  • Example: touchscreens in cars for particular segments of clients are unwanted and they may actually prefer cars without them.

Indifferent Features: Neutral Impact

Questionable features are those where customer preferences are unclear or vary widely. These features require further research or testing to determine how they impact customer satisfaction. Understanding these ambiguities may bring additional insights for better customers’ understanding.

  • Example: Gesture control for car functions (like adjusting radio volume) hasn’t gained widespread popularity. Some might find it intuitive, while others might prefer physical knobs or buttons for precision and focus while driving.

Questionable Features: Unclear Preferences

Questionable features are those where customer preferences are unclear or vary widely. These features require further research or testing to determine how they impact customer satisfaction. Understanding these ambiguities is crucial for refining product offerings and aligning them more closely with consumer desires.

  • Example: Autonomous Driving Systems. While rapidly evolving, consumer acceptance of self-driving cars remains uncertain. Further research is necessary to determine the optimal level of autonomy for driver comfort and safety.

Getting started with Kano Analysis is all about crafting a good survey. First, you can start with Survalyzer Kano Model solution template from our education center. Additionally Our guide on creating online surveys can help you with the tricks of the trade to get the best results from your Kano data. It covers the basics you need to know to write questions that give you clear and useful information.

How to Use the Kano Model

One way to start a Kano analysis is by understanding how customers view different features of your product. There are templates available to help you do this, like the solution template from Survalyzer’s education center. A visual example of such a template can be seen as in the picture above, where features are presented with detailed descriptions.

Survey template displaying a Kano Model questionnaire with options for user sentiment about the presence or absence of a feature

When taking a Kano survey, people respond how they’d feel about each feature being there or not. They choose from liking it a lot to not wanting it at all. This double-sided questioning is key to digging deeper than just first impressions. It tells us not only if they like a feature but how important it really is to them. After we gather these insights, each response gets categorized following the rules presented in the matrix table below.

Kano Model matrix categorizing customer reactions to product features as Attractive, Must-be, Performance, Indifferent, Reverse, or Questionable

How to Analyze and Interpret the Results

Analyzing results from the Kano Model involves two main steps:

1. Individual Response Classification: Each survey participant’s answers are sorted to determine their personal views on each feature. This helps place features into categories like Attractive, Must-be, and others, based on how each person feels about them. This step is important for understanding individual preferences.

2. Aggregate Analysis: After sorting individual answers, we combine all the data to see broader trends that apply to all survey respondents. This shows the overall pattern among all participants. This bigger picture helps us understand which features are valued by the majority and which are not.

Kano model analysis results in Survalyzer report

Interpreting Kano Analysis results requires understanding customer satisfaction. Read our dedicated article on CSAT metrics for more information about customer satisfaction and how it relates to customer loyalty. This deeper understanding will enable you to make better decisions about feature development and enhancements.

Conclusion

Kano analysis provides a practical framework for product development. It enables proper investments prioritization by e.g. the inclusion of ‘Must-be’ features, further refinement of ‘Performance’ features, or investment in new ‘Attractive’ features.

Attention to customer satisfaction can help build loyalty and may lead to customers recommending the product to others, enhancing its standing in the market.

Christian Hyka

Managing Partner

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