Application of the Kano model in product development: cross-industry insights and methodological approaches

1. Introduction

In today’s digital economy, companies must constantly improve their product offerings to remain competitive and respond to rapidly evolving customer expectations. One methodology that has proven effective in analyzing customer needs and prioritizing product functionality is the Kano model, developed by Japanese professor Noriaki Kano in the 1980s within the Total Quality Management (TQM) framework.

The core idea of the model is that different product features have varying impacts on customer satisfaction: some are basic and expected by default, others are performance-related and predictably enhance user perception, and still others are delight factors that generate a "wow" effect, significantly increasing customer loyalty. This classification enables companies to make informed decisions about which features to include at different stages of product development [3, p. 89].

The goal of this article is to examine the applicability of the Kano model across different industries and to evaluate its effectiveness in the development of both digital and physical products within a highly dynamic technological landscape. Special focus is given to its practical application in SaaS products for the travel and hospitality sector, as well as its integration with other tools such as conjoint analysis, MaxDiff, and TURF analysis (Total Unduplicated Reach and Frequency).

Through real-world examples from telecommunications, real estate, fintech, electronics, and hospitality software, and drawing on the author’s professional experience, the article identifies the model’s practical boundaries and provides recommendations for its adaptation in uncertain and rapidly shifting environments.

2. Theoretical Framework: The Kano Model

The Kano model is a classification tool for product features based on their impact on customer satisfaction. The methodology was introduced by Professor Noriaki Kano in 1984 and has since become the foundation for numerous studies in quality management, user experience design, and product management.

2.1. Classification of Product Features

The Kano model distinguishes the following main types of customer requirements:

• Must-be (Basic) Features – These are characteristics whose absence leads to significant customer dissatisfaction, while their presence does not increase satisfaction. They represent the minimum expected standard, often taken for granted. Examples include car reliability or a functioning internet connection in a hotel.
• One-dimensional (Performance) Features – These features have a direct linear relationship with satisfaction: the better the performance, the higher the satisfaction, and vice versa. Examples include internet speed or the number of available TV channels.
• Attractive (Delighters) Features – These are unexpected and pleasant characteristics that elicit positive emotions when present but do not cause dissatisfaction when absent. They are a key source of competitive advantage and the “wow” effect. Examples include complimentary gifts or exclusive features.

Additionally, the model may identify:

• Indifferent Features – Attributes that have no impact on the customer’s perception.
• Reverse Features – Elements that may cause dissatisfaction if present and satisfaction if absent (rare cases).
• Questionable Features – Features for which the consumer gives logically inconsistent responses, indicating confusion or misunderstanding [4, p. 56-63].

2.2. Evaluation Methodology

The classical Kano model uses a paired-question format for each feature, asking customers:

1. How would you feel if this feature were present in the product?
2. How would you feel if this feature were absent?

Responses are interpreted using a predefined evaluation table, allowing each respondent to categorize the feature accordingly. Aggregating all responses results in a Kano map – a visual matrix that distributes features across quadrants of satisfaction and dissatisfaction.

2.3. Modern Interpretations and Modifications

Over time, several additional approaches and frameworks have been developed to expand the capabilities of the classical Kano model:

• Kano Continuum – A method where each type of response is assigned a numerical weight (e.g., 4, 2, 1, 0), enabling a more nuanced evaluation of each feature’s contribution to satisfaction.
• Regression-Based Approach – Statistical analysis of how the presence or absence of features impacts overall satisfaction metrics such as Customer Satisfaction Index (CSI) or Net Promoter Score (NPS).
• Segmentation and Feature Mapping by Target Audience – During research, respondents can be divided into clusters, allowing for the construction of separate Kano models tailored to each group.

Thus, the Kano model serves not only as a diagnostic tool but also as a strategic guide in product design and evolution. It helps optimize the value proposition and prioritize development efforts in resource-constrained environments.

3. Integration with Other Frameworks

Despite the practical value of the Kano model, using it in isolation does not always address the full range of challenges involved in product decision-making. In highly competitive and fast-changing markets, it becomes essential to combine Kano with other quantitative methods that offer deeper insights into demand structure, customer preferences, and the potential reach within the target audience. Among the most effective of these methods are TURF analysis, MaxDiff analysis, and conjoint analysis [2].

3.1. TURF Analysis (Total Unduplicated Reach and Frequency)

TURF analysis is used to identify the optimal combination of features or products that will provide the maximum unduplicated reach across a target audience. Unlike the Kano model, which focuses on emotional response, TURF enables a quantitative assessment of which minimum set of features or products can satisfy the greatest number of user needs (jobs-to-be-done). It is particularly valuable when deciding where to invest among a long list of attractive or performance features.

Example: When designing a new tablet model with 30 potential features (e.g., AR support, built-in projector, waterproofing), TURF analysis can help select the 5 most relevant features to cover 80–90% of the audience.

3.2. MaxDiff Analysis (Maximum Difference Scaling)

MaxDiff analysis helps rank features based on their relative importance. Instead of asking users to rate all features at once – which often leads to fatigue and inconsistent results–respondents are shown sets of 4 to 6 items and asked to select the most and least important. Repeating these rounds generates a stable distribution of preferences. This method is especially useful when the number of potential attributes is large and accurate ranking is essential.

MaxDiff can serve as an anchor method for TURF analysis, as it helps identify which features fall into the top-1 or top-2 preferences for each respondent.

3.3. Conjoint Analysis

Conjoint analysis is one of the most complex yet powerful tools in the product research toolkit. It simulates real-world consumer behavior by asking users to choose between product options with different combinations of attributes. This enables researchers to:

• Determine the weight of each attribute in the decision-making process;
• Build pricing models (e.g., how much a user is willing to pay for an additional feature);
• Forecast market share under different combinations of attributes and pricing.

Conjoint analysis is particularly valuable when entering new markets, updating product lines, or planning an MVP (Minimum Viable Product).

3.4. Combined Approaches

In practice, a hybrid model is most commonly used, combining the Kano model with one or more of the methods mentioned above. The following sequence is often applied:

• Kano → Identification of requirement types (basic, performance, delighters)
• MaxDiff → Prioritization by importance
• TURF → Selection of the optimal feature set for launch
• Conjoint → Validation of the final feature combination and calculation of willingness to pay

This approach enables a comprehensive evaluation of customer perception from both emotional and expectation-based perspectives, while also providing the numerical data needed for informed business decisions.

We propose starting with the first example – the telecommunications industry – as it clearly illustrates market saturation with basic features and the challenge of identifying new delight attributes.

4. Application of the Kano Model Across Industries: Case Studies

4.1. Telecommunications: Internet and TV subscription

The market for telecom services – internet and television – is one of the most mature and competitive sectors in Russia. Studies conducted in 2018 with a sample of over 1,000 respondents across the country demonstrated that the Kano model effectively illustrates market saturation and the dominance of must-be factors in customer perception.

Key Findings:

Must-be Features:

• Competitive pricing and offers
• Internet speed of at least 100 Mbps
• Uninterrupted service with no disconnections
• Antivirus software and additional service bundles included
• “3-in-1” package: internet + TV + phone line

All of these attributes are perceived by users as standard expectations. The absence of any one of them leads to strong dissatisfaction, while their presence does not increase loyalty – they merely prevent negative sentiment.

Performance Features:

• Online gaming speed,
• Number of TV channels,
• Customer support response time.

These attributes are those where customers clearly perceive differences in quality: the higher the level, the better the satisfaction. These factors can serve as sources of competitive advantage within the boundaries of a “standard” product.

Delight Features:

• Easy cancellation of subscription,
• Rewards for on-time payments,
• Ability to change plans independently.

These are rare but powerful delighters. Most users do not expect such features, but their presence can create a “wow” effect and significantly increase brand loyalty. For instance, an easy cancellation option or a flexible loyalty system can shift the perception of a provider from “faceless infrastructure” to “a caring partner.”

Conclusion:

The Kano model demonstrates that in mature, highly standardized markets (such as fixed internet services), the main competition occurs within the must-be and performance categories. Opportunities for introducing new delight features are limited–but it is precisely these that can create a marketing breakthrough.

However, due to the predominance of must-be requirements in this market, there is increasingly less room for innovation. Most of the operator’s resources are spent on maintaining standards, which reduces flexibility in product development. This highlights the need to supplement the Kano model with satisfaction tracking tools (e.g., NPS/CSI), as well as with additional methods such as TURF or conjoint analysis to test and validate new offerings.

4.2. Real Estate: Mass-Market Housing Purchases

The residential real estate market – particularly in the mass segment–is characterized by the high importance of the decision for buyers, a lengthy transaction cycle, and low product renewal frequency. These factors create a unique structure of consumer expectations that the Kano model helps analyze systematically.

Market Characteristics:

• Psychological nature of decision-making: Housing is a fundamental life necessity, and the purchase decision is often emotionally charged.
• Extended product lifecycle: Buying an apartment is a decision that spans decades, so expectations regarding quality and reliability are extremely high.
• Limited wow factors: Due to the nature of the product, delight features are rare and tend to lose uniqueness quickly.

Kano Analysis Results:

Must-be Features:

• Quality of construction materials
• Performance of property management services
• Guarantee of on-time project completion
• Developer integrity and fulfillment of promises
• Ability to track construction progress

These attributes are not just expected – they are perceived as critical. The absence of any of them can completely negate a positive impression of the property.

Performance Features:

• Completeness and accuracy of information from the sales representative
• Time required to process contracts
• Interior finishing (if included)
• Access to local infrastructure

These attributes influence satisfaction in a straightforward “more is better” fashion but do not typically evoke strong emotions.

Delight Features:

• Aesthetically appealing building facade
• Loyalty programs for buyers
• Energy-efficient and eco-friendly technologies
• Strong, reputable developer brand

These factors are not deal-breakers, but in situations where price and core features are equal, they can serve as decisive triggers that tilt the choice toward one project over another.

Conclusion:

In the real estate market, the Kano model clearly illustrates the dominance of must-be factors, reflecting the fundamental nature of the product. The role of the product manager or marketer here lies less in delivering delight and more in eliminating pain points and minimizing risks for the buyer.

Moreover, due to the stability of expectations and the slow pace of change in this sector, using the Kano model dynamically (as a tracking tool) is especially beneficial. By monitoring how perceptions of baseline features evolve (e.g., composite facades shifting from delighters to must-be), developers can adapt their product offerings and communication strategies without needing to conduct new large-scale studies.

4.3. Financial Services: Credit Cards for Small Businesses

Financial products – particularly credit cards for entrepreneurs and small businesses – are highly standardized, and customer decision-making tends to be highly rational. This creates a specific distribution of Kano model factors, where performance attributes dominate, and both must-be and delight features are scarce.

Context and Market Characteristics:

Target audience: Sole proprietors, small business owners, and microbusiness operators

• Expectations center on: Functionality, cost-efficiency, and ease of use.
• High product standardization: “Wow” innovations are rare in this category.

Kano Analysis Results:

Must-be Features:

Functions as a standard credit card – a baseline expectation without which the product has no value.

Performance Features:

• No annual fee,
• Lower interest rate,
• Cashback or reward points for purchases,
• Discounts with partners,
• Higher credit limit

These features are directly tied to benefits and convenience. Consumers actively compare offers based on these attributes, and even small differences can significantly impact their decision.

Delight Features:

• Access to exclusive sales events
• Fuel bonuses
• Special offers for seasonal businesses

These features generate a positive emotional response but are not expected by default. Their presence can increase loyalty, especially when tailored to specific segments (e.g., fleet owners or retail shop operators).

Indifferent Features:

• Card branding (e.g., Gold, Platinum status).
• Card design and visual aesthetics.

For this customer segment, status and aesthetics are secondary to practical utility.

Conclusion:

Unlike the real estate and telecommunications markets, the small business credit card sector is driven by rational decision-making, with minimal influence from emotional or delight factors. The Kano model in this context reveals a strong emphasis on performance features, which should be the core focus in product development, positioning, and communication strategies.

Additional frameworks such as conjoint analysis can be used to quantify the value of each feature in monetary terms (e.g., how much a user is willing to pay for cashback). This is especially important when designing tiered pricing plans or differentiated product lines.

4.4. Electronic devices: Tablets

The consumer electronics market is one of the most dynamic and innovation-driven sectors, where the lifecycle of features is significantly shorter than in other industries. This makes the application of the Kano model particularly interesting: many features that were considered delighters just a year ago are now perceived as must-haves.

Industry Characteristics:

• Technologies become obsolete quickly; “wow features” turn into expectations within 6–12 months.
• User expectations vary by use case–entertainment, work, education, children, etc.
• High competition forces manufacturers to constantly seek new features that can surprise users.

Kano Analysis Results (by Segment):

The study included two segments: young families and freelancers.

Segment: Young Families

Must-be Features:

• Suitable for video content (e.g., evening cartoons)
• Supports gaming (children’s entertainment)
• Minimum 256 GB of storage

Performance Features:

• User interface convenience
• Battery life
• Device speed

Delight Features:

• Built-in projector
• Smart home integration
• Individual profiles for children and adults
• Durable casing
• Peripheral connectivity options

Segment: Freelancers

Must-be Features:

• Suitable for professional work
• Microsoft Office compatibility

Performance Features:

• Suitable for creative tasks (graphics, audio, coding)
• Stylus support or precision input
• Ability to connect to keyboard and monitor

Delight Features:

• Voice assistant autonomy
• AI-powered interface features
• AR/VR interaction modes

Conclusion:

This case clearly illustrates how different user segments perceive the same features differently – what is a delighter for a family may be irrelevant to a freelancer, and vice versa. This underscores the importance of segmentation and the need to conduct separate Kano analyses for each target audience.

Additionally, in the electronics market, it is crucial to regularly update research findings, as feature categories evolve rapidly: AI functions that were once considered delightful are becoming standard and soon will be essential in all devices.

In such markets, it is especially important to combine the Kano model with TURF analysis to identify which 3–5 features will deliver the greatest reach when launching a new device model.

4.5. Hospitality and Tourism: B2B SaaS Products for the Hotel Industry

Industry Characteristics:

Since 2014, the Russian hospitality sector has undergone a rapid digital transformation. The withdrawal of international operators, the growth of domestic tourism, and increased competition among small hotels have all fueled demand for specialized SaaS solutions.

The target audience of this study – small hotels, apartments, hostels, and later properties with 100+ rooms – had limited exposure to technological tools and demonstrated a wide range of digital maturity. This made the Kano model particularly valuable for identifying key user expectations and informing product strategy.

Kano Analysis Results:

Must-be Features:

• Stable system performance with no crashes
• Integration with a wide range of Russian and international online booking systems
• Reporting features for government agencies (e.g., Rosstat and the tax authority)
• Capability to accept online payments via the hotel’s official website

These attributes became industry standards and were seen by clients as basic requirements for being considered a trustworthy provider.

Performance Features:

1. Number of available integrations (banks, payment systems, CRMs, IP telephony, electronic locks, POS terminals).
2. Flexibility in pricing and promotions.
3. Level of automation in handling requests and bookings.

These features determined the usability, efficiency, and resource savings of competing solutions – clear differentiators in buyer decisions.

Delight Features:

API access for external developers:

• Proprietary marketplace with plug-and-play modules
• Online academy and video courses for users
• Automated sales funnels and self-onboarding without manager involvement
• Innovations such as voice assistants and messenger integrations

These features were perceived as innovative and unexpectedly useful. Their presence increased customer loyalty and contributed to Bnovo’s organic growth into the premium segment.

Conclusion:

The Bnovo case demonstrates how the Kano model can be effectively applied in a B2B SaaS context with a diverse customer base. As must-be features quickly become the norm, the true competitive edge lies in performance and delight attributes. Flexibility and adaptability to different customer segments are especially important.

Furthermore, the fast pace of market evolution reinforces the need for regular Kano model updates, ideally combined with MaxDiff and conjoint analysis during the development of pricing plans and product roadmaps. This approach enables a clearer understanding of where expectations end and delight begins.

5. Comparative Analysis: Behavior of Kano Factors Across Industries

Analyzing the application of the Kano model across five different industries reveals patterns in factor distribution and types of customer expectations. Below are key insights derived from the case studies in telecommunications, real estate, financial services, electronics, and tourism SaaS products [1, p. 112].

5.1. The Level of Must-be Factor Saturation Depends on Market Maturity

In mature, standardized markets (e.g., telecom and real estate), there is a high concentration of must-be features. Market participants are required to deliver baseline functionality at a high level just to remain competitive. Innovation has minimal impact on customer choice if core expectations are unmet.

Examples:

• “Competitive pricing” in telecom services → must-be
• “Project deadlines and construction quality” in real estate → must-be

5.2. Rational Markets Gravitate Toward Performance Features

In markets dominated by rational decision-making (e.g., financial services and B2B SaaS), most customer requirements fall into the performance category. Clients compare offerings based on functionality, cost, and flexibility, expecting each improvement to deliver measurable value.

Examples:

• “Lower interest rates” or “cashback” in credit card services
• “Number of integrations” and “pricing flexibility” in SaaS products

5.3. Dynamic Markets Require Ongoing Work with Delight Features

In fast-paced, technology-driven industries (e.g., electronics, IT), delight features frequently transition into performance or even must-be categories. It's crucial to monitor the lifecycle of product features and develop customer “wow” strategies proactively.

Example:

• Built-in projectors or AR integration were yesterday’s delighters but are becoming today’s industry standard.

5.4. Kano Model Structure is Sensitive to Customer Segment

Different user segments within the same industry may categorize the same features differently. This is especially evident in B2C products (e.g., families vs. freelancers in electronics) and the hospitality sector (small hotels vs. 100+ room properties).

Implication:

Separate Kano models should be developed for each customer segment, or clustering should be conducted prior to analysis.

5.5. The Kano Model Requires Regular Updating

Kano factors are not static. What delights users today may become an expectation tomorrow–this is particularly true in digital markets. Using the Kano model in combination with tracking tools (e.g., CSI, NPS) and dynamic methods (e.g., conjoint, MaxDiff, TURF) helps build a stable strategic picture over time.

6. Limitations of the Kano Model and Practical Recommendations

Despite its high practical value, the Kano model has several limitations that should be considered when applying it in real-world projects. These limitations pertain both to methodological aspects and to its applicability across different product types and market conditions.

6.1. Model Limitations

1) Model Staticity

The classical Kano model is typically conducted as a one-time study. However, in fast-evolving industries such as electronics and digital services, the lifecycle of features is very short. Within six months, customer perceptions may shift dramatically.

Recommendation: Use the Kano model dynamically – as part of a continuous customer insight process (e.g., in a tracking format).

2) Dependence on Question Wording

Respondents' answers are highly sensitive to how features are described. Poorly worded or overly abstract descriptions can distort results and misclassify features.

Recommendation: Conduct qualitative research beforehand (e.g., in-depth interviews, laddering) to gather the customer’s “natural language” and use it to formulate feature descriptions.

3) Respondent Fatigue

Each feature in the Kano model requires a pair of questions: one about its presence and one about its absence. With a long list of features, respondents may become fatigued, which reduces the accuracy of their responses.

Recommendation: Use MaxDiff analysis beforehand to eliminate weak features, or divide the survey into randomized blocks to reduce cognitive load.

4) Limited Suitability for Willingness-to-Pay Assessment

The Kano model does not provide insight into how much a customer is willing to pay for a feature. It captures sentiment (satisfied/dissatisfied), but not price sensitivity.

Recommendation: Use conjoint analysis or incorporate price as an additional attribute–especially when making decisions about pricing plans and market segmentation.

5) Limited Applicability to Complex and Modular Products

For multi-layered, “menu-style” products (e.g., subscriptions, platforms), the classical Kano model becomes less effective, as it does not account for the interaction between different features.

Recommendation: Apply the Kano model in conjunction with other methods – such as scenario modeling, customer journey mapping (CJM), TURF analysis – or build separate models at the component level.

6.2. Practical Guidelines for Integrating the Kano Model into Business Processes (tab.)

Table

7. Conclusion

The Kano model remains one of the most powerful tools for evaluating and prioritizing product features from the end-user’s perspective. It enables the structuring of numerous attributes based on their impact on customer satisfaction and, crucially, differentiates expectations according to market maturity, audience segments, and technological context.

The analysis of five distinct industries – telecommunications, real estate, financial services, consumer electronics, and tourism SaaS – demonstrated that the distribution of Kano factors varies significantly depending on:

• The stage of technological product development.
• The type of audience (emotional vs. rational behavior).
• Market innovation cycle speed.
• Cultural expectations of users.

The model proves especially effective during initial feature prioritization, MVP development, and the identification of key customer pain points. However, its value increases dramatically when combined with quantitative methods (TURF, MaxDiff, conjoint) and integrated into a continuous feedback loop (e.g., via NPS, CSI, Customer Journey Mapping).

In the context of increasing product complexity and market competition, focusing on customer expectations and perceptions becomes a cornerstone of product strategy. The Kano model is not merely a research tool – it is a philosophy of attentiveness to customer needs, enabling companies to build solutions that truly serve their users.