Heuristic Evaluation According to Nielsen
The heuristic evaluation is an established method for analyzing the usability of digital products - from website prototypes to finished apps. It was developed by Jakob Nielsen and Rolf Molich in the early 1990s and is based on the assumption that experienced UX experts can already identify many usability problems without real users having to operate the system. The method is based on so-called usability heuristics - general principles of good interface design, such as consistency, error avoidance or system feedback.
When and Why is Heuristic Evaluation Used?
Heuristic evaluations are typically used in the early phases of product development. For example, an interactive prototype of an online store is checked by a UX team before the first user test. It is noticed that the shopping cart icon is difficult to recognize in the mobile view and that there is no feedback after adding a product - violations of several heuristics. These problems can be resolved early and cost-effectively, even before real users are confronted with them in tests.
The aim is always to detect Usability problems as early as possible in order to avoid subsequent corrections. The method is suitable for websites, apps, complex tools, but also for interactive hardware - wherever user interaction plays a role.
This is How a Heuristic Evaluation Works
A heuristic evaluation process usually follows a systematic sequence:
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Briefing of the evaluators Before the interface is analyzed, the target group, context of use and typical tasks should be clearly defined. For example: “The system is aimed at first-time users with little technical affinity and should be optimized for getting started with online banking.”
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Individual appraisal Several UX experts (ideally 3-5) run through the interface independently of each other. They use specific tasks to check whether the operation is intuitive, understandable and efficient.
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Application of heuristics The evaluation is based on the 10 usability heuristics from Nielsen (see below).
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Logging of problems Every problem found is documented - often with screenshots, affected heuristics, a brief description and a severity rating.
5 Merger and consolidation In a joint evaluation step, the findings are compared, consolidated and prioritized.
- Determination of recommendations for action Concrete design improvements are derived from the findings - for example to redesign buttons, simplify dialogs or add feedback mechanisms.

The 10 Heuristics According to Nielsen - with examples
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Visibility of the System Status Users should always be able to see what the system is doing.
Example: After clicking on “Save”, a loading indicator is missing - the system seems to hang. -
Match between System and Real World Language, symbols and processes should be based on familiar concepts.
Example: Instead of “Complete download”, “Finalize transfer entity” is displayed. -
User Control and Freedom Users must be able to easily undo mistakes.
Example: No “Cancel” button in the order process. -
Consistency and Standards The same object should always look the same and behave the same.
Example: On one page a red button means “delete”, on the next “back”. -
Error Prevention The system should help to prevent mistakes from being made in the first place.
Example: A form accepts a password without any indication of minimum length - a failed attempt is inevitable. -
Recognition Rather Than Recall Information should be visible instead of hidden.
Example: The price information disappears after switching to the payment page. -
Flexibility and Efficiency of Use Advanced users should be able to reach their destination more quickly using shortcuts or filters.
Example: No option to mark or delete several e-mails at once. -
Aesthetic and Minimalist Design No superfluous content that distracts from the essentials.
Example:_ Four call-to-actions in different styles on a landing page. -
Help Users Recognize, Diagnose, and Recover from Errors Error messages should be understandable and helpful.
Example:_ “Error code 1327” instead of “Please enter a valid e-mail address.” -
Help and Documentation If necessary, support should be available quickly.
Example:_ No help link for complex filter function.
Assessment of the Issues
In order to categorize problems, they are typically classified according to severity. An indicative scheme is as follows:
Severity | Meaning |
---|---|
0 | No problem |
1 | Cosmetic - only remedy in case of excess time |
2 | Low priority - rectify if possible |
3 | High - should be fixed |
4 | Critical - must be remedied |
A practical example: In an administration portal, a mandatory field is not sufficiently highlighted visually. The error is rated “3”, as many test users skip the step and a frustrating error dialog follows.
Advantages and Limitations of the Method
Heuristic evaluation is particularly popular because it is fast, comparatively inexpensive and repeatable. It can already be used in the wireframe phase and provides initial indications of structural weaknesses - without the need for functional prototypes or real users.
However, the perspective remains expert-centered. This means that the results do not necessarily reflect the actual problems of real users - especially if they are very inexperienced, limited or context-specific.
The following therefore applies: Heuristic evaluations are no substitute for usability tests, but they are an effective supplement.
Conclusion
The heuristic evaluation according to Nielsen is a practical, proven procedure that is particularly suitable for the initial quality check of interfaces. It promotes systematic discussions within the team, creates a structured basis for improvements - and is particularly valuable when it is embedded in an iterative, user-centered process.
Current research on heuristic UX evaluation
These contributions offer systematic literature reviews, practical case studies and methodological developments in the field of heuristic UX evaluation.
Heuristic-Based Usability Evaluation Support: A Systematic Literature Review and Comparative Study
Provides a comprehensive overview of tools and methods of heuristic evaluation and identifies deficits in software support - helpful for understanding methodological frameworks.
Fernández, J., & Macías, J. A. (2021). Heuristic-based usability evaluation support: A systematic literature review and comparative study. International Conference on Human-Computer Interaction. https://doi.org/10.1145/3471391.3471395
The Use of Heuristic Evaluation on UI/UX Design: A Review to Anticipate Web App’s Usability
Literature review of 455 articles on UI/UX heuristics. Shows how heuristic evaluation supports user-centered design decisions.
Ramadhanti, N. T., Budiyanto, C. W., & Yuana, R. A. (2023). The use of heuristic evaluation on UI/UX design: A review to anticipate web app's usability. AIP Conference Proceedings. https://doi.org/10.1063/5.0105701
Heuristic Evaluation of UI/UX to Enhance Experience and Sales in E-commerce
Shows the practical use of Nielsen's heuristics in a commercial UX context with demonstrable improvements in UI and user satisfaction.
Andika, R., & Renaldi, D. (2024). Heuristic evaluation of UI/UX to enhance experience and sales in e-commerce. bit-Tech, 7(2). https://doi.org/10.32877/bt.v7i2.1730
An Experimental Activity to Develop Usability and UX Heuristics
Describes a domain-specific approach for the further development of Nielsen's heuristics for mobile applications - with a focus on experimental methods.
Reis, P., Páris, C., & Gomes, A. (2020). An experimental activity to develop usability and UX heuristics. In Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-030-66919-5_3
Coherent Heuristic Evaluation (CoHE): Toward Increasing the Effectiveness of Heuristic Evaluation for Novice Evaluators
Addresses challenges in the application of heuristic evaluation by non-experts and presents a step-by-step framework for increasing evaluation accuracy.
Abulfaraj, A., & Steele, A. (2020). Coherent heuristic evaluation (CoHE): Toward increasing the effectiveness of heuristic evaluation for novice evaluators. International Conference on Human-Computer Interaction. https://doi.org/10.1007/978-3-030-49713-2_1
Last modified: 17 June 2025