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How to Make Your Designs More Forgiving: Handling User Error

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Read Time: 2 min

People make mistakes. And part of designing a well functioning system is to make sure your system is more forgiving of common errors. What does this mean in terms of user experience? 

1. Allow for Correction 

Reversible actions provide room for correction, and are a simple and intuitive way of making your system more forgiving. 

The “Undo” action is a well known example that allows for correction. Without an undo action, users may look to the “Back” button, or a breadcrumb which takes them to their previous position. Having an undo action makes for a stress-free workflow so that if a user missteps during the process of completing a task, they can course correct themselves without unpleasant consequences. 

2. Preventing Errors

Consider using a confirmation dialog before a somewhat non-reversible action (like an online purchase). Make sure your warning messages and states are clearly visible and colored. Also consider having a summary of actions before a non-reversible step. 

A common place for errors is a form field, or a long entry form. Not only can these be daunting but they can be plagued with tiny pitfalls for the careless user. How can you guide users in these circumstances?

Practical Constraints

Form fields that cater to the type of information that is required are a perfect way of constraining a user’s movements. Limiting the characters for a phone number will help to ensure more accuracy when a user is typing in their information. 

Good Defaults

A form field that has an example of the type of information that is required will help remind the user what they have to type. 

Write Clearly

One final thing to note is to make the written copy in your digital experience concise and understandable in the first place–this will have a huge impact on preventing errors. 

3. Offer Smart Suggestions

Think of user error as a reflection of the failure of a system rather than a failure of the user. Did the user search for something in non-standard language? Is there a way to predict what they did mean to search for?

An example of smart suggestions could be a search engine that corrects spelling mistakes or suggests other examples of what might be relevant to the user. 


By making your designs more forgiving, you develop systems that are more empathetic to the needs of real people, who inevitably may make mistakes. 

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