Streamline user bug reporting
Efficiently resolve issues affecting your users
Table of Contents
User bug reporting can play an important role in finding and fixing problems in web and mobile apps. Even the most thorough testing cycle can’t reasonably account for every device, browser, and operating system combination possible when an app hits production. No matter how scrupulous your team is, some bugs are bound to sneak through.
While user bug reporting can be useful for maintaining and improving applications, users may describe the problem vaguely or lack the technical knowledge to understand what went wrong. From their perspective, it can be difficult to pinpoint when and how an issue occurred. This means Engineers don’t have the context to reproduce and fix the problem, and users are subjected to back-and-forth questions — a frustrating situation for both sides.
Beyond this difficulty, not all bugs need to be fixed. With more intrusive user bug reporting options, such as dynamic feedback forms, users sometimes report an otherwise trivial issue. If, for instance, an issue affects one out of a million users with no impact to revenue, it’s likely not worth fixing. But how can you tell?
Without the necessary clarity and context, user issue resolution can result in a lot of wasted time and inefficient outcomes. A successful process involves understanding what happened and properly scoping the impact and reach of the problem before prioritizing a fix.
Methods for user bug reporting range widely, from simple to sophisticated. Some of the top user bug reporting options include:
Depending on how highly you prioritize collecting bug reports from users, you may want to keep in mind that some of these methods are considered more intrusive while others are more passive.
LogRocket’s session replay provides the context that Support and Engineering teams need to efficiently identify, reproduce, and resolve issues at their root cause.
When a user reports an issue, you can see exactly what that user saw, as well as the technical context for why it happened. Furthermore, you can see how many users the issue affected and whether it impacted key business goals or not. With this data, you can determine whether a bug is worth fixing and how to quickly ship a fix.
With LogRocket’s Galileo machine learning module, you can find out about the most impactful issues before users report them. We’ve analyzed over a trillion user interactions and, using that data, have built a model to alert you each week with an Issues Digest of the most impactful user-facing problems that need immediate attention. This way, you can know the work you’re doing each day will have an effect on the vital KPIs that drive your business.
If you’re interested in reducing or removing the need for users to self-report bugs, start a free trial of LogRocket today.
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