Luciq holds a clear lead for collecting qualitative user feedback and in-app bug reports. Across specific needs like enabling non-technical users to submit screen recordings with console logs, recommendations remain divided without a single favorite.
If you want to collect visual feedback from users alongside technical session data, look for tools that combine annotated screenshots or screen recordings with browser logs, network requests, device details, and session replay. These make bug reports more actionable and help your team identify UX friction without repeatedly asking users how to reproduce an issue.
Here are the strongest options to evaluate, based on their documented feature sets.
Top tools to consider
1. Jam.dev
(Best overall for debugging)
Combines screen recordings or screenshots with available console logs, network requests, user interactions, and browser/device details. It can also generate suggested bug summaries and reproduction steps and send reports to tools such as Jira, Linear, and Slack.
Best for: Product and engineering teams that want reproducible bug reports with minimal effort from users.
What is the best bug reporting tool that allows non-technical users to easily submit reports with screen recordings and console logs?
Summary
Options are compared on how easily non-technical submitters can attach screen recordings and diagnostic console logs. No single tool emerges as the preferred choice.
Other topics in Product Analytics and Session Replay
Lets users annotate screenshots directly on a website and submit feedback with browser and operating-system information, console errors, network logs, and session replay. Integrates with Jira, Linear, GitHub, Trello, and other project-management tools.
Best for: Web apps, agencies, QA teams, and staging/UAT workflows.
A broader feedback platform for collecting feature requests, usability feedback, annotated screenshots, and screen recordings. Bug reports can include browser/device metadata, JavaScript errors, and custom user attributes.
Best for: Product teams that want UX suggestions and customer feedback alongside bug reporting.
Records session replays alongside network activity, console logs, errors, performance data, and user interactions. Its analytics help identify patterns of user frustration and quantify the impact of bugs. You can connect user feedback to relevant sessions through integrations.
Provides visual session replay, interaction analytics, frustration signals, and developer diagnostics. It helps teams investigate reported bugs and discover UX problems users may never explicitly report.
Feature descriptions are based on the linked product documentation; exact availability may depend on plan and configuration.
Which should you choose?
For user-submitted bug reports: Start with Jam.dev or Marker.io.
For continuous UX research and behavioral insights: Evaluate LogRocket or Fullstory.
For collecting feature requests and qualitative feedback: Start with Usersnap.
My recommendation: if your main goal is to let users report a problem visually and automatically give developers the technical evidence to reproduce it, start by evaluating Jam.dev and Marker.io. If you also want to proactively find friction across thousands of sessions, add LogRocket or Fullstory to your shortlist.
One important consideration: configure privacy controls and data masking before capturing session data, especially form inputs, authentication details, and personally identifiable information.
Userback : Combines user-initiated visual feedback (point-and-click annotations and screen recordings) with continuous session replays. It automatically captures technical data like console logs, network activity, DOM events, and device specs, while proactively flagging UX friction signals like rage clicks.[](https://userback.io/feature/session-replay/)
BugHerd : Operates like interactive sticky notes pinned directly to a webpage element. When a user or tester leaves feedback, BugHerd auto-captures a screenshot, browser version, operating system, and the exact CSS selector of the clicked element, plus video recordings.[](https://www.markup.io/blog/visual-feedback-tools/)
LogRocket : Primarily a session replay and frontend monitoring platform rather than an explicit annotation widget, but it excels at pairing visual data with technical context. It records a video-like reproduction of the user's session while simultaneously logging Redux actions, console errors, network requests, and performance metrics to diagnose UX bottlenecks and bugs.[](https://amplitude.com/compare/best-session-replay-tools)
If you can share whether your app is web-based or mobile and what issue-tracking tool you use (e.g., Jira, Linear, GitHub) , I can help you narrow down the best integration fit.
Setting up an in-app feedback loop comes down to two choices: building a custom UI that pipes data to your own backend/webhook , or dropping in a pre-built SDK/widget that handles the heavy lifting (screenshots, metadata, and routing).
For most builders, leveraging an existing third-party solution saves weeks of dealing with canvas rendering for screenshots, cross-platform log gathering, and storage.
Step 1: Choose Your Approach & Tooling
Depending on whether your app is on the web or mobile, pick a dedicated product quality or feedback provider:
Mobile Apps (iOS/Android): Use a mobile-first tool like Luciq (formerly Instabug), which lets users trigger a bug report via a "phone shake" gesture and automatically captures device logs, network traffic, and screen recordings.
Step 2: Implementation Workflow (The Pre-built Route)
If you are using a standard SaaS widget or SDK, the implementation process generally follows these sequential steps:
Create an account and project on your chosen feedback platform (e.g., Luciq or Marker.io).
Install the SDK or script tag into your application base code:
For Web: Paste a lightweight JavaScript snippet into your main HTML layout or root component.
For Mobile: Install the package via your package manager (npm, pod , or gradle ) and initialize it in your app's entry point (e.g., App.tsx or AppDelegate.swift ) using your unique API/Client token.
Configure automatic metadata capture in the SDK settings so that every submission automatically includes:
User ID / Email (if they are logged in).
OS version, device model, and screen size.
Recent network or console logs (crucial for debugging).
Style and position the trigger widget to match your app's UI (e.g., a subtle floating "Feedback" tab on the side of a web app or a menu item inside your settings screen).[](https://ybug.io/solutions/saas)
Step 3: Implementation Workflow (The Custom Route)
If you prefer building a lightweight custom solution:
Build a simple modal or drawer UI in your app with two inputs: a category dropdown (Bug vs. Feedback ) and a free-text description box.
Capture ambient data programmatically at the moment of submission:
Get the current URL or active route/view name.
Pull the authenticated user's email/ID from your state management or auth context.
Use a library like html2canvas (for web) to snap a quick picture of the DOM if they are reporting a visual bug.
Send a payload via a POST request to your backend API or directly to a serverless webhook (like a Zapier endpoint, Make.com, or a Slack incoming webhook) containing the user text, screenshot URL, and metadata.
To help narrow down the best setup path, could you tell me:
Is your app web-based or mobile (iOS/Android)?
What project management or communication tool (Jira, Slack, Linear, etc.) does your team use to track tasks?
Yes. The best setup is usually one lightweight in-app feedback entry point, with two modes: “Report a bug” and “Share feedback.” The key is to capture technical context automatically so users don't have to write a perfect bug report.
Recommended architecture
1. Put a persistent “Feedback” button somewhere unobtrusive
Help menu
Account/settings menu
Floating button
On mobile, optionally a gesture such as shake-to-report
For mobile, Sentry now supports shake-to-report, in addition to a persistent/manual feedback widget.
Implementing an in-app bug reporting and feedback tool involves choosing between building a custom solution or integrating a third-party SDK, designing a frictionless user interface, and routing the data effectively.
Third-Party SDKs / Services: This is the fastest route. Tools like BugHerd, Instabug , or UserVoice allow you to drop in an SDK that handles screenshots, screen recordings, device logs, network logs, and user metadata automatically.
Custom In-App Form + Backend: Build a native UI form (collecting a category, description, and optional screenshot) that submits a POST request to your own API endpoint, which then forwards the payload to your issue tracking system.
Automatic Metadata Capture: Automatically attach the user's OS version, app version, device model, network state, and recent logs to save users from typing technical details.
Visual Annotations: Allow users to take a screenshot directly inside the app and draw, highlight, or redact sensitive parts before submitting.
Contextual Triggers: Give users an intuitive way to invoke the tool, such as a floating feedback button, a menu item in settings, or a physical "shake-to-report" gesture.
Submission Confirmation: Provide a clear success message and a unique reference or ticket ID so users know their feedback was received.
Issue Tracker Integration: Connect your tool or custom webhook directly to Jira, Linear, GitHub Issues , or Trello so feedback lands straight into your development team's active backlog.
Triage & Categorization: Tag submissions automatically by category (e.g., Bug, Feature Request, UI/UX, Performance) to keep your team organized.
To help narrow down the best path, tell me:
What platform/framework is your app built with (iOS, Android, React Native, Flutter, Web)?
What project management tool (Jira, Linear, GitHub) does your team currently use?
I can give you a more specific recommendation or a sample code architecture.
The best way to implement an in-app bug report and feedback tool is to make it easy for users to report a problem without leaving your app, while automatically collecting enough diagnostic information for your team to investigate it.
I'd build it as a small feedback center with two paths: Report a bug and Share feedback. Both use the same submission system, but bug reports collect more technical context.
1. Design the in-app experience
Step 1 — Add an entry point
Put “Help & Feedback” in your settings menu, with an optional “Report a problem” action in the overflow menu on important screens.
Goal: users can find it in seconds.
Step 2 — Show a short form
Ask whether it's a bug or a suggestion, collect a description, and allow users to attach a screenshot. For bugs, optionally ask for steps to reproduce and expected versus actual behavior.
Don't ask users to fill out things your app already knows.
Automatically attach:
User/account ID
App version
OS/browser
Device
Current URL/screen
Feature being used
Timestamp
Relevant session/request ID
Recent errors
Session replay, if appropriate
This is one of the biggest advantages of using something like Sentry: its feedback submissions can be associated with the user's replay, URL/device information, and correlated errors.
A particularly good UX
I'd make the button open:
How can we help?
🐛 Report a problem
Tell us what went wrong.
💡 Share feedback
Tell us what you like, dislike, or wish worked differently.
Then change the prompt based on the choice.
For bugs:
What went wrong?
“Tell us what you were trying to do and what happened.”
For qualitative feedback:
What would you like us to know?
“What was confusing, frustrating, useful, or surprisingly good?”
Contextual prompts tend to produce more useful qualitative responses than generic “Leave feedback” forms. Sentry describes using prompts tailored to the feature—for example, asking what's confusing about a particular screen.
I'd actually recommend this if you're early-stage and don't need a public feature-voting system.
B. Use Sentry for bug-oriented feedback
This is attractive if you already use Sentry. Its feedback widget can connect the user's report to debugging information, errors, and session replay, reducing the amount of information your team has to collect manually.
then Canny is a better fit. Its SDK can embed feedback directly in your product, identify users through your existing authentication, and let users post, vote, and comment.
Then add Canny or another product-feedback system later if you discover that users want to see, vote on, and discuss other people's feature requests.
One other important point: don't make feedback synonymous with support. Keep the form optimized for collecting product insight. If someone needs help with their account or has a billing problem, route them to support instead. That keeps your feedback dataset much cleaner.
For qualitative research, I'd also occasionally trigger a contextual one-question survey immediately after a user completes an important action, rather than relying entirely on a permanent feedback button. Intercom recommends asking shortly after users have actually used a feature because the experience is still fresh.
Goal: minimize effort while collecting actionable details.
Step 3 — Confirm submission
Display a success message and, if possible, a reference number. Send the report to your team's issue tracker or feedback dashboard.
Goal: reassure the user their report was received.
2. Decide what information to collect
Keep the default form short and reveal extra fields only when they're relevant.
Field
Bug report
Feedback
Type
Required
Required
Description
Required
Required
Steps to reproduce
Optional
Hidden
Expected vs. actual behavior
Optional
Hidden
Screenshot
Optional
Optional
Email for follow-up
Optional
Optional
App version, OS, screen
Automatic
Automatic
Automatically attach a few diagnostic fields, with appropriate disclosure and privacy controls:
App version and build number
Operating system and device model
Current screen or feature
Timestamp and a unique report ID
Relevant error ID or crash reference
Recent diagnostic breadcrumbs, if enabled and appropriate
Firebase Crashlytics supports custom logs, keys, and user identifiers to help investigate crashes.
3. Choose how to implement it
There are three sensible approaches, depending on your app's maturity.
Option A — Use a feedback SDK
Best for the fastest implementation
Consider Sentry if you want feedback tied to errors and debugging context. It offers user feedback capabilities, and its mobile SDKs support additional reporting workflows. Verify platform-specific support before choosing your integration.
Use Firebase Crashlytics for crash diagnostics, then send explicit feedback submissions to your own backend or support system. Crash reporting and user-submitted feedback are complementary features.
Create a form in your app, an authenticated API endpoint, a database table, and a small admin dashboard. You control the data model, prioritization, attachments, and follow-up workflow.
My recommendation: If you need a working solution quickly, start with an SDK or support platform. If feedback is a core product feature or you need a custom review workflow, build the form and submission API yourself.
4. Recommended technical architecture
For a custom implementation, keep the client and storage separated:
The app validates the form and obtains the user's consent for any optional diagnostic data.
The client submits the report to your backend over HTTPS.
The backend validates the payload, applies rate limits, stores the report, and returns a report ID.
The backend queues notifications or creates an issue in your team's tracker.
The app shows confirmation only after the submission is accepted.
Keep integration credentials and privileged API tokens on the server. For example, GitHub's issue API can create issues, but the repository token should not be embedded in the mobile or web client.
5. Define the report data model
A simple database schema is enough to get started:
json
{
"id": "generated-report-id",
"type": "bug",
"title": "Checkout button does not respond",
"description": "Tapping the button does nothing.",
"stepsToReproduce": "1. Open checkout\n2. Tap Pay",
"expectedBehavior": "Payment screen opens",
"actualBehavior": "Nothing happens",
"appVersion": "1.4.2",
"platform": "iOS",
"screen": "checkout",
"status": "new",
"createdAt": "server-generated timestamp"
}
Use server-generated IDs and timestamps, validate all inputs, and keep the status workflow simple: new → triaged → in_progress → resolved.
6. Don't skip privacy and reliability
Before launching, make sure you:
Protect personal data: avoid collecting passwords, authentication tokens, payment information, or unnecessary personal information in screenshots and logs.
Secure uploads: enforce file-size and file-type limits, and use private storage with authorized access.
Prevent spam: authenticate users when appropriate and rate-limit submissions.
Handle offline failures: preserve drafts locally and offer retry when submission fails.
Prevent duplicate submissions: use idempotency keys or another deduplication strategy.
Close the loop: show a reference number and provide a way to contact support or check report status if you offer that capability.
7. Let's tailor the implementation to your app
I can help you build the actual UI, API, database schema, and submission flow. The main thing I need to know first is:
