How do I know if my QA process is failing?

Look at what's reaching players and whether it's catchable. The direct sign is bugs and crashes regularly reaching players, especially significant, catchable ones (not just obscure edge cases), some bugs always slip through, but if catchable bugs routinely reach the field, QA isn't catching enough. A sign is regressions shipping in updates (the new build breaking things that worked before), indicating QA isn't catching regressions. And a telling sign is field crashes you should have caught, crashes on common conditions, in core flows, or in obvious cases that good testing would have found. To assess this, capture crashes and bugs from the field (to see what's reaching players and judge whether QA should have caught it) and track per version (to see regressions shipping). If catchable bugs regularly reach players, regressions ship in updates, or field crashes are ones testing should have caught, your QA process is failing, with gaps in what it covers. The captured field crashes show you the specific gaps, what conditions, devices, or flows QA isn't covering, so you can improve. The key is that QA failure isn't 'any bug reaching players' (impossible to prevent entirely) but 'catchable bugs regularly reaching players, regressions shipping, and crashes QA should have caught', which indicate the process isn't matching the conditions players hit or isn't catching regressions, both fixable by closing the specific gaps the field data reveals.

Why are bugs getting past my QA?

Usually because your QA doesn't match the conditions where bugs occur, or doesn't catch regressions. Common reasons bugs slip through: testing on the wrong setup (a high-end dev machine and one OS, so device- and OS-specific bugs never appear), testing the wrong way (your own predictable playstyle, so bugs from different playstyles and input orders aren't triggered), not covering regressions (testing the new feature but not whether it broke existing ones, so regressions slip by), not covering edge cases (testing the happy path but not unusual inputs and conditions, where many bugs hide), and simply not being able to test everything (the range of devices, conditions, and behaviors is too vast for any testing to cover completely). In short, QA covers your setup and your assumptions, while bugs live in the gaps, the conditions, devices, and paths you didn't exercise. The bugs getting past QA are evidence of these gaps: capturing the bugs that reach players (from the field, with context) shows you what conditions they occurred in, which reveals the specific gaps (maybe they cluster on devices you don't test, or in edge cases you skip, or as regressions you didn't re-check). So bugs get past your QA because your testing doesn't match the conditions where the bugs are, on real varied devices, in edge cases, as regressions, and the way to find the gaps is to let the bugs reaching players show you (capturing them from the field reveals exactly what QA missed and under what conditions). The fix is to close the specific gaps the field data reveals: match testing to real player conditions (test on real varied devices including low-end, in the ways players actually play), cover regressions (run a regression pass over core flows before shipping), cover edge cases (test unusual inputs and conditions), and accept that some bugs will slip through, so use field crash capture as a backstop to catch and learn from them. So bugs get past QA because of gaps between your testing and the real conditions where bugs occur, and capturing the bugs that reach players is how you find and close those gaps, turning field bugs into feedback that improves your QA over time.

How do I improve my QA process?

Close the gaps the field data reveals, match testing to real conditions, cover regressions, and use field crash data as a backstop. First, use what's reaching players to find your gaps: capture crashes and bugs from the field with context, which shows you exactly what QA missed and under what conditions (devices, flows, edge cases), so you can target the specific weaknesses rather than guessing. Then improve the process: test where bugs are most likely (the changes you made, highest risk for new bugs, and the conditions players hit, common paths, real devices especially low-end, since device-specific bugs concentrate there), run a regression pass before shipping (a checklist of core flows plus automated tests, to catch the regressions that are slipping through, this addresses the 'regressions shipping' failure directly), test on real varied devices (to catch the device-specific bugs your dev machine hides), and cover edge cases (unusual inputs and conditions where bugs hide). Automate the repetitive checks (so regression coverage runs every build without manual effort, more reliable than remembering). And critically, use field crash data as a continuous backstop and feedback loop: it catches the bugs that slip through (so you fix them fast) and reveals your gaps (so you improve testing), turning QA from a one-shot gate into a continuous improving loop. So you improve your QA process by using field crash data to find your gaps (what's reaching players and under what conditions), then closing them, matching testing to real player conditions (real devices, common paths, edge cases), covering regressions (a pre-ship regression pass, automated tests), and using field capture as a backstop. The key is that QA can't catch everything (the conditions are too vast), so the goal isn't perfect pre-release testing but a process that catches most catchable bugs (especially regressions and high-impact issues) before release and uses field data to catch and learn from the rest, continuously closing the specific gaps that field bugs reveal. This data-informed approach, let the field bugs show you what QA missed, then improve testing to cover those conditions, is far more effective than generically 'testing more', it targets your actual weaknesses. For a small team without a QA department, this means focused testing (on high-risk areas and real conditions), automation (for repetitive regression checks), and field crash capture (as the backstop and gap-finder) together approximate strong QA, with the field data being what tells you where to focus your limited testing effort.

Signs Your QA Process Is Failing

Quick answer: Watch for bugs and crashes regularly reaching players, regressions shipping in updates, the same kinds of issues recurring, and field crashes you should have caught. QA fails when it misses what players actually hit.

A failing QA process lets bugs reach players that it should have caught, costing you reviews, retention, and trust. Here are the signs your QA process is failing.

Bugs and Crashes Regularly Reaching Players

The direct sign is bugs and crashes regularly reaching players, especially ones you could have caught with better testing. Some bugs always slip through (you can't test everything), but if significant, catchable bugs are routinely reaching the field, your QA isn't catching enough before release, a failing process.

Bugnet captures the crashes and bugs reaching players, so you can see what QA missed. Bugs and crashes regularly reaching players are the direct sign QA is failing, and capturing what reaches the field shows you exactly what QA missed, which both reveals the failure and tells you where to improve (the conditions and areas QA isn't covering).

Regressions Shipping in Updates

A sign is regressions shipping, updates breaking things that worked before. If your updates regularly introduce regressions (the new build worse than the last, features breaking), your QA isn't catching regressions before release, a failure of the regression-testing part of QA specifically.

Bugnet tracks crashes per version, so regressions shipping in updates are identifiable. Regressions shipping in updates are a sign QA is failing to catch regressions specifically, and per-version tracking exposes them (the new build performing worse), pointing at the need for a regression pass before shipping that covers core flows, not just the changed area.

Field Crashes You Should Have Caught

A telling sign is field crashes that you should have caught in testing, crashes on common conditions, in core flows, or in obvious cases that a good QA process would have found. If the crashes reaching players are ones testing should have caught (not just obscure edge cases), your QA process has gaps.

Bugnet captures crashes with context, so you can judge whether QA should have caught them. Field crashes you should have caught are a sign of QA gaps, and the captured context (what conditions, what device, what flow) shows you what QA isn't covering, the common conditions, core flows, or real devices, so you can close the specific gaps.

Watch for bugs and crashes regularly reaching players, regressions shipping in updates, the same kinds of issues recurring, and field crashes you should have caught. QA fails when it misses what players actually hit.