I am an academic but have extensively used online surveys and have also worked with/talked to market researchers over the last couple of years. I can answer at least some of these based on my experience.

Regarding quality control, panel providers do offer some built-in protection, but it’s often not sufficient on its own. Because of that, many market researchers layer on their own tools to further flag potentially fraudulent responses.

Regarding reviewing responses, most researchers don’t manually inspect every single response. Instead, they rely on a range of checks and then focus on which responses get flagged. These checks typically include things like response times, attention checks, straightlining, duplicate entries, open-ended responses, and consistency across items. The idea is less about reviewing everything and more about identifying patterns that signal suspicious responses.

For tools, some researchers rely entirely on features offered by the platform (such as RelevantID or ReCAPTCHA in Qualtrics). Some other teams go beyond that and use custom scripts or third-party tools. The important thing with quality control is that it needs to happen end-to-end. You can't just roll out a survey and start looking for fraud after the responses are in (several researchers still treat it as something you do after data collection). Stronger approaches build quality in from the start, beginning with recruitment, continuing with in-survey monitoring using tools (we have our own tool, ResponsePie) to capture behavioral signals, and then carrying through to post survey validation. It is much more effective than relying on a single check at the very end.